BRIEF DESCRIPTION OF THE DRAWINGS
The invention can be more fully understood by reading the subsequent detailed description and examples with references made to the accompanying drawings, wherein:
FIG. 1 is a diagram of a conventional single phased manufacturing data processing system.
FIG. 2 is a flowchart of an embodiment of a computer-implemented dual phased manufacturing data processing method.
FIG. 3 is a diagram of an embodiment of a dual phased manufacturing data processing system.
FIG. 4 is a diagram of an exemplary implementation of a dual phased manufacturing data processing system.
DESCRIPTION
FIG. 2 is a flowchart of an embodiment of a computer-implemented dual phased manufacturing data processing method. Manufacturing data is collected and classified as urgent data and non-urgent data (Step S200). The manufacturing data may be collected from various sources, such as customers, engineers, detection systems of manufacturing tools, and service systems for the customers. The manufacturing data may be collected through networks, such as the Internet. The non-urgent data may comprise warning, status, and log data. Warning data indicate states which are unusual but not urgent. Status data implies the current statuses of systems, such as service systems or detection systems. Log data comprises entrance records for system users, such as customers, operators, or other systems. The urgent data from various sources indicates that the corresponding manufacturing situations require to be handled immediately.
Suitable actions for the urgent data, such as terminating one manufacturing process or debugging an on-line controller, are generated (step S202). The non-urgent data is then analyzed (step S204). The analysis comprises data integration, data recalculation, historical data analysis, urgent data reference, and data conversion.
Actions responding to the non-urgent data are generated according to the analysis results (step S206). The actions comprise notification of customers and/or operators, updating databases of the detection systems, and establishing data filtering rules in the service systems.
FIG. 3 is a diagram of an embodiment of a dual phased manufacturing data processing system. The dual phased manufacturing data processing system comprises a collection module 30, an analysis module 32, and a generation module 34.
The collection module 30 collects manufacturing data from various sources, such as customer systems, support operation systems, detection systems of manufacturing tools, and service systems for the customers. The manufacturing data is classified as urgent data and non-urgent data. The collection module 30 may collect the manufacturing data through networks, such as the Internet. Here, the non-urgent data may comprise warning, status, and log data.
The analysis module 32 analyzes the non-urgent data by data integration, data recalculation, historical data analysis, urgent data reference, and data conversion.
The generation module 34 generates actions to the non-urgent data according to the analysis result. The generation module 34 also generates actions of the urgent data. The actions comprise notification of customers and/or operators, updating databases of the detection systems, and establishing data filtering rules in the service systems.
FIG. 4 is a diagram of an exemplary implementation of a dual phased manufacturing data processing system. Service systems 400 are provided by manufacturers to customer systems 402. The customer systems 402 may access the service systems 400 through networks 404, such as the Internet. Detection systems 406, connected to the service systems 400, customer systems 402, and manufacturing tools 408, are coupled to receive data from all resources and operated to generate manufacturing data 410. After the detection systems 406 collected and compiled manufacturing data from various sources, the manufacturing data is categorized as urgent data 412 and non-urgent data 414. The manufacturing data 410 is processed by an analysis module 420, which conducts operations and analyses on manufacturing data 410 to generate analysis results. The data processing may comprise data integration, data recalculation, historical data analysis, urgent data reference, and data conversion. The analysis results and corresponding reactions are sent to a support operation system 416.
The operator attending to the support operation system 416 may provide instructions to the support operation system to take action corresponding to the urgent data 412 to respond to data urgency and take action of the non-urgent data 414 to maintain the service systems 400. If the analysis result shows optimal operations for the customers 402, corresponding information may be sent to service personnel 418. The service personnel 418 can recommend or notify the customers 402 prior to problems occurring.
An analysis module 420 appears in FIG. 4, unlike FIG. 1. The analysis module 420 analyzes manufacturing data and generates corresponding reactions. The analysis result can be utilized in the maintenance of the service systems or provide recommendations to the customers, improving service quality significantly.
While the invention has been described by way of example and in terms of preferred embodiment, it is to be understood that the invention is not limited thereto. Those skilled in the technology can still make various alterations and modifications without departing from the scope and spirit of this invention. Therefore, the scope of the present invention shall be defined and protected by the following claims and their equivalents.