Production Server for Automated Control of Production Document Management (Squires, et al., D/A0417, pending application Ser. No. 09/706,078, filed Nov. 3, 2000);
Print Shop Resource Optimization Via the Use of Autonomous Cells (Duke, et al., D/A0130, pending application Ser. No. 09/706,430, filed Nov. 3, 2000); and
Methods and Systems for Determining Resource Capabilities for a Lean Production Environment, (Gartstein, et al. pending application Ser. No. 10/756,210, filed Jan. 12, 2004), the disclosures of which are totally incorporated herein by reference.
The present embodiments relate to systems and methods for the acquisition and analysis of data for print shop performance evaluation and the use of feedback based on flow metrics to control print shop productivity. By “flow metrics” is meant the quantity of printed materials (e.g., number of pages, sets of books) that moves from one production stage to another per unit time. It finds particular application in conjunction with print shop workflows and performance evaluation, and will be described with particular reference thereto. However, it is to be appreciated that the present exemplary embodiments are also amenable to other like applications.
The costs for operating a print shop are generally categorized as the capitalization cost of the printing equipment, and the operating and employment costs for running the equipment. As print shops tend to transform from being lithographic to digital, additional equipment costs will be incurred, so that how the facilities of the print shops are managed becomes even more important to achieve the desired and more profitable operating results.
Print shops face regular pressures to reduce the costs and improve the productivity of their printing processes. This pressure exists whether a print shop is classified as a job print shop, e.g., one producing small-run individual print jobs for customers, a transactional print shop, e.g., one producing statements for a brokerage firm, or a production print shop, e.g., one producing large-run catalogs for mail order businesses. No matter which class a print shop falls into, each print shop operates in essentially the same way. It accepts a digital file, flat sheet stack, bound material or other original as a job input, operates upon this job according to customer instructions, e.g., paper selection, binding, and distribution, and produces a final product which is then transferred and billed to the customer.
The traditional print shop operation is separated into departments, such as data processing and e-prep, printing, finishing, and shipping departments. Each job progresses sequentially through the various departments. Operators are usually trained to operate one piece of equipment. Like pieces of equipment are usually grouped together within each department, and one operator per machine is required for each shift. This configuration produces frequent waste and requires large amounts of inter-shop inventory, which must then be moved from department to department as a job progresses through the print shop. This traditional method of print shop operation causes frequent delays in meeting job delivery dates, increases waste, and takes up a maximum amount of floor space. As a print shop ramps up its production, accurate job production time becomes increasingly difficult to estimate, often resulting in frequent overflow which must be outsourced to other print shops.
The scheduling and flow of jobs through print shops today is typically controlled by preset, often manual, scheduling policies and workflows that take into consideration only the overall equipment, physical layout and labor in the shop. Workflow is typically fixed in a departmental framework. Emphasis is given to keeping all the equipment busy, with the consequence that a lot of work in progress is generated, jobs are often late, error rates are large, and the exact status of specific jobs in progress in the shop is generally not known. Therefore, the productivity of the vast majority of print shops is far from the optimal that can be realized using modern control theory methods to adjust the scheduling, labor, and workflow to respond to both changes in the incoming job flow and to the state of the shop when the jobs are arriving.
Methods exist for improving the operation of the traditional print shop. One method involves re-conceptualizing a traditional print shop as a type of factory process. The print shop itself is then synonymous with the factory plant, and the print job with the manufactured product. Once thus re-conceptualized, commonly known factory flow processes, such as those discussed by Wallace J. Hopp and Mark L. Spearman in Factory Physics (McGraw Hill: New York, 1996) may be adapted to the print shop environment and used to improve the flow of print jobs through the print shop.
In accordance with another method, a print shop may be reorganized into autonomous cells as disclosed in co-pending application Ser. No. ______ Sudhendu Rai, et al. Autonomous cells group equipment together according to different job classes commonly encountered by a specific print shop. The jobs are then broken down into smaller sub-jobs and processed through the cells. Another method to improve operation is to cross-train operators on multiple pieces of equipment. Operators can then be allocated more flexibly as needed throughout the shop. Opportunities also exist to improve scheduling of jobs so as to reduce the amount of inventory and to more fully utilize equipment. An additional option is to improve the layout of equipment on the print shop floor in order to decrease the amount of excess movement required within the print shop. When implemented, these methods have been shown to reduce costs of all classes of print shops by up to twenty percent within six months of implementing the methods.
Although these methods for operational improvement exist, print shop owners are understandably slow to change their traditional methods of operations. One reason for hesitation is that change is typically quite invasive, requiring re-training operators, moving heavy equipment, and learning new habits, all of which equates to down time and lost productivity for the shop during transition. This lost productivity is problematic for a shop owner who must keep the shop operating smoothly throughout transition periods. There is thus little incentive for a print shop owner to make operational changes without having quantitative data showing a positive benefit to boftom-line profits. It is therefore problematic that print shop owners typically have insufficient data to quantify the extent of possible gains available to them by implementing improved operational methods.
Many print shops do acquire some data on such figures as equipment utilization, labor utilization, and percent of jobs completed on-time that are used as average characterizations of shop performance. Almost all print shops collect data for billing and evaluation of on-time delivery of jobs. However, the global nature of this data limits its ability to assist the print shop owner in making value added changes to the workflow through the print shop. The print shop owner typically uses this limited data in an ad hoc manner to make empirical adjustments in global shop policies based on heuristics that make sense to the local print shop owner. As a result, print shop owners rarely know just how poorly their shops are performing. There is no systematic and detailed way to quantify the amount of savings and productivity improvement that may be achieved using the above-mentioned methods for improving print shop operations.
Moreover, even if print shop owners had the data necessary to recognize that their shops are operating poorly, print shop owners have no way to implement changes to their operations and then continue to adapt to ongoing operational variables, such as equipment failure, irregular arrival of jobs, and fluctuations in the availability of labor, etc.
Thus, what is needed is a system and method for characterizing a print shop and defining a comprehensive set of flow metrics, and for measuring, analyzing, and modeling those flow metrics for the print shop owner in order to quantify for a print shop owner the amount of savings and productivity improvement that may be achieved by using an improved method of operation. Moreover, once the measurement of flow metrics has been implemented, what is needed is a system and method for print shop owners to use feedback from flow-metrics to continually monitor and adapt their operations to changing operational variables.
In accordance with one aspect of the present embodiments, a system and method for collecting and analyzing data on print shop performance that allows a quantitative assessment of that performance and the identification of opportunities for improvement is disclosed. Data are collected on the flow of job events through the shop: their characteristics, the process steps required for their completion, their duration at each step of the work process, and ancillary information of the casuals of their characteristics at each work process step (e.g., the required machine is broken, the required labor is unavailable, the cause of machine failure when it has occurred). They are collected via multiple means: manually, via hand-held scanners, via keystroke entry, via rf tags, etc.) The data are analyzed using methods and simulations that model the workflow through the shop in terms of work process steps that are described in statistical terms (e.g., distributions of jobs in buffers, execution time distributions of various work process steps, statistical distributions of failure and repair time of individual machines). The outputs of these analyses are quantitative current state operational metrics of print shop operations such as equipment utilization, labor utilization, floor space utilization, shop capacity, job and volume profiles, labor costs, set-up costs, work in progress waste and timeliness.
In accordance with another aspect of the subject embodiments, a method and system is disclosed for characterizing the flow of jobs through a print shop and using this characterization to provide real time feedback resulting in changes in the scheduling of these jobs, their routing through the shop, and the allocation of labor resources in the shop. The internal state of the shop and all the jobs therein is characterized by metrics based on the flow of jobs through the shop (e.g., utilization of specific pieces of equipment and labor skills, turn-around time, waiting time at specific work stations, work in progress at specific points in the flow, the time it takes to do specific operations, or the start, interrupt or stop status of specific jobs). Using these metrics to characterize the state of the shop at specific points in time, feedback control policies are applied to reschedule or reroute jobs, or to reallocate labor resources in real time so as to improve the measured metrics. This generation of sensory feedback based on flow metrics, combined with the actuation mechanisms of job rerouting, job rescheduling, and labor reallocation, results in vast improvements in the productivity of most print shops.
Print shops are typically organized into departmental units (all printers together, all binders together, etc.) and print jobs are processed through the departments in sequential steps. Simple algorithms are used to schedule the jobs moving through the shop, e.g., first in first out, smaller jobs first, higher priority jobs first, etc. The flow of jobs can be improved by organizing the print shop into autonomous cells and breaking up large jobs into smaller batches.
Print shops collect widely varying amounts and types of data on their equipment, jobs and labor assignments. Essentially all shops collect data for billing and the evaluation of their on-time delivery of jobs. These data may or may not contain a specification of all the processes needed to complete the job and information on how the job traverses the shop, e.g., when it enters and exits each of these processes and the operator(s) who perform the process. Few shops measure the productivity of each of their pieces of equipment and the variations in this productivity due to the use of different operators and to machine failures and their repair. Acquisition of job characteristic and status data is generally an expensive manual process. The subject embodiments comprise the acquisition of comprehensive data on the equipment, job mix, job flow and labor assignments of a print shop, typically by semi automated means like the use of hand helds to read bar codes printed on jobs in the shop and automatically record the jobs progress through the shop. Given these data items, improved analyses of the data using process models of the shop that are amenable to analysis relative to alternative configurations and control policies in order to assess the productivity of the shop relative to these alternatives is facilitated. Additionally, by measuring the flow of jobs at various points I the work process, and using flow metrics to characterize this flow, the state of flow in the shop at selected instants in time can be evaluated and this information used to change the scheduling of the jobs, their routing and the allocation of labor in such a fashion as to improve the flow and hence the productivity of the shop.
With reference to
Variability enters the shop by virtue of the fact that most of the production steps involve machines (printers, binders, staplers, etc.) that fail, assumed randomly, with mean probability of failure of pf and a mean probability of repair (after failure) of Pr. Typically one assumes that both probability distributions are exponentially characterized by mean times to fail and repair. Variability also enters the shop via the irregular arrival of jobs and fluctuations in the availability of labor to perform the various production processes. Thus, if buffers (not shown) are introduced between production steps (i.e., work in process “WIP”), we find that the occupancy of the various buffers can fluctuate widely. Buffers in which WIP piles up identify bottlenecks and empty buffers identify production steps that are not utilized to their capacity. At any moment in time the shop is characterized by the jobs in progress, the occupancies of all the buffers, the running-idle—broken state of each process, and the assignment of labor to the various processes.
A print shop is characterized by the process steps that it supports, described diagrammatically by the boxes in
The subject development concerns the acquisition of the data that are required to specify selected local states of the print shop and the use of these data to characterize the specified state(s) of the shop, evaluate its productivity based on these states, and compare this performance with alternatives. Typically the print shop will be modeled with discrete-event simulations based on equipment parameters determined by the interview process and a hypothetical job mix based on extrapolations from data acquired from the actual jobs over a sampling time period. The time dependence of the job mix is considered explicitly in the modeling. Bottlenecks are identified and procedures for mitigating them are identified and modeled to determine their effectiveness. These mitigations are presented to the print shop operator in the form of a list of potential improvements ordered in some fashion (e.g., benefit of implementation, cost of implementation, speed/ease of implementation etc). Operator feedback on the feasibility and cost of the mitigations may be incorporated into a second round of proposals. Based on these analyses and data about the cost of labor, renovations and equipment, the financial consequences of a proposed set of modifications can be estimated. If the operator elects to adopt one or more of these proposals, the model based on the data is used as the basis for planning the reorganization of the workflow, the revised layout of the shop, the cross training of operators, the scheduling of jobs in the shop. Thus, the acquisition and analysis of these data form the basis for a set of services offered to the print shop manager to analyze the shop, its capabilities, its costs, and to suggest specific changes in work process, layout, equipment, staffing and staff training, scheduling, and the control process determining scheduling and routing in the shop, that will improve the performance of the shop by amounts that can be estimated to within roughly 10%. The essence of this subject embodiment is a practical methodology for acquiring the requisite data, analyzing it, and suggesting practical improvements that when implemented resulted in on-average a 20% cost saving that fell to the bottom line as profit.
The required data to be acquired 30 fall into seven classes,
These data are acquired by a wide variety of means. Shop layout data can be acquired from prior drawings or specified by shop floor measurements in real time (e.g., by tape measurements or ultrasonic or laser range finders). Cost data are obtained from shop financial records. Job data can be obtained either manually or semi-automatically. At the manual extreme the parameters of the job can be written down on job tickets that are physically associated with each job. Alternatively this information can be keyed into a computer and printed out on bar coded job tickets that are physically associated with each job. Then these can be swiped with hand helds (and extra data keyed in with each swipe) to give a complete record of how the job progressed through the shop. Another alternative to keystroke job ticket entry is to construct rf tags that accompany the job (e.g., are taped to the physical job ticket) and can be read at the beginning and end of each production step. The mapping of the flow of work to the layout diagram is done manually at the present time, but could be automated if that proved cost effective. The parameters associated with the production steps are typically measured (e.g., using stop watches) or extracted from the records of the shop (e.g., machine counters for processing times, historical failure and repair times). Labor requirements are obtained by observation of the current operation of the shop. Characteristics of the labor force are obtained from shop records. Waste is measured by direct observation of current operations or (less often) by comparing shipping information with meter reads.
With reference to
Further analysis depends on the nature of the results for the current state. If the complexity of jobs is low and the utilization rates are low, very simple analyses (e.g., typical black belt projects) can lead to great improvement in the productivity of the shop. If the complexity of jobs is high and the utilization rates are low, analyses of the average parameters of the shop can be used to make major productivity improvements. This is the domain of typical print shops for which automated data collection, data reporting, and data assessment tools are currently being developed. If the job complexity and utilization rates are both high, full-scale statistical modeling is required to predict the effect of proposed improvements in shop performance.
A representative inquiry format for the desired data acquisition may comprise the following format.
After acquisition of the information identified in the foregoing inquiries, the analysis processes of
Another aspect of the subject embodiments concerns insuring high job flow through a shop by identifying bottlenecks via the measurement of flow metrics and to relieve these bottlenecks by the reassignment of labor, the addition of buffers, the reassignment of equipment, and the reprioritizing of jobs (e.g., in order to schedule first jobs that avoid the bottleneck). Similar notions can be applied even to a single printer. This is a workable and valuable aspect in print shops because they handle a wide variety of jobs that entail a wide variety of equivalence classes as described in connection with
Another way of describing this invention is that the control policies for a shop are designed in conjunction with the characteristics, most particularly the throughput and perceived reliability, of the individual process steps. Then when a machine breaks or a person is sick, etc., the control policy is modified because the characteristics of the process steps have changed. In this point of view, the sensing is the measurement of the characteristics (product rate, operating or down state, error indications (e.g., paper jam, defect generation), set up characteristics, etc.) of each step in the process in real time. These data are inputs into a controller that specifies the actuation used to improve the flow. Typical actuations might be to assign more labor to a bottleneck process step, assign buffers associated with this step, change routings to avoid this step, etc.
With reference to
A print shop floor is a dynamic entity. Machines jam and break. They run out of toner or paper. Supplies of specialty paper run out unexpectedly. Workers take unexpected breaks or call in sick. In short, during the course of a day the conditions on the floor change in unexpected ways. Step three is to use the characterization of the shop and its current and immediately prospective job flows to respond to unexpected changes by adjusting the actuation parameters in the shop to respond to its current state in such a fashion that the job flow is maximized (or nearly so). This is done by using feedback from each production step to change in real time the sequencing, scheduling and/or routing of the prospective jobs, the labor assignments of people to machines, or even the production steps themselves (e.g., by inserting a buffer to mitigate the effects of a down machine).
Workers in print shops (and manufacturing environments more generally) are today intuitively trying to do similar things all the time. Books are written on how to do this well (e.g., Eliyahu M. Goldratt, Theory of Constraints (North River Press, Great Barrington 1990). The subject method differs from current practice in three major respects. First, it is based on a quantitative characterization of the production process steps in the shop and the job flows through this shop using known techniques of quantitative manufacturing systems analysis, (e.g., Wallace J. Hopp and Mark L. Spearman, Factory Physics, Irwin McGraw Hill, Boston, 1996.) Some of these techniques have been specifically tailored to the print shop environment. Second, feedback is measured and used from flow parameters to maximize the flow of jobs through the shop rather than maximizing the utilization of the equipment in the shop, which is the current practice in print shops. Third we are envisioning rapid feedback (minutes to hours, i.e., effectively real time) to measure, record and respond to changes in the shop's state so that the sequencing, scheduling and routing of jobs, as well as labor assignments, may be changed on the fly during a shift rather than having to rely on lengthy delays to effect changes at later shifts, days or weeks. One implication of this is that the flow through any routing is dynamically changed to respond to changing requirements and state of the shop. The new aspect is that it is the measured state of the shop rather than a forecast of the state of the shop that is used to make the flow changes. Thus, the subject embodiment describes an analog for manual print shop environments of the automated computer based method and system described in Duke, Jackson and Rai, “Interactive, Distributed Communication Method and System for Bidding On, Scheduling, Routing and Executing a Document Processing Job”, U.S. Pat. No. 6,573,910 B1. These functions can be automated and embedded in a distributed computer/communications system as described in that patent, but they can be done manually (or semi-automated using computer tools like spreadsheets) as well as described herein.
The claims, as originally presented and as they may be amended, encompass variations, alternatives, modifications, improvements, equivalents, and substantial equivalents of the embodiments and teachings disclosed herein, including those that are presently unforeseen or unappreciated, and that, for example, may arise from applicants/patentees and others.
This application claims the priority of U.S. Provisional Application Ser. No. 60/505,676, filed Sep. 24, 2003.
Number | Date | Country | |
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60505676 | Sep 2003 | US |