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Production planning : operations scheduling with applications in manufacturing and services

Production planning : operations scheduling with applications in manufacturing and services. Erwin Hans (T&M-OMST) BB-235, tel. 3523, e.w.hans@sms.utwente.nl Johann Hurink (TW-STOR) J.L.Hurink@math.utwente.nl Faculty of Technology and Management University of Twente

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Production planning : operations scheduling with applications in manufacturing and services

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  1. Production planning: operations scheduling with applications in manufacturing and services Erwin Hans (T&M-OMST) BB-235, tel. 3523, e.w.hans@sms.utwente.nl Johann Hurink (TW-STOR) J.L.Hurink@math.utwente.nl Faculty of Technology and Management University of Twente Enschede, The Netherlands

  2. Literature Book: Operations Scheduling with applications in manufacturing and services Authors: M. Pinedo, X. Chao Handouts, also downloadable from website

  3. Exam • These methods must be learned entirely • (one or two questions about these will be in the exam): • adaptive search • branch-and-bound, beam-search • shifting bottleneck • The idea (approach) and application of all other discussed • methods must be learned (i.e., no formulas) • One question will be asked about the software demonstration • Aside from the discussed chapters from the book, • the handouts must be learned

  4. Scheduling: definition Allocation of jobs to scarce resources the types of jobs and resources depend on the specific situation Combinatorial optimization problem maximize/minimize objective subject to constraints

  5. Application areas • Manufacturing, e.g.: • job shop / flow shop scheduling • workforce scheduling • tool scheduling • Services, e.g.: • Hotel / airline reservation systems • Hospitals (operating rooms) • Transportation and distribution, e.g.: • vehicle scheduling, and routing • railways

  6. Application areas (cont.) • Information processing and communications: • CPU’s, series and parallel computing • call centers • Time-tabling, e.g.: • lecture planning at a University • soccer competition • flight scheduling • Warehousing, e.g.: • AGV scheduling, and routing • Maintenance, e.g.: • scheduling maintenance of a fleet of ships

  7. Scheduling in manufacturing Due to increasing market competition, companies strive to: • shorten delivery times • increase variety in end-products • shorten production lead times • increase resource utilization • improve quality, reduce WIP • prevent production disturbances (machine breakdowns) --> more products in less time!

  8. Different types of manufacturing control • Make and assemble to stock • Make to stock, assemble to order • Make to order • Engineer to order

  9. Scheduling in a manufacturing planning and control framework • Long range forecasting and sales planning • Facility and resources planning • Demand management, aggregate and workforce planning • Order acceptance and resource group loading • Shop floor scheduling, workforce scheduling

  10. Relations with other management areas • Product and process design • Process planning • Inventory management and materials planning • Purchasing and procurement management • Warehousing and physical distribution

  11. Scheduling in services • Workforce Scheduling in • Call Centers • Hospitals • Employment agencies • Schools, universities • Reservation Systems in • Airlines • Hotels • Car Rentals • Travel Agencies • Postal services

  12. Our approach Scheduling problem Problem formulation Model Solve with algorithms Conclusions

  13. Scheduling models • Job shop scheduling • Project scheduling • Flexible Assembly Systems • Lot sizing and scheduling • Workforce scheduling, staffing • Interval scheduling, reservation systems, timetabling

  14. Scheduling algorithms General solution Techniques: • Mathematical programming • linear, non-linear, (mixed) integer programming • Exact methods (enumeration) • branch-and-bound • dynamic programming • cutting plane / column generation methods • Local search methods, heuristics • simulated annealing • tabu search • adaptive search • k-opt methods • genetic algorithms • neural networks

  15. Scheduling algorithms (cont.) • Heuristics • dispatching rules • composite dispatching rules • beam-search • Decomposition Techniques • Temporal decomposition (rolling horizon approach) • Machine decomposition (Shifting Bottleneck) • Hybrid Methods • combined usage of scheduling methods

  16. Important characteristics of optimization techniques • Quality of Solutions Obtained(How Close to Optimal?) • Amount of CPU-Time Needed(Real-Time on a PC?) • Ease of Development and Implementation(How much time needed to code, test, adjust and modify) • Implementation costs (Are expensive LP-solvers required?)

  17. Dispatching Rules Value Objective Function Local Search Beam Search Branch and Bound CPU - Time

  18. Consideration of software companies w.r.t. optimization techniques Implementation costs (Are expensive LP-solvers required? Easy to implement?) vs. What solution quality does the customer require? (Is an immediate answer required, or are long calculations allowed? Does customer accept complex solutions?) online scheduling offline scheduling

  19. Commercial Packages • ERP-SYSTEMS • SAP, Baan, JD Edwards, People Soft, Navision, MFG Pro • GENERAL OPTIMIZATION • Ilog, Dash, MINTO, OSL (IBM), XPRESS-MP, OML, XA • GENERAL SCHEDULING • I2, Cybertec, AutoSimulation, IDS Professor Scheer, ORTEC • SCHEDULING OIL AND PROCESS INDUSTRIES • Haverly Systems, Chesapeake, Finity, ORTEC • SCHEDULING CONSUMER PRODUCTS • Manugistics, Numetrix • SCHEDULING WORKFORCE IN CALL CENTERS • AIX, TCS, Siebel

  20. Decision Support Systems Important issues in design of DSS: • Database design and management • Data collection (e.g. barcoding system) • Module Design and Interfacing • GUI Design (Gantt-charts, etc.) • Design of link between GUI and algorithm library (data organization before transfer) • Internal Re-optimization • External Re-optimization

  21. GUI’S should allow: • Interactive Optimization • Freezing Jobs and Re-optimizing • Creating New Schedules by Combining Different Parts from Different Schedules • Cascading and Propagation Effects After a Change or Mutation by the User, the system: • does Feasibility Analysis • takes care of Cascading and Propagation Effects, • does Internal Re-optimization

  22. Graphics user interfaces for scheduling production processes • Gantt Chart Interface • Dispatch List Interface • Time Buckets (resource capacity loading) • Throughput Diagrams • Time tables

  23. Important objectives to be displayed • Due Date Related • Number of late jobs • Maximum lateness • Average lateness, tardiness • Productivity and Inventory Related • Total Setup Time • Total Machine Idle Time • Average Time Jobs Remain in System, WIP • Resource usage • resource shortage

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