Advanced Manufacturing Enterprise Technology Thrust Breakout

Transcription

1 Advanced Manufacturing Enterprise Technology Thrust Breakout DMDII-16-04: Real-time Optimization Of Factory Operations Steven Turek, PhD September 8, 2016 D M D I I. O R G

2 Introduction AME Thrust Lead: Steven Turek, AFRL/RXMS (937) Purpose is to introduce the general concept and generate dialog Editorial comments are in red Direct text from the project call is in blue D M D I I. O R G C O N F I D E N T I A L N O T F O R D I S T R I B U T I O N 2

3 Project Topic Background & Overview The operations of a modern manufacturing facility are typically controlled by multiple information systems that do not interact with one another or the information systems upstream/downstream in the manufacturing enterprise. Businesses rely on these silos of information for decision support, which leads to local optimization. To counter this, there is need to unify engineering analysis, production planning/control, and real-time factory floor data to enable operationally dynamic, closed loop control of the manufacturing environment. Emphasis for this call: data/information integration for real-time, global optimization of critical operations D M D I I. O R G C O N F I D E N T I A L N O T F O R D I S T R I B U T I O N 3

4 Problems Assessed Siloed data systems Local optimization of operations Decision making within the manufacturing enterprise is often done on an ad-hoc basis If data is integrated from desperate systems, it is often not real-time or live D M D I I. O R G C O N F I D E N T I A L N O T F O R D I S T R I B U T I O N 4

5 Solution The proposed technology should be demonstrated on at least one scenario that has the potential for a broad-based impact to industry. The demonstration must be realized through industry-relevant virtual and physical test environments (i.e. more than a computer simulation) and quantitatively assessed using both technical and business criteria. The demonstration must be realized in an industry-relevant, virtual and physical test bed and quantitatively assessed using both technical and business criteria. D M D I I. O R G C O N F I D E N T I A L N O T F O R D I S T R I B U T I O N 5

6 Requirements... The solution should use a framework that supports both planning and real time decision making within an integrated work flow environment. The solution should include the ability to model and predict the impacts of variation related to work force make-up, performance level, or disruption. The solution should be extendable to a network of manufacturing facilities serving the same customer base. The technology should provide the capability to provide near real time support for analyzing the impact of process level variations, and their interactions, on factory level metrics. This capability should be robust to data quality, timeliness and completeness gaps. The technology should have the capability to evaluate how specific changes or disturbances in factory operations will affect both short and long term planning scenarios, as well as their impact on factory level metrics. The solution should support the ability to model factory internal as well as external (e.g., supply chain) disturbances. Projects should include, at a minimum, multiple functions within the manufacturing enterprise and multiple products that may compete for resources. The solution should have applicability to both continuous manufacturing as well as discrete manufacturing, however only needs to be demonstrated in one environment. The use of industry standards and protocols is highly encouraged to increase the likelihood of technology transfer outside this effort. Teams must include a minimum of one Industry partner who is a potential end user of the proposed technology and a DMDII Member. The proposed technology must have an initial TRL of 4 or higher at the beginning of the project. D M D I I. O R G C O N F I D E N T I A L N O T F O R D I S T R I B U T I O N 6

7 Innovation and Success Factors Decision making within the manufacturing enterprise include scheduling and timing, order sequencing, and the assignment of resources including materials, workforce, resource, software and assets. Think big, across the enterprise There is a need to connect different information systems to enable efficient and optimal decision-making across a single factory, a network of factories, and the complete supply chain. Diverse data streams, integration, avoid local optimums The exchange and use of information should occur as close to real time as possible. Application space should justify the need for real time decision making requires visibility into the status of production equipment and personnel on the plant floor, machine throughput, inventory movement, labor/material/utilities consumption, machine setups, and plant logistical sequencing. Again, think about diverse activities across the enterprise This is real time decision support for factory operations. Probably require integration of MES, ERP systems, machine status (via MTConnect or other?), supply chain delivery data, etc. MUST target an impactful decision: Operational MUST DEMO, not just a simulation Usage of standards Successful proposals will likely: Baseline current operations Utilize TRLs and MRLs to quantify current and future states (specific technologies and the integration effort) D M D I I. O R G C O N F I D E N T I A L N O T F O R D I S T R I B U T I O N 7