1. Simulation Assisted Optimization and Real-Time Control Aspects of Flexible Production Systems Subject to Disturbances Authors: Wilhelm Dangelmaier Kiran R Mahajan Thomas Seeger Benjamin Klöpper Mark Aufenanger Presenter: Greg Broderick Date: November 17, 2008

2. Function of Paper/ Things Considered Describes how to Design and Develop a Predictive and Reactive system for Scheduling and Rescheduling Describes how to Design and Develop a Predictive and Reactive system for Scheduling and Rescheduling Rescheduling Methods for real-time Controls Rescheduling Methods for real-time Controls Do this while considering Flexible and Fixed Flows with Parallel Machines Do this while considering Flexible and Fixed Flows with Parallel Machines

3. Why it is Important to Us This System Benefits Production This System Benefits Production Increases PerformanceIncreases Performance Reduce Material BufferReduce Material Buffer Reduce Material HandlingReduce Material Handling StabilityStability Real-Time ControlReal-Time Control Show Accuracy and Importance of Simulations Show Accuracy and Importance of Simulations

4. References 1 Brah, S. A. and J. L. Hunsucker. 1991. Branch and Bound Brah, S. A. and J. L. Hunsucker. 1991. Branch and Bound algorithm for the flow shop with multiple processors, European Journal of Operational Research, Vol. 51, pp- 88-99. Cheng, J., Y. Karuno, and H. Kise. 2001. A shifting bottleneck Cheng, J., Y. Karuno, and H. Kise. 2001. A shifting bottleneck procedure for a parallel machine flow shop scheduling problem. Journal of Operations Research, Society of Japan, 29, No. 2, pp. 140-156. Chong, C. S., A. I. Sivakumar, and R. Gay. 2003. Simulation- Chong, C. S., A. I. Sivakumar, and R. Gay. 2003. Simulation- based scheduling for dynamic discrete production. In Proceedings of the 2003 Winter Simulation Conference, ed. S. Chick, P. J. Sanchez, D. Ferrin, and D. J. Morrice, 1465 - 1473. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers. Church, L. K., and R. Uzsoy. 1992. Analysis of periodic Church, L. K., and R. Uzsoy. 1992. Analysis of periodic and event driven rescheduling policies in dynamic

5. References 2 shops. International Journal of Computer Integrated Manufacturing 5, 153-163. Gupta, J. N. D., and A. J. Ruiz-Torres. 2000. Minimizing Gupta, J. N. D., and A. J. Ruiz-Torres. 2000. Minimizing makespan subject to minimum total flow time on identical parallel machines, European Journal of Operational Research, Vol. 125, No.5, pp.616-625. Haldun, A., M. Lawley, K. McKay, S. Mohan and R. Haldun, A., M. Lawley, K. McKay, S. Mohan and R. Uzsoy. 2005. Executing production schedules in the face of disturbances: A review. European Journal of Operational Research 161, 86-110. Harmonosky, C. M., R. H. Farr, and M. C. Ni. 1997. Selective Harmonosky, C. M., R. H. Farr, and M. C. Ni. 1997. Selective rerouting using simulated steady state system data. In Proceedings of the 1997 Winter Simulation Conference, ed. S. Andradottir, K. J. Healy, D. H. Withers, and B. L. Nelson, 1293 - 1298. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers. Leon, V. J., S. D. Wu, and R. H. Storer. 1994. A Leon, V. J., S. D. Wu, and R. H. Storer. 1994. A

6. References 3 control approach for job shops in the presence of disruptions. International journal of production research 32: 1451-1476. Leon, V. J., S. D. Wu, and R. H. Storer. 1993. Robustness Leon, V. J., S. D. Wu, and R. H. Storer. 1993. Robustness measures and robust scheduling for job shops. IIE Transactions 26, 32-43. Phadniis, S., and S. Irani. 2003. Development of a new Phadniis, S., and S. Irani. 2003. Development of a new heuristic for scheduling flow-shops with parallel machines by prioritizing bottleneck stages. Transactions of the SDPS, Vol. 7, No. 1, pp 87-97. Wu, S. D., and R. A. Wysk. 1989. An application of discrete- Wu, S. D., and R. A. Wysk. 1989. An application of discrete- event simulation to on-line control and scheduling of flexible manufacturing. International Journal of Production Research, Vol. 27 (9). Wu, S. D., E. Byeon, and R. H. Storer. 1999. A graphtheoretic Wu, S. D., E. Byeon, and R. H. Storer. 1999. A graphtheoretic decomposition of job shop scheduling problems to achieve scheduling robustness. Operations Research, Vol. 47, pp. 113-124.

7. How it Relates to Me En 482 The Paper Considers Different Types of Planning

8. How it Relates to Me En 482

9. Parameters and Terms Defined Scheduling? Scheduling? Initial Factory Plan Before ProductionInitial Factory Plan Before Production Based on Make Span/Time (1) or Upper Bounds/Quantity (2)Based on Make Span/Time (1) or Upper Bounds/Quantity (2) Disturbance? Disturbance? Slows or Alters ProductionSlows or Alters Production Due to Complexity and Business DynamicsDue to Complexity and Business Dynamics Re-Scheduling or Realized Solution (3)? Re-Scheduling or Realized Solution (3)? Change in Plan after Production StartsChange in Plan after Production Starts Requires Real-Time Controls and DataRequires Real-Time Controls and Data Parameters Required For Optimization Parameters Required For Optimization Processing and Waiting TimesProcessing and Waiting Times Jobs and Materials AvailableJobs and Materials Available Machines and maintenance SchedulesMachines and maintenance Schedules Stages and Traveling TimeStages and Traveling Time Black Box – Optimization Algorithm Black Box – Optimization Algorithm KPI – Key Performance Indicator – How a Model is Evaluated KPI – Key Performance Indicator – How a Model is Evaluated Stability - Job Starting Time and Job Sequence Deviations Stability - Job Starting Time and Job Sequence Deviations FAM – Flow Analyzer Module FAM – Flow Analyzer Module

10. Design Principles/Considerations Optimization and Their Trade Offs Optimization and Their Trade Offs Global Vs. Localized SchedulingGlobal Vs. Localized Scheduling Reducing Disturbances Vs. Developing Complicated Scheduling LogicReducing Disturbances Vs. Developing Complicated Scheduling Logic When to initiate a Re-scheduling When to initiate a Re-scheduling Event Driven –New Job –Machine BreaksEvent Driven –New Job –Machine Breaks Periodic –One day –One ShiftPeriodic –One day –One Shift What should it be What should it be

11. Experimental Equipment What is the foundation for the Results Aggregate production planning Aggregate production planning Master production planning Master production planning Material requirements planning (MRP) Material requirements planning (MRP) Capacity planning Capacity planning

12. Design Principles Applied Combining Simulation and Optimization to Achieve Validity and Optimality of the Predictive Schedule

13. Design Principles Applied Combination of Simulation and Optimization for Rescheduling and real-time control

14. Design Principles Applied Selective Rescheduling Stability Algorithm

15. Results (data/tables/design) Here they show the Difference between the three Design Principles

16. Results Correlated with Model Sometimes Re-Scheduling slows down the Process Sometimes Re-Scheduling slows down the Process

17. Practical Industrial Use Provides an ability to actively regulate the production of a factory to meet needs. Provides an ability to actively regulate the production of a factory to meet needs. Could boost efficiency Could boost efficiency Agile manufacturing Vs. Lean production

18. Technical Advancements Agile manufacturing

19. Industries most Impacted Most Factories Most Factories Factories that are subject to Disturbances Factories that are subject to Disturbances Factories that make custom parts Factories that make custom parts Small Factories that produce quality items Small Factories that produce quality items

20. Thanks Questions?