Patent Grant
8620779
This invention relates generally to process control systems and, more particularly, to the use of economic calculations to facilitate and provide better control of a process or plant.
Process control systems, like those used in chemical, petroleum or other processes, typically include one or more centralized process controllers communicatively coupled to at least one host or operator workstation and to one or more field devices via analog, digital or combined analog/digital buses. The field devices, which may be, for example valves, valve positioners, switches and transmitters (e.g., temperature, pressure and flow rate sensors), perform functions within the process such as opening or closing valves and measuring process parameters. The process controller receives signals indicative of process measurements made by the field devices and/or other information pertaining to the field devices, uses this information to implement a control routine and then generates control signals which are sent over the buses or other communication lines to the field devices to control the operation of the process. Information from the field devices and the controllers may be made available to one or more applications executed by the operator workstation to enable an operator to perform desired functions with respect to the process, such as viewing the current state of the process, modifying the operation of the process, etc.
Typically, a process control system operates within a business enterprise that may include several process control plants, component and/or service suppliers and customers, all of which may be distributed throughout a large geographic area, or in some cases, throughout the world. The process control plants, suppliers and customers may communicate with each other using a variety of communication media and technologies or platforms such as, for example, the Internet, satellite links, ground-based wireless transmissions, telephone lines, etc. Of course, the Internet has become a preferred communication platform for many business enterprises because the communications infrastructure is already established, making the communication infrastructure costs for an enterprise near zero, and the technologies used to communicate information via the Internet are well-understood, stable, secure, etc.
A process plant within an enterprise may include one or more process control systems as well as a number of other business-related or information technology systems, which are needed to support or maintain or which are used to effect the operation of the process plant. In general, the information technology systems within a process plant may include manufacturing execution systems such as, for example, a maintenance management system and may also include enterprise resource planning systems such as, for example, scheduling, accounting and procurement systems. Although these information technology systems may be physically located within or near a plant, in some cases a few or possibly all of these systems may be remotely located with respect to the plant and may communicate with the plant using the Internet or any other suitable communication link.
Each process plant may also include user-interactive applications that may be executed on a server or workstation that is communicatively coupled to one or more servers, workstations, or other computers that coordinate or perform the activities of the process control system within the plant. Such user-interactive applications may perform campaign management functions, historical data management functions, asset management functions, batch management functions, diagnostics functions, etc. In addition, each of the process control systems within a plant may include process management applications that may, for example, manage the communications of and provide information relating to alarm and/or other process events, provide information or data relating to the condition of the process or processes being performed by the process plant, provide information or data relating to the condition or performance of equipment associated with the process control plant, etc. In particular, process management applications may include vibration monitoring applications, real-time optimization applications, expert system applications, predictive maintenance applications, control loop monitoring applications, or any other applications related to controlling, monitoring and/or maintaining a process control system or plant. Still further, a process plant or enterprise may include one or more communication applications that may be used to communicate information from the process control system or plant to a user via a variety of different communication media and platforms. For example, these communication applications may include e-mail applications, paging applications, voice messaging applications, file-based applications, etc., all of which may be adapted to send information via a wireless or hardwired media to a desktop computer, a laptop computer, a personal data assistant, a cellular phone or pager, or any other type of device or hardware platform.
Despite the complex information technology systems now typically associated with process plants and the vast array of data associated therewith, the methods of controlling plants in order to optimize plant output have been typically based on the same principles, namely, increasing throughput of the plant within certain quality limits. While there is traditionally an attempt to run the plant optimally from a profit or economic standpoint, it has been difficult to do so because the profit analysis has been performed using financial and accounting information and other data that is, at best, backward looking. For example profitability, costs, inventories, operating efficiencies, waste, scrap, quality, and other industrial management information is often reported in aggregate as much as two weeks to a month after the relevant performance. As a result, this information is not available in a time correlated manner or integrated with other measurements and analyses or external environmental, market factors or information. Thus, current plant control methodology provides little or no support for on-line or up-to-the-minute process or business management and the concept of closed loop control and optimization of any part or aspect of the entities being managed is lacking.
A process control system includes economic models disposed in communication with process control modules, as well as with sources of economic data, and uses the economic models to determine useful economic parameters or information associated with the actual operation of the process plant at the time the plant is operating. The economic models can be used to provide financial statistics such as profitability, cost of manufactured product, etc. in real time based on the actual current operating state of the process and the business data associated with the finished product, raw materials, etc. These financial statistics can be used to drive alarms and alerts within the process network and be used as inputs to process plant optimizers, etc. to provide for better or more optimal control of the process and to provide a better understanding of the conditions which lead to maximum profitability of the plant.
Referring now to
Still further, maintenance systems, such as computers executing the AMS (Asset Management Solutions) system sold by Emerson Process Management or any other device or equipment monitoring and communication applications may be connected to the process control system 14 or to the individual devices therein to perform maintenance and monitoring activities. For example, maintenance applications such as the AMS application may be installed in and executed by one or more of the user interfaces 14A associated with the distributed process control system 14 to perform maintenance and monitoring functions, including data collection related to the operating status of the devices 16. Of course these maintenance applications may be implemented in other computers or interfaces within the process plant 10.
The process control plant 10 also includes various rotating equipment 20, such as turbines, motors, etc. which are connected to a maintenance computer 22 via a permanent or temporary communication link (such as a bus, a wireless communication system or hand held devices which are connected to the equipment 20 to take readings and are then removed). The maintenance computer 22 may store and execute known monitoring and diagnostic applications 23 provided by, for example, CSi Systems or any other known applications used to diagnose, monitor and optimize the operating state of the rotating equipment 20. Maintenance personnel usually use the applications 23 to maintain and oversee the performance of rotating equipment 20 in the plant 10, to determine problems with the rotating equipment 20 and to determine when and if the rotating equipment 20 must be repaired or replaced. In some cases, outside consultants or service organizations may temporarily acquire or measure data pertaining to the equipment 20 and use this data to perform analyses for the equipment 20 to detect problems, poor performance or other issues effecting the equipment 20. In these cases, the computers running the analyses may not be connected to the rest of the system 10 via any communication line or may be connected only temporarily.
Similarly, a power generation and distribution system 24 having power generating and distribution equipment 25 associated with the plant 10 is connected via, for example, a bus, to another computer 26 which runs and oversees the operation of the power generating and distribution equipment 25 within the plant 10. The computer 26 may execute known power control and diagnostics applications 27 such as those provided by, for example, Liebert and ASCO or other service companies to control and maintain the power generation and distribution equipment 25. Again, in many cases, outside consultants or service organizations may temporarily acquire or measure data pertaining to the equipment 25 and use this data to perform analyses for the equipment 25 to detect problems, poor performance or other issues effecting the equipment 25. In these cases, the computers (such as the computer 26) running the analyses may be connected to the rest of the system 10 via a communication line or may be connected only temporarily.
As illustrated in
Of course, any other equipment and process control devices could be attached to or be part of the plant 10 and the system described herein is not limited to the equipment specifically illustrated in
As illustrated in
In the past, the various process control systems 14 and the business systems 35, 36, etc., have not been interconnected with each other or with business systems in a manner that enables them to share data generated in or collected by each of these systems in a useful manner. As a result, the process control functions have operated on the assumptions that the most profitable operating state of the plant is one which maximizes some variable, such as throughput. In some cases, systems have been operated on a profitability basis that was computed or calculated based on previously measured or acquired data, such as data that may be associated with process operation weeks in the past, and not on data associated with the process as currently operating.
To overcome this problem, certain profit or economic models are created and communicatively coupled to the process control network to perform on-line profitability analyses. The economic models automatically communicate with the process control system to access and use process control data and are configured to automatically receive economic data pertaining to the process control system from business systems or other data sources that, in the past, have not been made available to determine profitability of the process control system on an on-line basis.
The economic models may be provided at any place within the process 10, but are illustrated in
While the data communication system 59 is illustrated as being provided in the computer 45, it may be provided or implemented at numerous locations throughout the process network 10 to acquire and process data from any source of data such as the controller systems 14, the monitoring systems 22 and 26, the financial systems 35, 36, etc. The data communication system 59 may also acquire data from various other sources of data, such as from PDAs or other hand-held devices or portable computers, from data historians or from any other electronic source of data, especially profit related data, such as that associated with the sales price of goods being manufactured, contract prices and quantities, costs associated with the manufacture of goods, such as the costs of raw materials, power (such as electricity, gas, coal, etc.), overhead costs, plant operating costs, etc.
If the data communication system 59 is located in the computer 45, it may receive data from the disparate sources of data, such as the controllers, equipment monitoring and financial applications separately using different data formats, or using a common format. In one embodiment, the communications over the bus 42 occur using the XML protocol as discussed in more detail below. Here, data from each of the computers 14A, 22, 26, 35, 36, etc. is wrapped in an XML wrapper and is sent to an XML data server which may be located in, for example, the computer 45. Because XML is a descriptive language, the computer 45 can process any type of data. At the computer 45, if necessary, the data is encapsulated and mapped to a new XML wrapper, i.e., this data is mapped from one XML schema to one or more other XML schemas which are created for each of the receiving applications. One method of providing this communication is described in co-pending U.S. application Ser. No. 09/902,201 filed Jul. 10, 2001, entitled “Transactional Data Communications for Process Control Systems” which is assigned to the assignee of this application and which is hereby expressly incorporated by reference herein. With this system, each data originator can wrap its data using a schema understood or convenient for that device or application, and each receiving application can receive the data in a different schema used for or understood by the receiving application. The computer 45 is configured to map one schema to another schema depending on the source and destination(s) of the data. If desired, the computer 45 may also perform certain data processing functions or other functions based on the receipt of data. The mapping and processing function rules are set up and stored in the computer 45 prior to operation of a suite of data integration applications described herein. In this manner, data may be sent from any one application to one or more other applications.
Generally speaking, the goal of the system described herein is to be able to provide accurate and up-to-date profit or other economic calculations to provide better profit information on which to make decisions when controlling the operation of the plant 10. These economic calculations combine process measurements with software components and business transaction services to provide an on-line, real-time financial, accounting, and quality measurement system utilizing data verification, validation, reconciliation, archiving, alarm and support analyses, reports, displays, inquiry and search functions for the process.
An assumption often made during the design of a control strategy is that maximum throughput equals maximum profit. Although this assumption is sometimes true, especially where the process is constrained by a specific piece of equipment, it is not always true. To provide better economic information, the system described herein may calculate profit based on all or most of the costs actually associated with the product being made at the current time.
Referring now to
The data may be acquired online directly from process equipment, controllers, sensors, transmitters, laboratory equipment, analyzers, video equipment, imaging equipment, microphones and databases, such as market and commodity, feedstock, raw material database, and may be indicative of, for example, flows, temperatures, pressures, compositions and other variables measured or determined by process or equipment measurements or services. The economic data may be, for example, supply cost information, sales and sales price information, tax, duty, shipping and handling costs, etc., personnel status and location etc. as appropriate to the entity being managed.
If desired, local archival storage of data may be used (e.g., within the data collector) to insure that data is not lost should communications or other system components fail or be unavailable for any reason. The data may also be compressed locally by the data collector using any desired data compression technique, such as swinging door or recursive wavelets exception transmission, data transformation, filtering etc. to reduce the required communication bandwidth and to increase the speed and responsiveness of the system while minimizing archival storage requirements.
The data manipulation block 70, which is optional, may include one or more applications that massage the data from the various sources for different purposes. For example, the data manipulation block 70 may use neural networks or other modeling or estimation techniques to provide missing data, e.g., data that is either not present due to missing or malfunctioning measurements, analyzers or instrumentation or measurements that are inherently not directly measurable. While indicated as being performed after data is collected, the data manipulation stage 70 may occur in part or in whole locally in transmitters, analyzers, intelligent equipment or other devices that measure or otherwise acquire the data.
As illustrated in
Of course, there are many other factors to consider and to take into account when constructing models to accurately reflect the economic state of the process. In fact, there are many factors effecting costs including, for example, material costs, equipment efficiency, utilities costs (heating on gas, oi), recycled materials), etc. The models 72 can be used to provide or determine these efficiency numbers and the costs to be used as part of the process control system to monitor and alter the operation of the process to make the process more profitable. Ideally, profit calculations need to include the price being paid for a particular customer order and the costs at the time of manufacture for the product run.
There are, of course, potentially many different aspects in determining profit. For example, profit calculations require detailed knowledge about the price being paid by the customer. If a manufacturing lot is tied to a customer order, then the profit may be computed from that sale price. If the production is continuous, then the profit may be based on product price. Of course, each of the cost and profit calculations will vary depending on the circumstances and the nature of the product being manufactured, as well as the marketing and sales strategy being used. Generally speaking, however, the models 72 are constructed to calculate variability, operating constraints, energy and material balances to determine economic, financial, and equipment health performance on line for fast decision support, control or other uses. The models 72 may also provide the profitability, cost and financial return for each product, grade, campaign or batch run and, in doing so, may use total derivatives to estimate changes from a base value of critical cost or profit. This technique is applicable as an adjunct to direct computation of the desired variable when the errors of measurement or speed of measurement would degrade or slow the result. Such a total derivative methodology allows fast and accurate computation of changes in the desired variable from the measured changes in the component variables. If desired, the models 72 may reconcile calculations to minimize closure errors (i.e., compare the calculations to actual profit realized and alter the calculations to minimize the error between the calculated profit and the actual profit).
If desired, the models 72 may be coupled to a controller engine 76 which can provide intentional perturbations to elements or loops within the process control system for the purpose of verifying, validating and reconciling measurements, analyzers, sensors, etc. as well as operating cost, profitability, quality and equipment health data. In this manner, providing a known perturbation (with attendant known changes in profitability) can be used to test and determine if one or more of the models 72 calculates the same or similar change in profitability, to determine how to reconcile profitability measurements with the calculations made by the models 72.
Additionally, if desired a data manipulation block 70 and one or more economic models 72 may be coupled together within a single process module 73, as illustrated in
The services or service applications 74 may include any number of different applications that use the information or economic calculations produced by the models 72. For example, the service applications 74 may include one or more reporting applications 80 which may provide reports to users in any desired manner. The reports may take the form of real time spread sheets, allowing data to be analyzed, trended, plotted, logged and presented to a user to allow decision support based on current and historical information as well on derived measures such as costs, profitability, return on investment, equipment health, quality etc. The reports may compare historical, current and forecasted relative equipment health, reliability, safety, quality, costs, profitability, throughput, asset utilization, inventories, accounts receivable, accounts payable, days in cash cycle, return on assets, cash flow and/or other parameters of the process control system entities being monitored with other entities, maintenance facilities, companies, processes, plant sites, units, etc. both for current conditions as well as for past and forecasted future performance. If desired, these reports in the form of, for example, spreadsheets, can be embedded into runtime controllers, devices, equipment and users can configure the spreadsheets in any manner currently performed in the art for generating reports. These report generation applications can then be run embedded in the real-time system to automatically produce the desired reports.
The service applications 74 may also include one or more forecasting applications 82 of any desired typed. Advanced forecasting techniques, such as ARIMA, moving window Fourier or other data transformation methodologies, statistical trending, calculation of future response based on prior actions, current measurement values and real-time models (such as process models) may be used to compute future values of any of the measurements, compositions, healthy data, costs, profitability etc. This forecasted future data may be provided to controllers, alarming applications, etc. to enable anticipatory alarming, control, emergency response etc. not allowed by current methods or systems.
Still further, one or more diagnostic applications may be provided to perform diagnostic procedures using economic data in a manner that provides a more complete diagnostic analysis. In one example, a diagnostic application may access dynamic parameters associated with function blocks or other control blocks within the control system, such as DeltaV and Fieldbus function blocks, and provide high speed analysis on this data. In this application, a selected number of parameters may be accessed during or after each execution cycle of a control module or function block. The diagnostic application may trend these values or analyze these values using any desired power spectrum, correlation and statistical techniques. Also, the diagnostic application may allow the user to directly access other diagnostic data provided by other diagnostic applications, such as the AMS diagnostics. For control blocks, the diagnostic application may provide access to diagnostic data associated with, for example, tuning applications, etc.
Of course, the diagnostic application may provide additional analysis tools such as those that perform power spectrum, cross correlation, and auto correlation on any desired variables. The diagnostic application may still further direct the customer to the appropriate solution, such to one or more tuning applications, etc, may utilize high-speed data provided by Fieldbus trend objects or virtual trend objects based on traditional input/output (I/O) in the controller, may collect trend information on-demand or perform any other desired procedures.
If desired, the diagnostic applications may support continuous monitoring and detection of abnormal conditions that may exist in control blocks and input/output blocks or other blocks within the process control system. Such a diagnostic application is described and illustrated in U.S. Pat. No. 6,298,454, which is hereby expressly incorporated by reference herein. Using this technique, it is possible to identify blocks that contain one or more abnormal conditions for more than a specified percent of time. In addition, the PO or control blocks that exhibit high variability may be identified.
In general, this application may include tools to allow a user to quantify the cost of process variability based on, for example, total and capability standard deviations, user defined limits and the cost of the product. The application may also generate pre-defined reports that may be directly used by a user to justify improving control. As described in U.S. Pat. No. 6,298,454, this tool can include a status parameter that allows detection of abnormal conditions to be suspended such as when the module is not being used, to prevent false alarms from being generated when a process is off-line, in startup, etc. This tool may also allow plant performance and utilization to be saved by a data historian to support charting or plotting by the month, year, etc., with this data being available by plant area, process cell or other logical entity. This diagnostic application may, of course, provide predefined reports that summarize and detail bad conditions, provide dynamos to allow conditions and economic calculations for a unit or other entity to be easily summarized at an operator screen and to provide context sensitive help for process analysis.
Still further, the service applications 74 of
The advanced control applications may also include a scheduler application that uses one or more of on-line historical, current and forecasted data in conjunction with one or more of equipment status, order status, economic data, environmental data, regulatory data, market data, competitive data, etc. to select and/or schedule the products or grades to be manufactured, the maintenance to be performed, or the equipment or the arrangement of equipment to be used to manufacture a product most economically.
The service applications 74 may also include an alarm/alert application that may be used to provide alarms or alerts based on the output of the models 72. In particular, the alarm/alert application may compare certain economic variables, such a profitability, etc. with fixed or preset ranges or values and provide an alarm or alert if the profitability or other economic variable falls outside of the range or below or above the preset value. These alarms (or alerts) may be sent to any desired user in any desired manner, such as wirelessly, via the process control communication network, the business network, a pager network, e-mail, etc. As part of this process, a diagnostic application may include an agent that recommends advanced control tools that should be used to address problems areas. Still further, the alarm or alert application may allow a user to assign different priorities to measurements or control blocks. In this case, an alert, mail message or pager notification can be issued when an abnormal condition is detected in a block in an active unit with the priority set by the user or based on the priority set by the user.
While not specifically illustrated in
While
Referring now to
More specifically, the web services-based communication system and technique described herein includes a communications engine that performs message routing, scheduling and configuration functions for a plurality of clients or web-services and, for this particular purpose, for providing on-line or up-to-date financial or profit data to the process control system 14 of
The web services-based communication system and technique described herein may include a graphical user interface that enables one or more users to configure and/or add web-services to the system and to create a highly personalized profile that causes the communications engine to route selected process control information and other information to be displayed to the user via the graphical user interface in a manner desired by the user. This feature enables a multitude of different profitability data associated with different plant environments to be provided to the process control system for on-line profitability purposes.
In any event, the web services, the communications engine and the graphical user interface may communicate with one another via a network such as, for example, the Internet using an extensible markup language (e.g., XML) or any other similar language that enables applications, services and/or systems to communicate with one another without requiring the development of custom communication interfaces or drivers.
Generally speaking, the web-services described herein may include data services or sources, which may be business systems, that collect and store data needed to make current profitability analyses and data subscribers or consumers which may be, for example, applications implemented in the process control or process maintenance systems, to perform on-line profitability calculations. On the other hand, the data services or sources may be process control systems or applications, asset management systems or applications, equipment condition monitoring systems or applications, diagnostic systems or applications, or any other system or application that acquires or generates information or data associated with the operation of a process control system or plant as well as business systems or financial data sources. Likewise, the data subscribers or consumers may include user-interactive applications such as, for example, diagnostic applications, control optimization applications, reporting systems including paging systems or applications, e-mail systems or applications, file generation systems or applications, etc.
As will be understood, each of the data services and data consumers may be an application or system that includes a web services interface. As is well known, a web services interface may use an extensible markup language such as XML in conjunction with a messaging protocol such as, for example, simple object access protocol (SOAP) and a communications transport protocol such as, for example, hypertext transport protocol (HTTP). Because web services are somewhat generic in nature (i.e., the behavior or characteristics of the communications via a web server interface are independent of any underlying application or system), data services and data consumers can be easily connected to (i.e., communicate with) the communications engine without having to create any custom communication interfaces, as typically was the case with prior systems. Additionally, the communications engine may be easily adapted to discover or find (either automatically or at the direction of a user) web services that are available for connection to the communications engine. For example, the communications engine may use a web services discovery tool or service such as, for example, universal discovery description and integration (UDDI), or any other type of web services discovery tool or service to identify available web services.
Still further, the web services-based communication system and technique described herein provides a system architecture that results in efficient and robust data collection, data analysis and data communication. In particular, the communications engine may request data from the data services as it is needed by the communications engine. Alternatively, one or more of the data services may be configured to asynchronously notify the communications engine as new data or information becomes available. In either case, efficient use of communications resources (e.g., communication links, processing capacity within the communications engine, etc.) may be achieved by the system and technique described herein. In particular, only newly available and/or data needed by the communications engine is conveyed between the various data services and the communications engine, as opposed to collecting all available data from the data sources regardless of whether the data was needed, as was the case with prior systems.
Further, with the web services-based communication system and technique described herein, the data services may perform complex analyses and may communicate analysis results (in addition to raw data, if desired) to the communications engine and, in turn, to the graphical user interface and/or other data consumers. Thus, because the web services-based communication system and technique described herein is adapted to transmit only requested and/or newly available data and, if desired, only analysis results (as opposed to all data required to perform the analysis at a central location such as the communications engine or the graphical user interface application), the web services-based communication system and technique described herein facilitates highly efficient use of available communication network bandwidth.
The web services-based communication system and technique described herein also provides a high degree of data robustness. In particular, each of the web services may be responsible for data backup, storage of data history, etc. As a result, a communications and/or power failure at the communications engine and/or the graphical user interface will not result in the catastrophic loss of data, and recovery of the system can be quickly and easily accomplished upon restoration of power and/or communications to the communications engine and/or the graphical user interface. Likewise, failure of a particular web service will not result in a catastrophic failure of the entire system, and when the failed web service recovers, the system can easily begin communicating with that web service without having to be reconfigured, restarted, etc.
Each of the data services 102-106 may include field devices, controllers, workstations, etc. that are communicatively coupled via one or more communication networks and/or other types of communication links. If desired or necessary, each of the data services 102-106 may perform process control activities such as, for example, execution of control loops, may perform diagnostic activities, may perform asset management activities, etc. for a collection of equipment or devices associated with a particular process plant or portion of a process plant. Further, each of the data services 102-106 may also perform data historian functions, may include redundant or failsafe devices, may perform data analysis activities, all of which are generally well known in the art and, thus, are not described in greater detail herein. Still further, and for the purposes discussed herein, the data services 102-106 may include computers or other data acquisition devices of any type that collect, store, generate, etc. financial data needed to make profit determinations within a process plant.
Preferably, the data services 102-106 include respective web services communication interfaces 122-126, which enable the data services 102-106 to communicate within the system 100 as web services when connected to the network 120. The web services communication interfaces 122-126 may be implemented using XML messages that have been formatted using SOAP, or any other desired message protocol, and which have been encapsulated for transmission using a network transport protocol such as, for example, HTTP.
In general, the data consumers 108-112 are systems or applications that perform activities or functions that consume process control data and/or which convey data or information provided by the data services 102-106 to system users or operators. In this instance, the data consumers 108-112 may be the models 72 of
As illustrated in
In general, the router 136 performs message routing functions that receive messages from one or more of the web services, which includes the data services 102-106 and the data consumers 108-112, coupled to the network 120 via the connections 142-152 and route these received messages to appropriate destinations, which may be any of the web services (e.g., the data services 102-106 and data consumers 108-112) coupled to the network 120. More specifically, the router 136 may function in a manner similar or identical to an XML transaction server. The router 136 may use input and output schemas in conjunction with business rules, data manipulations, etc., all of which may be stored in and retrieved from the database 138, or which may be provided by another one of the web services coupled to the network 120, to route XML messages received from one or more of the web services coupled to the network 120 to another one or other ones of the web services.
By way of example, the data service 102 may generate alarm or alert information that needs to be conveyed to the data consumer 112, which may be a communication system or application such as an e-mail system or application. When the alert or alarm information is generated, the data service 102 uses its web services interface 122 to wrap the alert or alarm information in an XML schema to form an XML message, encapsulates the XML message using HTTP and sends the XML message to the network 120. The network 120 uses the HTTP encapsulation to route the XML message, using known techniques, to an appropriate one of the data service connections 142-146 available within the information server 114. The communications engine 140 receives the XML message from the one of the data service connections 142-146 that received the XML message and the router 136 uses an appropriate input schema (retrieved from the database 138) to decode the XML message. The router 136 may then, based on the content of the decoded message and one or more rules and/or data manipulations, map the contents (or a portion of the contents) of the message to an appropriate output schema associated with the destination (i.e., the data consumer 112), which may also be retrieved from the database 138. The router 136 may then encapsulate the mapped alarm or alert message (which is also an XML message) using HTTP and may send the encapsulated message to the data consumer 112 via the one of the data consumer connections 148-152 associated with the data consumer 112 and the network 120 to the data consumer 112. The data consumer 112 then receives the alert or alarm information via its web services interface 132 and may generate an e-mail message that conveys the alert or alarm information to one or more designated or applications.
Thus, the router 136 is adapted to process messages, which are preferably, but not necessarily, expressed using XML or some other extensible markup language, received from a plurality of web services such as, for example, data services, via a communications network and routes or sends these messages to other web services that are also coupled to the communications network. Because all of the data generation and data consuming applications or systems that make up the system 100 are configured to communicate as web services, the information server 114 and, more particularly, the communications engine 140, can dynamically establish communications with any of the data generation or consuming applications or systems by adding or removing connections (e.g., the connections 142-152) without having to generate any custom communication interfaces or drivers and without having to halt the operations of the communications engine 140 (i.e., connections to applications can be established without disturbing communications between already connected web services and the communications engine 140). To the contrary, because each of the data services 102-106 and each of the data consumers 108-112 includes a web services interface and because the communications engine 140 is adapted to communicate with web services, it is not necessary for the information server 114 or for any of the web services coupled to the network 120 to have any detailed knowledge about the operation of the systems or applications being performed by any of the other web services to enable information to be exchanged between the web services via the information server 114.
In general, the scheduler 134 performs scheduling functions that enable the communications engine 140 to periodically request information from one or more of the data services 102-106. More specifically, the scheduler 134 may establish periodic requests for information or data from one or more of the data services 102-106, particularly where the information requested is of a type that would not generate an event. For example, if one of the data consumers 108-112 periodically needs information or data such as costs or prices associated with raw materials or finished products from one of the data services 102-106, the scheduler 136 may be configured to periodically send messages requesting this data to the one or ones the data services 102-106 which may store or have access to this data. The one or ones of the data services 102-106 receiving the request may subsequently send the data to the information server 114 in the form of an HTTP encapsulated XML message, which may then be routed by the router 136 to the appropriate ones of the data consumers 108-112, such a one of the models 72, via the network 120.
The discovery service 118 may also include a web services interface 154 that enables the discovery service 118 to communicate with the information server 114, the data services 102-106 and/or the data consumers 108-112, as desired. The discovery service 118 may be a web services directory or registry service such as, for example, UDDI or any other similar or different web services directory or registry. As is well known, UDDI enables a web service to discover and obtain interface and/or communications information about another web service, which may then be used by the discovering web service or server to automatically establish communications with the discovered web service.
The system 100 may use the discovery service 118 to automatically or dynamically establish communications between the information server 114, the data services 102-106 and the data consumers 108-112, without requiring intervention from a system user, or operator, a programmer, etc. By way of example only, at initial start-up or power-up of the system 100, the information server 114 and, in particular the communications engine 140, may communicate with the discovery service 118 to determine what web services are coupled to the network 120 and available for use by the system 100. The communications engine 140 may store available web services and communications interface information pertaining to available web services in the database 138. The information related to available web services may then be automatically and periodically updated by the communications engine 140 so that if a web service becomes unavailable, becomes available, and/or if communications interface information relating to any available web service changes, such information may be reflected in the database 138 for use by the communications engine 140 in routing and scheduling communications.
Each of the web services that is discovered, licensed (if required) and coupled to the information server via the network 120, may have a unique service identifier (SID) associated therewith. In this manner, the communications engine 140 may store communications interface information and other information pertaining to each of the available web services in a table or any other data structure within the database 138. The table or other data structure may subsequently be used by the router 136 and the scheduler 134 to route messages received from particular services and to schedule information requests from particular services.
The graphical user interface 116 performs functions that enable a system user or operator to selectively view information provided by the data services 102-106 and/or the data consumers 108-112, to configure communications (e.g., to schedule information requests, establish routings, etc.) within the system 100 and/or to generally interact with applications or services that are communicatively coupled to the network 120 via the information server 114. The type of information presented by the graphical user interface 116 and the manner in which information may be presented by the graphical user interface 116, may vary from user to user based on profiles that are defined by the users and stored in the database 138. By way of example, a user may initially interact with the system 100 via the graphical user interface 116 to define a profile and the information or content that the user wants displayed. A particular user's profile may include information associated with the user's organizational role (e.g., manager, engineer, executive, etc.), the hours that the user works (e.g., the user's shift), the personal preferences of the user, the manners and times in which the user may be contacted off-site or on-site, etc. Additionally, the user profile information may be sent by the graphical user interface 116 to the information server 114, which may store the user profile information in the database 138.
In addition to user profile information, configuration information associated with each user may also be stored in the database 138. A user may interact with the graphical user interface 116 to establish the manner in which the user wants to view information from the data services 102-106 and the data consumers 108-112, the manner in which the user wants information to be conveyed between the various web services coupled to the network 120, etc. To store configuration information for each user, a table may be generated in the database 138 so that each user is assigned a unique identifier or a user ID (UID) and a user's desired configuration for each of the available web services is stored along with the UID and the SIDs of the services.
By way of example, when a user logs into the graphical user interface 116, they may be authenticated using their username and password. In turn, the username and password information may be used to create or may be associated with a security identifier (e.g., the UID). The graphical user interface 116 may send the UID for that user to the information server 114, which will then retrieve the profile and configuration information associated with that UID from the database 138. The profile and configuration information may then be used by the communications engine 140 to establish the manner in which messages will be routed, the manner in which the scheduler 134 requests information from the data services 102-106, the type and manner in which information will be displayed by the graphical user interface 116, etc. while that user or at least that user's UID) remains in control of the graphical user interface 116.
While the graphical user interface 116 (and the software application or applications associated therewith) is depicted in
The system 200 shown in
The personal data assistant web service 214 may receive messages containing information from data sources such as the web services 202-206 and may convey information contained in these messages to one or more personal data assistant computers, each of which may be carried or operated by a different person or user. In this manner, a system user may, if desired, configure the system 200 to send selected detailed information about the operation of a process control plant or system including, for example, diagnostic information, profit information, cost information, advanced control and condition monitoring information, asset management information, or any other information to their personal data assistant computer.
The file system web service 216 may receive messages containing process control data, diagnostic data, profit or economic data, etc. from one or more of the web services 202-206 via the information server 114 and the network 120 and may store the information contained therein in one or more data files, which may subsequently be accessed, transmitted, printed, displayed, etc.
The CMMS web service 212, the campaign management web service 218, the diagnostics web service 220 and the optimizer web service 221 may be characterized as user-interactive applications or services. The CMMS web service 212 may, for example, enable users to configure the type of and the manner in which alert or alarm information should be conveyed to them. Additionally, the CMMS web service 212 may perform functions that generate work orders (either in electronic or paper form) that may be printed or displayed at a central location such as, for example, a maintenance department within a process plant, that may be conveyed directly to the persons responsible for responding to the work orders, etc. Still further, the CMMS web service 212 may generate orders for replacement parts that may be needed to repair or otherwise maintain a process control plant associated with the system 200. The part orders generated by the CMMS web service 212 may, in turn, be sent in the form of HTTP encapsulated XML messages to a business system such as, for example, a procurement system (not shown) that is communicatively coupled to the network 120.
The campaign management web service 218 may include any desired campaign management application or applications that are used to define and manage the execution of one or more batch processes within a process control plant. The diagnostics web service 220 may include one or more applications that function to perform diagnostics within the process control system using profit data or profit calculations obtained on-line within the process plant from, for example, one or more business data systems. The optimizer web service 221 includes one or more optimizer applications used to optimize the control of the process plant based on particular constraints and optimized variables, which may be profit related variables in this case. Both the campaign management applications and optimizer applications are well known and, thus, are not described in greater detail herein.
It is important to recognize that data or information typically flows from web services such as the asset management web service 202, the advanced control and condition monitoring web service 204 and the business or financial information web service 205, all of which typically acquire data, analyze data and generate analysis results data, to primarily data consuming web services such as, for example, the e-mail web service 208, the paging web service 210, the CMMS web service 212, the personal data assistant web service 214, the file system web service 216, the campaign management web service 218, the diagnostic web service 220 and the optimizer web service 221. However, any one of the web services 202-221, the discovery service 118 and the graphical user interface 116 may send messages or exchange information with one or more of the other web services 202-221, the discovery service 118 and the graphical user interface 116 via the network 120 and the information server 114.
In operation, the system 200 may initially not have knowledge of any of the web services 202-221, may not have any user configurations or profiles stored within the information server 114 and, thus, may not initially route any messages from any of the data sources (i.e., the web services 202-206) to any of the data consumers (i.e., the web services 208-221). The information server 114 may then use the discovery service 118 to discover each of the available web services 202-221, which are coupled to the network 120. In particular, the information server 114 may retrieve communications interface information (e.g., schema information, network address information, etc.) from the discovery service 118 and may store this information within its database 138 (
Users may interact with the graphical user interface 116 to create user profiles and configurations which are stored within the database 138 together with a UID for each user. The user profiles and configurations may be used by the graphical user interface 116 to control the type and manner in which data will be displayed to each user and may be used by the information server 114 to control the manner in which messages are routed between the web services 202-221. In this manner, when a particular user enters their authentication information (e.g., username and password) into the graphical user interface 116, the information server 114 retrieves the unique security identifier (i.e., the UID) associated with that user. The information server 114 may then use the UID to retrieve the configuration information associated with that user's UID from the database 138 and configures the router 136 and the scheduler 134 to operate so that messages are automatically conveyed to the graphical user interface 116 in the manner specified by that user's configuration and/or profile or by the application being accessed by the user. In the case where the graphical user interface 116 is implemented using an Internet browser application, the messages conveyed by the information server 114 to the graphical user interface 116 are preferably based on hypertext markup language (HTML), rather than XML, so that a conventional browser application may be used to display information to the user in the desired format. As different users log into the graphical user interface 116, the information server 114 automatically routes messages in a manner that will supply the information to the graphical user interface 116 as specified by that user's configuration. Thus, as each user uses the graphical user interface 116, the format and content of the information displayed will automatically be varied to suit that user's configuration and/or profile or application.
While the content and format of the information displayed within the graphical user interface 116 may vary as different users log into or use the graphical user interface 116, the various message routing configurations associated with the data consuming web services (e.g., the web services 208-221) may remain active for each of the user profiles stored within the database 138 (
Likewise, applications, such as the data consumer applications, that are configured to receive information from other web services may do so in a continuous manner, regardless of whether a user is logged on or not. For example, an alert or alarm may be generated by a process control system or by a model or alarming application based on, for example, a profit analysis, and the alarming application may convert the alarm or alert into an XML message, encapsulate the XML using HTTP and send the message via the network 120 to the information server 114. The information server 114 may then process the received alarm or alert message and may thereby determine, using the user profiles and schemas stored in the database 138, to whom and in what manner the alert or alarm message should be conveyed. The information server 114 will then cause the router 136 (
Additionally, the advanced control and condition monitoring web service 204 includes a web services block 256 and a web services interface 258, both of which function to enable the process control system 255 to exchange information or messages with other web services via the network 120 (
As will be understood, the I/O subsystems block 250 includes controllers, I/O devices and field devices connected thereto. The process control subsystems block 252 is preferably, but not necessarily, implemented using one or more software routines or applications that may be executed within one or more of workstations of other computer systems. By way of example, the process control subsystems block 252 may include software routines or applications that carry out control functions, operator interface functions, alarms and events processing functions, real-time data processing functions, or any other desired functions.
The embedded advanced control and condition monitoring block 254 may be implemented using a plurality of software routines or applications that process data and other information associated with the operation, condition, etc. of a process control system such as, for example the process control system 14 of
As illustrated in
As described in more detail below, the web service clients 266-272 receive incoming messages that contain requests for service, parse these incoming messages and dispatch the requests for service to appropriate methods available within the web services block 256. Preferably, but not necessarily, the web service listeners 266-272 receive service requests and also provide service responses. Additionally, the web service listeners 266-272 preferably, but not necessarily, convey alarm and event data, process condition data and equipment condition data using XML.
The web services interface 258 manages communications between the various web services within the web services block 256 and the information server 114, which may communicate with a process control system via the web services interface block 258 as a web client. In general, the web services interface block 258 provides a hosting or web server environment (i.e., a common interface) that enables a plurality of relatively technically diverse information systems such as, for example, manufacturing execution systems, enterprise resource planning systems, business systems, standalone computers, PDAs, cell phones, pagers, etc., or any other system associated with a process plant, customer, supplier, etc., to send and receive process control information or data to the process control subsystems block 252 and the advanced embedded control and condition monitoring block 250. In particular, the web services interface 258 is adapted to listen for incoming HTTP requests, perform security checks involving user authentication/verification, look up connection information and dispatch authorized HTTP requests to establish a connection with an appropriate one of the web service clients 266-272 available within the web services block 256, facilitate automatic recovery from service, hosting environment and system failures, and provide administrative facilities for deploying, monitoring and controlling services and managing resources such as, for example, processes, threads and shared state on behalf of each service.
In response to HTTP-based requests, the web services interface 258 may authenticate the requesting entity (e.g., another other web service) as a proper client of the web services block 256. Client authentication may be based on an identity of a user (i.e., based on the UID and/or some other identifier), the identity of the requesting entity itself, a terminal location or any other suitable identification technique. If the requesting entity is authenticated as a proper client, the web services interface 258 establishes a connection with an appropriate one of the web service listeners 266-272 within the web services block 256. For example, in the case that the requesting entity is interested in business information from the MMS 262, the web services interface 258 may establish a connection with a web service associated with the web service listener XML transaction server 270. Once such a connection is established, any type of business or maintenance system data from the MMS 262 and transmitted to the server 270 may be obtained and be communicated via one of the web service clients 272-276 to the process control system using HTTP packets containing XML formatted data.
On the other hand, when a device within the I/O subsystems block 250 generates a device alert or alarm such as, for example, a process control alert indicating a drop below acceptable profitability, the block 254 including this alarming application sends this alert to the web services block 256. In turn, the web service associated with the web service listener 272 converts the received maintenance alert into an XML format and then sends the XML formatted alert information or data to a user via the network 120. The user may be within the business system 260 or one of the other data users, such as a PDA, a pager, etc. Of course, as described above, appropriate input and output schemas need to be in place to properly convey the device alert information from the information server 114 within the block 256 to the appropriate data consuming applications or web services.
It should be recognized that the web services framework or architecture provided by the web services interface 258 and the web services block 256 enables any authenticated client to send or exchange information or data with the I/O subsystems block 250 and the process control subsystems block 252 using XML-based communications encapsulated within HTTP packets. Thus, any device that can execute an internet browser application can communicate with the process control system 255 via the web services interface 258 and the web services block 256. For example, a remote terminal or a hand held computer device adapted to execute a browser application may communicate with the control system 255 via the Internet or any other conventional or suitable communication link.
In one example embodiment, a diagnostics application may be configured to receive and use business or financial data to provide better or more accurate diagnostics fora process control system based on the profitability of the process control system. In particular, the diagnostics engine described in U.S. Pat. No. 6,298,454, which is hereby expressly incorporated by reference herein, may be used as a diagnostics engine for a process control system. As explained in U.S. Pat. No. 6,298,454, the diagnostics engine may be executed within one of the user interfaces of the process control network and be configured to receive appropriate data from the process control network regarding the on-line operation of the devices, controllers, etc. within the process control system. However, this same diagnostics application may include one or more economic models or be communicatively coupled to such economic models (such as those illustrated in
In any event, the economic model(s) may determine one or more outputs establishing an economic parameter associated with the operation of the process plant, such as financial or monetary aspects associated with the operation of the process plant, including the calculating and reporting efficiency, costs, savings, profits, etc. either in the aggregate or based on changes within the operation of the plant. For example, in the diagnostic application described within U.S. Pat. No. 6,298,454, an economic model may be used to assess the health and performance of instrumentation. This may occur by detection of abnormal conditions and variability in field devices and determining the costs or loss in efficiency that results from such abnormal conditions to enable a process control operator to determine the abnormal conditions that are most directly or significantly effecting the bottom line of the plant from a financial viewpoint.
As illustrated in
Of course, the (e.g., automatic) use of the economic parameters developed by the economic models in the control of the process plant (e.g., in the automatic control of the process plant) may effect the diagnostic variables determined by the diagnostics application to thereby reduce or eliminate the problems detected by the diagnostic application. As will be understood from U.S. Pat. No. 6,298,454, some example diagnostic variables that may be used are variability parameters (such as the variability of signals within control loops), an operational mode indication associated with the mode of one or more control blocks within a control loop, a limit indication indicating that one or more signals within a control loop have reached a preset limit, etc.
As noted in U.S. Pat. No. 6,298,454, a parameter may be added to I/O and control blocks to support prevention of false detection of abnormal conditions when a process is off-line, in startup, etc. The enabling and disabling of elements of the process control system reporting may be performed at a unit, equipment, cell, area or system level and may be performed using an explorer view to select the item to be enabled or disabled within a configuration menu. Of course, the reporting of abnormal conditions enable and disable parameter may be added to modules that may be configured for detection and reporting for units, cells, areas, systems, etc. The Enable/Disable parameter may also be written to by other applications or other blocks to turn detection and reporting on or off. Still further, the diagnostics application or a reporting application may provide on-line documentation to report costs associated with process variability.
As an example, using the diagnostic application described in U.S. Pat. No. 6,298,454 modified to include (e.g., to communicate with) the economic models and reporting described herein, a customer may configure predefined calculations to determine the savings obtained by, for example, reducing process variability. The cost savings may utilize the total and capability standard deviation determined by the diagnostics application and the calculated savings may be viewed over a user selected timeframe (that is supported by diagnostic application, e.g., an hour, a shift, a day, etc.) The calculated savings may also be displayed with a graphical representation that shows the current standard deviation, best operating point or limit, and the shift in variation and operating point that is possible with better control and the associated cost savings.
The calculations that have been configured may be viewed and easily accessed in an explorer-like view or may be included automatically on a user or operator display. Cost savings associated with deviating from best operating point may also be automatically calculated based on user configuration of the controlled parameter, the unit throughput, best operating point, and cost per throughput unit associated with deviation in the controlled parameter. Cost savings associated with deviating from a maximum or minimum limit may be calculated based on user configuration of the controlled parameter, limit value, unit throughput, and cost per throughput unit associated with deviation in the controlled parameter.
The diagnostic application may automatically access the throughput and the controlled parameters configured in a calculation and determine their average value over each of the reporting periods supported by the diagnostic application. An overview report of all cost saving calculations may be printed for a selected timeframe and this report may summarize the standard deviation, estimated improvement in standard deviation, and cost saving for each loop. A detailed report may be printed for each calculation that shows the standard deviation and improvement graphically along with the saving.
After having configured a savings view or calculation, and during operation of the process, the diagnostics application may collect the needed process control and financial data in the manner described above and may use the saving configuration to present an on-line savings view, such as that of
Moreover, if desired, any information, such as the savings information, plant efficiency, etc. can be reported to plant personnel and management using the mechanisms available as part of the control system (e.g., graphic displays, events and alarming and reporting applications, etc.) or via another computer or display (such as handhelds, pagers, PDAs, etc.) using the data communication system described above.
Of course, while a diagnostic application has been described above as including models configured to receive financial data to perform economic calculations within a process control system, other types of applications can use these or other models for many other purposes. For example, optimizer, reporting and alarming applications may use economic models to provide better performance and reporting for a process control system from the standpoint of maximizing actual profit within the plant. Likewise, other diagnostic applications could use financial information for other reasons as well to, for example, determine other financial measures besides those explicitly discussed herein.
Still further, if desired, the service applications 74 (
While the web services-based communication system and economic models and process control applications described herein have been described as being implemented using an XML-based server, this combined system can be implemented using any other suitable transactional data language on any suitable hardware platform. Further, although the functions of the information server described herein are described herein as being implemented primarily as software, some or all of these functions may be implemented in hardware, firmware, etc. Thus, the web services-based communication system and technique described herein may be implemented in a standard multi-purpose processor or using specifically designed hardware or firmware as desired. When implemented in software, the software routines discussed herein may be stored in any computer readable memory such as on a magnetic disk, a laser disk, or other storage medium, in a RAM or ROM of a computer or processor, etc. Likewise, the software may be delivered to a user or a process control system via any known or desired delivery method including, for example, on a computer readable disk or other transportable computer storage mechanism or over a communication channel such as a telephone line, the Internet, etc. (which are viewed as being the same as or interchangeable with providing such software via a transportable storage medium).
Still further, while the economic model analysis has been generally described herein as having a computer model that models the economic operation of a process plant based on economic data and process control data located at the process plant, a service provider could, for a fee, provide a service of collecting the process control data (or other process plant data) and the economic data from the process plant on a regular basis (e.g., a periodic, a regularly scheduled basis, etc.) and then use a computer model to produce an output related to the operation of the plant. The output could be analyzed or used in any manner described above to determine one or more actions to be taken or performed in the process plant, including any of the control, alarming, reporting, diagnostic, optimization, etc. actions discussed above. These one or more actions, which could include providing information to be displayed to plant personnel, could then be transmitted back to the process plant to be implemented or displayed to the appropriate person or decision maker, such as a control operator, a business manager, a maintenance person, etc. The service provider may be communicatively connected to the process plant in any desired manner, such as via the Internet, the World Wide Web, a LAN or WAN connection, a telephone connection, etc. If desired, one or more servers may be set up to collect the economic data and the process plant or process control data, as indicated above, and then to automatically forward or send this data to the service provider site for analysis. Of course, the service provider may charge a fee for any or all of collecting the data, running the computer model, analyzing the output of the model to determine one or more actions to be taken in the process plant and then communicating these actions to the process plant for display or implementation. It will be understood that the computer model or other software at the service provider site (which may, if desired, be physically located at the process plant or remotely from the process plant) can implement any of the functions described above with respect to
Thus, while the present invention has been described with reference to specific examples, which are intended to be illustrative only and not to be limiting of the invention, it will be apparent to those of ordinary skill in the art that changes, additions or deletions may be made to the disclosed embodiments without departing from the spirit and scope of the invention.
This is a divisional application of U.S. patent application Ser. No. 10/798,101, entitled “Economic Calculations in a Process Control System” (filed on Mar. 11, 2004) which claims the benefit of U.S. Provisional Patent Application No. 60/491,066 (filed on Jul. 30, 2003) and which is a continuation-in-part of U.S. patent application Ser. No. 10/123,445, entitled “Web-Services Based Communications for Use With Process Control Systems,” (filed on Apr. 15, 2002), and which is also a continuation-in-part of U.S. patent application Ser. No. 09/953,811, entitled “Fusion of Process Performance Monitoring with Process Equipment Monitoring and Control” (filed on Sep. 7, 2001) which claims the benefit under 35 U.S.C. §119(e) of U.S. Provisional Application Ser. No. 60/273,164, entitled “Asset Utilization Expert in a Process Control Plant” (filed Mar. 1, 2001). The entire disclosure of each of these applications is hereby expressly incorporated by reference herein.
| Number | Name | Date | Kind |
|---|---|---|---|
| 3096434 | King | Jul 1963 | A |
| 3404264 | Kugler | Oct 1968 | A |
| 3701280 | Stroman | Oct 1972 | A |
| 3705516 | Reis | Dec 1972 | A |
| 3981836 | Pangle, Jr. et al. | Sep 1976 | A |
| RE29383 | Gallatin et al. | Sep 1977 | E |
| 4058275 | Banks et al. | Nov 1977 | A |
| 4088413 | Rossignol de la Ronde et al. | May 1978 | A |
| 4099413 | Ohte et al. | Jul 1978 | A |
| 4322976 | Sisson et al. | Apr 1982 | A |
| 4337516 | Murphy et al. | Jun 1982 | A |
| 4408285 | Sisson et al. | Oct 1983 | A |
| 4425798 | Nagai et al. | Jan 1984 | A |
| 4435770 | Shiohata et al. | Mar 1984 | A |
| 4493042 | Shima et al. | Jan 1985 | A |
| 4517468 | Kemper et al. | May 1985 | A |
| 4527271 | Hallee et al. | Jul 1985 | A |
| 4530234 | Cullick et al. | Jul 1985 | A |
| 4607325 | Horn | Aug 1986 | A |
| 4635214 | Kasai et al. | Jan 1987 | A |
| 4642782 | Kemper et al. | Feb 1987 | A |
| 4644478 | Stephens et al. | Feb 1987 | A |
| 4644749 | Somes | Feb 1987 | A |
| 4649515 | Thompson et al. | Mar 1987 | A |
| 4657179 | Aggers et al. | Apr 1987 | A |
| 4683542 | Taniguti et al. | Jul 1987 | A |
| 4707796 | Calabro et al. | Nov 1987 | A |
| 4734873 | Malloy et al. | Mar 1988 | A |
| 4758964 | Bittner et al. | Jul 1988 | A |
| 4763243 | Barlow et al. | Aug 1988 | A |
| 4764862 | Barlow et al. | Aug 1988 | A |
| 4770543 | Burghoff et al. | Sep 1988 | A |
| 4777585 | Kokawa et al. | Oct 1988 | A |
| 4819233 | Delucia et al. | Apr 1989 | A |
| 4831564 | Suga | May 1989 | A |
| 4843557 | Ina et al. | Jun 1989 | A |
| 4853175 | Book, Sr. | Aug 1989 | A |
| 4873655 | Kondraske | Oct 1989 | A |
| 4885694 | Pray et al. | Dec 1989 | A |
| 4885707 | Nichol et al. | Dec 1989 | A |
| 4907167 | Skeirik | Mar 1990 | A |
| 4910691 | Skeirik | Mar 1990 | A |
| 4922412 | Lane et al. | May 1990 | A |
| 4924418 | Bachman et al. | May 1990 | A |
| 4934196 | Romano | Jun 1990 | A |
| 4942514 | Miyagaki et al. | Jul 1990 | A |
| 4944035 | Aagardl et al. | Jul 1990 | A |
| 4956793 | Bonne et al. | Sep 1990 | A |
| 4964125 | Kim | Oct 1990 | A |
| 4965742 | Skeirik | Oct 1990 | A |
| 4980844 | Demjanenko et al. | Dec 1990 | A |
| 4992965 | Holter et al. | Feb 1991 | A |
| 5005142 | Lipchak et al. | Apr 1991 | A |
| 5006992 | Skeirik | Apr 1991 | A |
| 5008810 | Kessel et al. | Apr 1991 | A |
| 5015934 | Holley et al. | May 1991 | A |
| 5018215 | Nasr et al. | May 1991 | A |
| 5043862 | Takahashi et al. | Aug 1991 | A |
| 5043863 | Bristol et al. | Aug 1991 | A |
| 5050095 | Samad | Sep 1991 | A |
| 5053815 | Wendell | Oct 1991 | A |
| 5070458 | Gilmore et al. | Dec 1991 | A |
| 5081598 | Bellows et al. | Jan 1992 | A |
| 5089978 | Lipner et al. | Feb 1992 | A |
| 5089984 | Struger et al. | Feb 1992 | A |
| 5094107 | Schoch | Mar 1992 | A |
| 5098197 | Shepard et al. | Mar 1992 | A |
| 5099436 | McCown et al. | Mar 1992 | A |
| 5103409 | Shimizu et al. | Apr 1992 | A |
| 5111531 | Grayson et al. | May 1992 | A |
| 5121467 | Skeirik | Jun 1992 | A |
| 5122976 | Bellows et al. | Jun 1992 | A |
| 5130936 | Sheppard et al. | Jul 1992 | A |
| 5134574 | Beaverstock et al. | Jul 1992 | A |
| 5140530 | Guha et al. | Aug 1992 | A |
| 5142612 | Skeirik | Aug 1992 | A |
| 5148378 | Shibayama et al. | Sep 1992 | A |
| 5161013 | Rylander et al. | Nov 1992 | A |
| 5163151 | Bronikowski et al. | Nov 1992 | A |
| 5167009 | Skeirik | Nov 1992 | A |
| 5175678 | Frerichs et al. | Dec 1992 | A |
| 5187674 | Bonne | Feb 1993 | A |
| 5189232 | Shabtai et al. | Feb 1993 | A |
| 5193143 | Kaemmerer et al. | Mar 1993 | A |
| 5197114 | Skeirik | Mar 1993 | A |
| 5197328 | Fitzgerald | Mar 1993 | A |
| 5200028 | Tatsumi et al. | Apr 1993 | A |
| 5200958 | Hamilton et al. | Apr 1993 | A |
| 5210704 | Husseiny | May 1993 | A |
| 5212765 | Skeirik | May 1993 | A |
| 5214582 | Gray | May 1993 | A |
| 5224203 | Skeirik | Jun 1993 | A |
| 5228780 | Shepard et al. | Jul 1993 | A |
| 5235527 | Ogawa et al. | Aug 1993 | A |
| 5251151 | Demjanenko et al. | Oct 1993 | A |
| 5265031 | Malczewski | Nov 1993 | A |
| 5265222 | Nishiya et al. | Nov 1993 | A |
| 5274572 | O'Neill et al. | Dec 1993 | A |
| 5282131 | Rudd et al. | Jan 1994 | A |
| 5282261 | Skeirik | Jan 1994 | A |
| 5291190 | Scarola et al. | Mar 1994 | A |
| 5293585 | Morita et al. | Mar 1994 | A |
| 5301101 | MacArthur et al. | Apr 1994 | A |
| 5303181 | Stockton | Apr 1994 | A |
| 5305230 | Matsumoto et al. | Apr 1994 | A |
| 5311421 | Nomura et al. | May 1994 | A |
| 5311447 | Bonne | May 1994 | A |
| 5311562 | Palosamy et al. | May 1994 | A |
| 5315521 | Hanson et al. | May 1994 | A |
| 5317520 | Castle | May 1994 | A |
| 5325522 | Vaughn | Jun 1994 | A |
| 5327357 | Feinstein et al. | Jul 1994 | A |
| 5329443 | Bonaquist et al. | Jul 1994 | A |
| 5333240 | Matsumoto et al. | Jul 1994 | A |
| 5333298 | Bland et al. | Jul 1994 | A |
| 5347449 | Meyer et al. | Sep 1994 | A |
| 5349541 | Alexandro, Jr. et al. | Sep 1994 | A |
| 5351184 | Lu et al. | Sep 1994 | A |
| 5353207 | Keeler et al. | Oct 1994 | A |
| 5353315 | Scarola et al. | Oct 1994 | A |
| 5361612 | Voiculescu et al. | Nov 1994 | A |
| 5369599 | Sadjadi et al. | Nov 1994 | A |
| 5373452 | Guha | Dec 1994 | A |
| 5384698 | Jelinek | Jan 1995 | A |
| 5384699 | Levy et al. | Jan 1995 | A |
| 5386373 | Keeler et al. | Jan 1995 | A |
| 5390287 | Obata et al. | Feb 1995 | A |
| 5390326 | Shah | Feb 1995 | A |
| 5392226 | Hamilton | Feb 1995 | A |
| 5394341 | Kepner | Feb 1995 | A |
| 5394543 | Hill et al. | Feb 1995 | A |
| 5396415 | Konar et al. | Mar 1995 | A |
| 5398303 | Tanaka | Mar 1995 | A |
| 5400246 | Wilson et al. | Mar 1995 | A |
| 5404064 | Mermelstein et al. | Apr 1995 | A |
| 5408406 | Mathur et al. | Apr 1995 | A |
| 5408586 | Skeirik | Apr 1995 | A |
| 5414645 | Hirano et al. | May 1995 | A |
| 5419197 | Ogi et al. | May 1995 | A |
| 5430642 | Nakajima et al. | Jul 1995 | A |
| 5440478 | Fisher et al. | Aug 1995 | A |
| 5442544 | Jelinek | Aug 1995 | A |
| 5461570 | Wang et al. | Oct 1995 | A |
| 5467355 | Umeda et al. | Nov 1995 | A |
| 5469735 | Watanabe et al. | Nov 1995 | A |
| 5483387 | Bauhahn et al. | Jan 1996 | A |
| 5485753 | Burns et al. | Jan 1996 | A |
| 5486920 | Killpatrick et al. | Jan 1996 | A |
| 5486995 | Krist et al. | Jan 1996 | A |
| 5486996 | Samad et al. | Jan 1996 | A |
| 5488697 | Kaemmerer et al. | Jan 1996 | A |
| 5489831 | Harris | Feb 1996 | A |
| 5499188 | Kline, Jr. et al. | Mar 1996 | A |
| 5500941 | Gil | Mar 1996 | A |
| 5504863 | Yoshida et al. | Apr 1996 | A |
| 5511004 | Dubost et al. | Apr 1996 | A |
| 5511442 | Tame | Apr 1996 | A |
| 5521214 | Bryant et al. | May 1996 | A |
| 5521814 | Teran et al. | May 1996 | A |
| 5521842 | Yamoda | May 1996 | A |
| 5528510 | Kraft | Jun 1996 | A |
| 5533413 | Kobayashi et al. | Jul 1996 | A |
| 5537310 | Tanake et al. | Jul 1996 | A |
| 5541833 | Bristol et al. | Jul 1996 | A |
| 5546301 | Agrawal et al. | Aug 1996 | A |
| 5548528 | Keeler et al. | Aug 1996 | A |
| 5559690 | Keeler et al. | Sep 1996 | A |
| 5561599 | Lu | Oct 1996 | A |
| 5566065 | Hansen et al. | Oct 1996 | A |
| 5570282 | Hansen et al. | Oct 1996 | A |
| 5570300 | Henry et al. | Oct 1996 | A |
| 5572420 | Lu | Nov 1996 | A |
| 5574638 | Lu | Nov 1996 | A |
| 5586066 | White et al. | Dec 1996 | A |
| 5596704 | Geddes et al. | Jan 1997 | A |
| 5598521 | Kilgore et al. | Jan 1997 | A |
| 5600148 | Cole et al. | Feb 1997 | A |
| 5602757 | Haseley et al. | Feb 1997 | A |
| 5602761 | Spoerre et al. | Feb 1997 | A |
| 5604914 | Kabe | Feb 1997 | A |
| 5608845 | Ohtsuka et al. | Mar 1997 | A |
| 5610339 | Haseley et al. | Mar 1997 | A |
| 5623598 | Voigt et al. | Apr 1997 | A |
| 5625574 | Griffiths et al. | Apr 1997 | A |
| 5628994 | Kaper et al. | May 1997 | A |
| 5631825 | van Weele et al. | May 1997 | A |
| 5640491 | Bhat et al. | Jun 1997 | A |
| 5640493 | Skeirik | Jun 1997 | A |
| 5646350 | Robinson et al. | Jul 1997 | A |
| 5666297 | Britt et al. | Sep 1997 | A |
| 5671335 | Davis et al. | Sep 1997 | A |
| 5671351 | Wild et al. | Sep 1997 | A |
| 5675504 | Serodes et al. | Oct 1997 | A |
| 5680409 | Qin et al. | Oct 1997 | A |
| 5682309 | Bartusiak et al. | Oct 1997 | A |
| 5687090 | Chen et al. | Nov 1997 | A |
| 5691895 | Kurtzberg et al. | Nov 1997 | A |
| 5692158 | Degeneff et al. | Nov 1997 | A |
| 5698788 | Mol et al. | Dec 1997 | A |
| 5704011 | Hansen et al. | Dec 1997 | A |
| 5715158 | Chen | Feb 1998 | A |
| 5729661 | Keeler et al. | Mar 1998 | A |
| 5740324 | Mathur et al. | Apr 1998 | A |
| 5742513 | Bouhenguel et al. | Apr 1998 | A |
| 5754451 | Williams | May 1998 | A |
| 5757371 | Oran et al. | May 1998 | A |
| 5761518 | Boehling et al. | Jun 1998 | A |
| 5764891 | Warrior | Jun 1998 | A |
| 5768119 | Havekost et al. | Jun 1998 | A |
| 5777872 | He | Jul 1998 | A |
| 5781432 | Keeler et al. | Jul 1998 | A |
| 5781878 | Mizoguchi et al. | Jul 1998 | A |
| 5790898 | Kishima et al. | Aug 1998 | A |
| 5796602 | Wellan et al. | Aug 1998 | A |
| 5796606 | Spring et al. | Aug 1998 | A |
| 5796609 | Tao et al. | Aug 1998 | A |
| 5798939 | Ochoa et al. | Aug 1998 | A |
| 5805442 | Crater et al. | Sep 1998 | A |
| 5809490 | Guiver et al. | Sep 1998 | A |
| 5819050 | Boehling et al. | Oct 1998 | A |
| 5819232 | Shipman | Oct 1998 | A |
| 5825645 | Konar et al. | Oct 1998 | A |
| 5826249 | Skeirik | Oct 1998 | A |
| 5838561 | Owen | Nov 1998 | A |
| 5842189 | Keeler et al. | Nov 1998 | A |
| 5847952 | Samad | Dec 1998 | A |
| 5848365 | Coverdill | Dec 1998 | A |
| 5855791 | Hays et al. | Jan 1999 | A |
| 5859773 | Keeler et al. | Jan 1999 | A |
| 5859885 | Rusnica et al. | Jan 1999 | A |
| 5859964 | Wang et al. | Jan 1999 | A |
| 5875420 | Piety et al. | Feb 1999 | A |
| 5877954 | Klimasauskas et al. | Mar 1999 | A |
| 5880716 | Kunugi et al. | Mar 1999 | A |
| 5892679 | He | Apr 1999 | A |
| 5892939 | Call et al. | Apr 1999 | A |
| 5898869 | Anderson | Apr 1999 | A |
| 5901058 | Steinman et al. | May 1999 | A |
| 5903455 | Sharpe, Jr. et al. | May 1999 | A |
| 5905989 | Biggs | May 1999 | A |
| 5906214 | Gueret et al. | May 1999 | A |
| 5907701 | Hanson | May 1999 | A |
| 5909370 | Lynch | Jun 1999 | A |
| 5909541 | Sampson et al. | Jun 1999 | A |
| 5909586 | Anderson | Jun 1999 | A |
| 5914875 | Monta et al. | Jun 1999 | A |
| 5918233 | La Chance et al. | Jun 1999 | A |
| 5922963 | Piety et al. | Jul 1999 | A |
| 5924086 | Mathur et al. | Jul 1999 | A |
| 5940290 | Dixon | Aug 1999 | A |
| 5948101 | David et al. | Sep 1999 | A |
| 5949417 | Calder | Sep 1999 | A |
| 5951654 | Avsan et al. | Sep 1999 | A |
| 5960214 | Sharpe, Jr. et al. | Sep 1999 | A |
| 5960441 | Bland et al. | Sep 1999 | A |
| 5975737 | Crater et al. | Nov 1999 | A |
| 5984502 | Calder | Nov 1999 | A |
| 5988847 | McLaughlin et al. | Nov 1999 | A |
| 5995916 | Nixon et al. | Nov 1999 | A |
| 5997167 | Crater et al. | Dec 1999 | A |
| 6006171 | Vines et al. | Dec 1999 | A |
| 6008985 | Lake et al. | Dec 1999 | A |
| 6014612 | Larson et al. | Jan 2000 | A |
| 6017143 | Eryurek et al. | Jan 2000 | A |
| 6026352 | Burns et al. | Feb 2000 | A |
| 6033257 | Lake et al. | Mar 2000 | A |
| 6035339 | Agraharam et al. | Mar 2000 | A |
| 6038486 | Saitoh et al. | Mar 2000 | A |
| 6038540 | Krist et al. | Mar 2000 | A |
| 6041263 | Boston et al. | Mar 2000 | A |
| 6047220 | Eryurek | Apr 2000 | A |
| 6047221 | Piche et al. | Apr 2000 | A |
| 6055483 | Lu | Apr 2000 | A |
| 6061603 | Papadopoulos et al. | May 2000 | A |
| 6067505 | Bonoyer et al. | May 2000 | A |
| 6076124 | Korowitz et al. | Jun 2000 | A |
| 6078843 | Shavit | Jun 2000 | A |
| 6093211 | Hamielec et al. | Jul 2000 | A |
| 6106785 | Haviena et al. | Aug 2000 | A |
| 6108616 | Borchers et al. | Aug 2000 | A |
| 6110214 | Kiimasauskas | Aug 2000 | A |
| 6119047 | Eryurek et al. | Sep 2000 | A |
| 6122555 | Lu | Sep 2000 | A |
| 6128279 | O'Neil et al. | Oct 2000 | A |
| 6134574 | Oberman et al. | Oct 2000 | A |
| 6144952 | Keeler et al. | Nov 2000 | A |
| 6169980 | Keeler et al. | Jan 2001 | B1 |
| 6185470 | Pado et al. | Feb 2001 | B1 |
| 6197480 | Iguchi et al. | Mar 2001 | B1 |
| 6246972 | Klimasauskas | Jun 2001 | B1 |
| 6259959 | Martin | Jul 2001 | B1 |
| 6266726 | Nixon et al. | Jul 2001 | B1 |
| 6285966 | Brown et al. | Sep 2001 | B1 |
| 6298377 | Hartikainen et al. | Oct 2001 | B1 |
| 6298454 | Schleiss et al. | Oct 2001 | B1 |
| 6317638 | Schreder et al. | Nov 2001 | B1 |
| 6317701 | Pyotsia et al. | Nov 2001 | B1 |
| 6332110 | Wolfe | Dec 2001 | B1 |
| 6389331 | Jensen et al. | May 2002 | B1 |
| 6397114 | Eryurek | May 2002 | B1 |
| 6400681 | Bertin et al. | Jun 2002 | B1 |
| 6418465 | Hirosawa et al. | Jul 2002 | B1 |
| 6421571 | Spriggs et al. | Jul 2002 | B1 |
| 6434435 | Tubel et al. | Aug 2002 | B1 |
| 6443435 | Hendrickson | Sep 2002 | B1 |
| 6445963 | Blevins et al. | Sep 2002 | B1 |
| 6507797 | Kliman et al. | Jan 2003 | B1 |
| 6529780 | Soergel et al. | Mar 2003 | B1 |
| 6532392 | Eryurek et al. | Mar 2003 | B1 |
| 6535769 | Konar et al. | Mar 2003 | B1 |
| 6539267 | Eryurek et al. | Mar 2003 | B1 |
| 6549130 | Joao | Apr 2003 | B1 |
| 6567718 | Campbell et al. | May 2003 | B1 |
| 6571273 | Shirai et al. | May 2003 | B1 |
| 6591260 | Schwarzhoff et al. | Jul 2003 | B1 |
| 6609040 | Brunnemann | Aug 2003 | B1 |
| 6615090 | Blevins et al. | Sep 2003 | B1 |
| 6628994 | Turicchi, Jr. et al. | Sep 2003 | B1 |
| 6633782 | Schleiss et al. | Oct 2003 | B1 |
| 6651012 | Bechhoefer | Nov 2003 | B1 |
| 6654697 | Eryurek et al. | Nov 2003 | B1 |
| 6681155 | Fujita et al. | Jan 2004 | B1 |
| 6690274 | Bristol | Feb 2004 | B1 |
| 6704689 | Hogan et al. | Mar 2004 | B1 |
| 6717513 | Sandelman et al. | Apr 2004 | B1 |
| 6721609 | Wojsznis | Apr 2004 | B1 |
| 6732191 | Baker et al. | May 2004 | B1 |
| 6738388 | Stevenson et al. | May 2004 | B1 |
| 6758168 | Koskinen et al. | Jul 2004 | B2 |
| 6760782 | Swales | Jul 2004 | B1 |
| 6774786 | Havekost et al. | Aug 2004 | B1 |
| 6965855 | Burbridge et al. | Nov 2005 | B1 |
| 6968389 | Menditto et al. | Nov 2005 | B1 |
| 7079984 | Eryurek et al. | Jul 2006 | B2 |
| 7120917 | Feist | Oct 2006 | B2 |
| 7206646 | Nixon et al. | Apr 2007 | B2 |
| 7720727 | Keyes et al. | May 2010 | B2 |
| 20020022894 | Eryurek et al. | Feb 2002 | A1 |
| 20020029130 | Eryurek et al. | Mar 2002 | A1 |
| 20020038156 | Eryurek et al. | Mar 2002 | A1 |
| 20020067370 | Forney et al. | Jun 2002 | A1 |
| 20020077711 | Nixon et al. | Jun 2002 | A1 |
| 20020147511 | Eryurek et al. | Oct 2002 | A1 |
| 20020156838 | Batke et al. | Oct 2002 | A1 |
| 20020161940 | Eryurek et al. | Oct 2002 | A1 |
| 20020163427 | Eryurek et al. | Nov 2002 | A1 |
| 20020199014 | Yang et al. | Dec 2002 | A1 |
| 20030002969 | Risser | Jan 2003 | A1 |
| 20030009572 | Thurner | Jan 2003 | A1 |
| 20030014500 | Schleiss et al. | Jan 2003 | A1 |
| 20030028268 | Eryurek et al. | Feb 2003 | A1 |
| 20030065409 | Raeth et al. | Apr 2003 | A1 |
| 20030195934 | Peterson et al. | Oct 2003 | A1 |
| 20030236579 | Hauhia et al. | Dec 2003 | A1 |
| 20040075689 | Schleiss et al. | Apr 2004 | A1 |
| 20040095237 | Chen et al. | May 2004 | A1 |
| 20040181364 | Reeves et al. | Sep 2004 | A1 |
| 20040249583 | Eryurek et al. | Dec 2004 | A1 |
| 20050007249 | Eryurek et al. | Jan 2005 | A1 |
| 20050015624 | Ginter et al. | Jan 2005 | A1 |
| 20050240289 | Hoyte et al. | Oct 2005 | A1 |
| Number | Date | Country |
|---|---|---|
| 1007757 | Apr 1990 | CN |
| 1097804 | Jan 1995 | CN |
| 1267373 | Sep 2000 | CN |
| 35 40 204 | Sep 1986 | DE |
| 40 08 560 | Sep 1990 | DE |
| 44 33 593 | Jun 1995 | DE |
| 195 02 499 | Aug 1996 | DE |
| 199 62 230 | Jun 2001 | DE |
| 0 122 622 | Oct 1984 | EP |
| 0 362 386 | Apr 1990 | EP |
| 0 377 736 | Jul 1990 | EP |
| 0 413 814 | Feb 1991 | EP |
| 0 487 419 | May 1992 | EP |
| 0 594 227 | Apr 1994 | EP |
| 0 612 039 | Aug 1994 | EP |
| 0 624 847 | Nov 1994 | EP |
| 0 626 697 | Nov 1994 | EP |
| 0 644 470 | Mar 1995 | EP |
| 0 827 096 | Mar 1998 | EP |
| 0 959 398 | Nov 1999 | EP |
| 0 961 184 | Dec 1999 | EP |
| 0 964 325 | Dec 1999 | EP |
| 0 965 897 | Dec 1999 | EP |
| 1 160 691 | Dec 2001 | EP |
| 2 083 258 | Mar 1982 | GB |
| 2 294 129 | Apr 1996 | GB |
| 2 294 793 | May 1996 | GB |
| 2 347 234 | Aug 2000 | GB |
| 2 380 833 | Apr 2003 | GB |
| 2 404 457 | Feb 2005 | GB |
| 02-197902 | Aug 1990 | JP |
| 4-220521 | Aug 1992 | JP |
| 05-122853 | May 1993 | JP |
| 05-149763 | Jun 1993 | JP |
| 6-121379 | Apr 1994 | JP |
| 06-125584 | May 1994 | JP |
| 06-242192 | Sep 1994 | JP |
| 06-331507 | Dec 1994 | JP |
| 07-234988 | Sep 1995 | JP |
| 8-249054 | Sep 1996 | JP |
| 08-261886 | Nov 1996 | JP |
| 09-200262 | Jul 1997 | JP |
| 10-039728 | Feb 1998 | JP |
| 10-260821 | Sep 1998 | JP |
| 10-320039 | Dec 1998 | JP |
| 11-231924 | Aug 1999 | JP |
| 11-355325 | Dec 1999 | JP |
| 2000-067015 | Mar 2000 | JP |
| 2000-078750 | Mar 2000 | JP |
| 2000-137504 | May 2000 | JP |
| 2000-172329 | Jun 2000 | JP |
| 2000-305620 | Nov 2000 | JP |
| 2001-016662 | Jan 2001 | JP |
| 2001-022430 | Jan 2001 | JP |
| 2001-044997 | Feb 2001 | JP |
| 2001-216423 | Aug 2001 | JP |
| 2001-265821 | Sep 2001 | JP |
| 2001-350507 | Dec 2001 | JP |
| 2002-315082 | Oct 2002 | JP |
| 2002-323922 | Nov 2002 | JP |
| 2003-058206 | Feb 2003 | JP |
| 94-030327 | Jun 1996 | RU |
| 2103668 | Jan 1998 | RU |
| 2114456 | Jun 1998 | RU |
| 2154853 | Aug 2000 | RU |
| 2178578 | Jan 2002 | RU |
| WO-9838585 | Sep 1998 | WO |
| WO-9913418 | Mar 1999 | WO |
| WO-0050851 | Aug 2000 | WO |
| WO-0108054 | Feb 2001 | WO |
| WO-0223405 | Mar 2002 | WO |
| WO-0295633 | Nov 2002 | WO |
| WO-03019304 | Mar 2003 | WO |
| WO-03075206 | Sep 2003 | WO |
| WO-2004068026 | Aug 2004 | WO |
| Entry |
|---|
| Remote Monitor Controller, JP8249054 Published: Sep. 27, 1996, to Ito Tomoji. |
| English-language translation of First Office Action for Chinese Application No. 2010102701455, received Aug. 22, 2011. |
| Notice of Rejection for Japanese Application No. 2004-219552, dated May 13, 2010. |
| English-language Machine Translation of JP-2002-323922-A. |
| English-language Machine Translation of JP-2003-058206-A. |
| “Components of GE Predictor™ Services,” GE Industrial Systems, available at http://www.geindustrial.com/cwc/services?id=74 on Jul. 18, 2002. |
| “Customer Benefits,” GE Industrial Systems, available at http://www.geindustrial.com/cwc/services?id=75 on Jul. 18, 2002. |
| “Customer Impact,” GE Industrial Systems, available at http://www.geindustrial.com/cwc/services?id=73 on Jul. 18, 2002. |
| “Electrical Equipment Coverage,” GE Industrial Systems, available at http://www.geindustrial.com/cwc/services?id=72 on Jul. 18, 2002. |
| “GE Predictor™ Services: GE Predictor Services Overview,” GE Industrial Systems, available at http://www.geindustrial.com/cwc/services?id=71 on Jul. 18, 2002. |
| “Status Signals of Field Instruments,” NAMUR Recommendation, NA 64, Feb. 1, 2001, pp. 1-8. |
| Bray et al., “Practical Alarm Filtering,” Intech, 41 (2):34-36 (1994). |
| Communication Pursuant to Article 96(2) EPC issued in 02 719 088.3-2206 application by the European Patent Office on Sep. 29, 2004. |
| Communication pursuant to Article 96(2) EPC issued in 02 723 258.6-2206 application by the European Patent Office on Sep. 28, 2004. |
| Dayal et al., “Process Coordination: State of the Art, Trends, and Open Issues,” Proceedings of the 27th International Conference on Very Large Data Bases, pp. 3-13 (2001). |
| dotnet.za.net, “Web Services—A Guide for Business and IT Managers (Sep. 23, 2001)”, (Copyright 2001), www.dotnet.za.net. |
| European Examination Report for Application No. 05714115.2, dated Nov. 5, 2010. |
| European Examination Report for Application No. 02717514.0, dated Jun. 29, 2004. |
| European Examination Report for Application No. 02723319.6, dated Jul. 1, 2004. |
| European Examination Report for Application No. 03743708, dated Feb. 2, 2010. |
| Examination Report for Application No. GB 0212610.0, dated Sep. 16, 2004. |
| Examination Report for Application No. GB 0308687.3, dated Mar. 11, 2005. |
| Examination Report for Application No. GB 0308687.9, dated Mar. 11, 2005. |
| Examination Report for Application No. GB 0416908.2, dated Jun. 27, 2006. |
| First Office Action issued in Chinese Application No. 02122060.3 on Feb. 4, 2005. |
| First Office Action issued in Chinese Application No. 02805785.6 on Nov. 11, 2005. |
| First Office Action issued in Chinese Application No. 02805854.2 on Nov. 11, 2005. |
| First Office Action issued in Chinese Application No. 200580006879.X on Jan. 25, 2008. |
| First Office Action issued in Russian Application No. 2006133968/09, dated May 6, 2009. |
| Fritch W., Primenenie mikroprocessorov v sistemah upravleniya, Moskwa, Mir, 1984 (D1, pp. 68-74). |
| Graupner et al., “E-Speak: An Enabling Infrastructure for Web-Based E-Services,” Proceedings of International Conferences on Advances in Infrastructure for Electronic Business (2000). Retrieved from the Internet: URL:http://yangtze.cs.uiuc.edu/˜wooyoung/espeak-ssgrr.pdf. |
| International Preliminary Examination Report for Application No. PCT/US02/15901, dated Sep. 10, 2003. |
| International Preliminary Examination Report for Application No. PCT/US05/00155, dated Sep. 5, 2006. |
| International Preliminary Examination Report for Application No. PCT/US05/00319. dated Sep. 5, 2006. |
| International Preliminary Examination Report for Application No. PCT/US05/00325, dated Sep. 5, 2006. |
| International Preliminary Examination Report for Application No. PCT/US02/05874, dated Feb. 3, 2003. |
| International Search Report and Written Opinion for Application No. PCT/US02/15901, dated Jun. 17, 2003. |
| International Search Report and Written Opinion for Application No. PCT/US05/00319, dated Sep. 16, 2005. |
| International Search Report and Written Opinion for Application No. PCT/US05/00325, dated Sep. 5, 2005. |
| International Search Report and Written Opinion for Application No. PCT/US05/06155, dated Sep. 5, 2005. |
| International Search Report and Written Opinion for Application No. PCT/US02/05874, dated Nov. 13, 2002. |
| Kalkhoff, “Agent-Oriented Robot Task Transformation,” Proceedings of the International Symposium on Intelligent Control, IEEE, pp. 242-247 (Aug. 27, 1995). |
| Kim et al., “Web E-Speak: Facilitating Web-Based E-Services,” Multimedia, IEEE 9(1):43-55 (2002). |
| Kuno et al., “My Agent Wants to Talk to Your Service: Personalizing Web Services Through Agents,” Proceedings of the First International Workshop on Challenges in Open Agent Systems (2002). Retrieved from the Internet on Apr. 22, 2010: URL:http://www.hpl.hp.com/techreports/2002/HPL-2002-114.pdf. |
| Lighthammer Illuminator™ Manufacturing Intelligence Brochure Now you can see all your manufacturing information from a single interface—in real-time, from anywhere. |
| Lighthammer Software Development, “Illuminator™ The 1st ‘Plant Information Portal’™” (Copyright 1999). |
| Mazeda et al., “Supervision and Optimised Process Control in Sugar Beet Factories,” Centre of Sugar Technology, Spain from www.univ-reims.fr/externes/avh1Omazaeda.pdf. |
| Mehta et al., “Feedforward Neural Networks for Process Identification and Prediction,” presented at ISA 2001, Houston, Texas, Sep. 2001. |
| Moskwa, Mir, A method for gathering data associated with a process plant is known from Fritch W. Primenenie mikroprocesssorov v sistemah upravleniya, (1994). |
| Namur Worksheet, “Status Signals of Field Instruments,” NA 64, Feb. 1, 2001, pp. 1-8. |
| Notice of Allowance U.S. Appl. No. 10/971,361, dated Feb. 27, 2006. |
| Notice of Reasons for Rejection for Japanese Application No. 2003-145503, dated Dec. 11, 2007. |
| Notice of Reasons for Rejection for Japanese Application No. 2003-573590, dated Dec. 1, 2009. |
| Notice of Reasons for Rejection for Japanese Application No. 2008-17965, dated Nov. 9, 2010. |
| Notice of Reasons for Rejection for Japanese Application No. 2002-570030, dated Jun. 19, 2007. |
| Notice of Reasons for Rejection for Japanese Application No. 2002-591920, dated Jun. 12, 2007. |
| Notice of Reasons for Rejection for Japanese Application No. 2003-573590, dated Dec. 9, 2008. |
| Office Action for related Russian Application No. 2006133970/09(036945), dated Jun. 11, 2009. |
| Office Action for U.S. Appl. No. 10/971,361, dated Sep. 26, 2005. |
| Parker et al., Distribution System for Structured Information (2001). |
| Partial International Search Report for PCT/US2005/006325 mailed Jul. 8, 2005. |
| Russian examiner's Decision on Grant and English translation thereof. |
| Search Report for Application No. GB 0308687.3, dated Aug. 28, 2003. |
| Search Report for Application No. GB 0308687.9, dated Aug. 28, 2003. |
| Search Report for Application No. GB 0416908.2, dated Oct. 13, 2004. |
| Second Office Action for Chinese Application No. 03110485.1, dated Oct. 26, 2007. |
| Second Office Action for Chinese Application No. 200580006879.X , dated Sep. 12, 2008. |
| Second Office Action for Russian Application No. 2006133970/09(036945), dated Nov. 9, 2009. |
| Sheldon et al., “Discover: A Resource Discovery System Based on Content Routing,” Proc. 3rd International World Wide Web Conference (1995). |
| Supplementary European Search Report for Application No. 03743708, dated Oct. 8, 2009. |
| Systinet, “Introduction to Web Services”, (Copyright 2001, 2002), www.systinet.com. |
| Third Office Action for Chinese Application No. 200410103816.3, dated Nov. 7, 2009. |
| Tzovla et al., “Abnormal Condition Management Using Expert Systems,” presented at ISA 2001, Houston, Texas, Sep. 2001. |
| U.S. Appl. No. 60/273,164, filed Mar. 1, 2001, “Asset Utilization Expert in a Process Control Plant.” |
| U.S. Appl. No. 60/491,066, filed Jul. 20, 2003, “Economic Calculations in a Process Control System.” |
| Web Services Architect, “What are Web Services”, www.webservicesarchitect.com. |
| Questioning for Japanese Appeal No. 2011-19471, mailed Nov. 29, 2011. |
| Decision of Rejection for Japanese Application No. 2009-1227, dated Feb. 28, 2012. |
| Questioning for Japanese Appeal No. 2012-9863, mailed Aug. 28, 2012. |
| Office Action for Japanese Application No. 2012-14052, dated Jan. 8, 2013. |
| Office Action for Japanese Application No. 2012-9863, dated Dec. 18, 2012. |
| Office Action for Japanese Application No. 2011-173168, dated Dec. 25, 2012. |
| Number | Date | Country | |
|---|---|---|---|
| 20100286798 A1 | Nov 2010 | US |
| Number | Date | Country | |
|---|---|---|---|
| 60491066 | Jul 2003 | US | |
| 60273164 | Mar 2001 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 10798101 | Mar 2004 | US |
| Child | 12779650 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 10123445 | Apr 2002 | US |
| Child | 10798101 | US | |
| Parent | 09953811 | Sep 2001 | US |
| Child | 10123445 | US |
