Factory optimization requires optimal planning of the factory’s workcells, production lines, and assembly operations. Critical inputs to that planning come from the product manufacturing information generated by the SIMCA program. The resulting plans contain important information detailing the optimal use of all factory resources. Today, most of this information is in various human-readable documents interpreted by expert factory personnel. Attempts to capture and convert this information into comprehensive, computer-interpretable data models have recently begun. However, measurement science is lacking to determine if these data models are correct, easily and accurately exchanged, and satisfy their intended optimization requirements. This project will develop and deploy that measurement science.
To develop and deploy advances in measurement science that will enable optimal production plans, schedules, and programs for workcells, production lines, and assembly operations, delivering results to standards bodies by 2016.What is the new technical idea?
Manufacturing efficiency pioneer W. Edwards Deming said, “Doing your best is not good enough. You have to know what to do. Then do your best.” The new technical idea for this project is based on this adage. It is to use product manufacturing information from the SIMCA program together with digital models of production plans and schedules as a basis for optimizing factory performance. In this case, optimizing performance means not only what to do, the production plan, but also when to do it, the schedule. The digital models provide the major inputs to the SMPE and NGRA programs, which determine how to execute the activities in the corresponding plans and schedules.
For machining workcells, the pervasive programming standard originated in the early 1950s. For inspection workcells, the information modeling has been tailored to parochial needs of the users, resulting in a wasted effort for data translation and reintegration of quality data. For assembly operations, individual programs are proprietary, and coordination is done with programmable logic controllers using simple text or block diagrams. Productions lines are coordinated similarly. Manufacturers work around these limitations today using expert process engineers who manually adjust process plans in a trial-and-error manner. This may be cost-effective for steady-state high-volume production, but limits the ability of small and medium enterprises to respond to quickly-changing market opportunities. New standards for “smart data” have been developed to solve these problems, but measurement science is lacking to determine if they meet their requirements, how well the information is exchanged among factory floor systems, and how well these systems meet their optimal targets. This project will develop the necessary measurement science, enabling optimized performance, improved quality, and higher productivity for large and small manufacturers alike.What is the research plan?
The research plan is to develop measurement methods and test cases to validate that standards for process information models fulfill their requirements, and verify that schedules, plans, and programs meet their optimality objectives. The targeted domains are workcells for machining, inspection, and assembly, and factory scheduling for production lines. The work will follow a phased approach for each of several production focuses and their associated standards. The first phase is standards validation, conducted in pilot tests with industry partners. The research will determine what optimization can be achieved in production, what information is needed to drive the optimization, and to what degree the associated standard information models provide this information. The outputs of this phase will be standards improvement requests (SIRs) that improve final standards outcomes. The second phase is standards verification, conducted within industry implementation forums. The research will determine the most effective test cases for conformance that cover the full range of information, and how to best measure and report conformance results to be useful to implementers. The outputs of this phase will be conformance tests and associated test cases that improve the ability of manufacturers to exchange information along their production streams. Machining and inspection are the production focuses early in the project. Assembly planning and production scheduling will be included following assessment periods. Project work will be externally linked with the Systems Integration for Manufacturing and Construction Applications (SIMCA) program that is developing standards for product manufacturing information, and the Smart Manufacturing Processes and Equipment (SMPE) program that is developing models and performance measures for the underlying unit process equipment.Recent Results:
Standards validation will take place through industry groups associated with standards committees. For machining, this group is the Open Modular Architecture Controller (OMAC) Machine Tool Working Group that is driving the pilot testing of standards from ISO TC 184 SC 4. For inspection, the group is the Dimensional Metrology Standards Organization (DMSC). The International Society for Automation (ISA) and ISO TC 184 SC 5 are the organizations for production scheduling. Standards verification will take place through the Computer-Aided Technology Implementer’s Forum (CAx-IF), an organization established to test conformance and performance of ISO 10303 (STEP) computer-aided design (CAD) systems that has expanded its scope to include computer-aided manufacturing (CAM) and computer-aided inspection (CAI). Support to public-sector agencies such as the Department of Defense for standards-based production information exchange is being provided through participation in the Model-Based Enterprise Manufacturing Working Group.
Start Date:October 1, 2012
Lead Organizational Unit:el
Related Programs and Projects:
Fred Proctor, Project Leader