1 / 29

Integration of scheduling and multiple process plans

Integration of scheduling and multiple process plans. Factory Automation Lab. 3/18/1999 Yang-Cha Chang. Contents. Introduction IPPM (Integrated Process Planning Model) Process Net Model (Multiple process plan generation approach) Mathematical Model Conclusions. Introduction (1/3).

edana
Download Presentation

Integration of scheduling and multiple process plans

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Integration of scheduling and multiple process plans Factory Automation Lab. 3/18/1999 Yang-Cha Chang

  2. Contents • Introduction • IPPM (Integrated Process Planning Model) • Process Net Model (Multiple process plan generation approach) • Mathematical Model • Conclusions Regular seminar in 1st semester of 1999

  3. Introduction (1/3) • Reason for the Integration of process planning and scheduling • resource availability varies with the dynamic condition of the shop floor (machine breakdown) • this change affects original schedule • schedules or process plans should be changed to adjust to the current situation • at the presence of alternative process plans, they can be considered to improve machine utilization and to reduce machining cost Regular seminar in 1st semester of 1999

  4. Introduction (2/3) • Multiple process plan generation • Non-Linear Process Planning • generates all possible process plans • ranks process plans according to some criteria • FLEXPLAN (Detand and Leuben, 1990) • Closed Loop Process Planning • generates only one process plan • if process plan becomes infeasible, modify it or generate another. • Distributed Process Planning • conducts process planning and scheduling at the same time • IPPM (Zhang, 1993), IPPS (Huang, 1992) Regular seminar in 1st semester of 1999

  5. Introduction (3/3) • Process plan selection • objective • load balancing, cost, profit, … • solution approach • mathematical model, tabu search, other heuristics • Integration of process planning and scheduling • Proposal of integration schema • Mathematical modeling • Heuristics Regular seminar in 1st semester of 1999

  6. An integrated model of process planning and production scheduling Hong-Chao Zhang and Srinidhi Mallur Dept. of IE, Texas Tech Univ. I.J.CIM, 1994, Vol. 7, No. 6, 536-364

  7. Model Objectives • To truly integrate process planning and scheduling functions • To generate process plans which reflect shop floor conditions • To consider the objectives of both process planning and the scheduling function simultaneously • To improve machine utilization and reduce machining cost and time Regular seminar in 1st semester of 1999

  8. Scheme of Integration Start & Finish time Manufacturing Resource Database Route sheet Job priority Shop floor status CAD Interface Feature relationship Process Planning Module Available machines Scheduling Module Tolerance analysis Final plans Final plans Decision Making Module Matrix Generation Possible setups Available Resource Process Planning Criteria Scheduling Criteria Regular seminar in 1st semester of 1999

  9. Methodology of integration (1/2) 1. Decide the value of time_window. 2. Feature recognition 3. Develop feature relation graph Final Part THRD CHMF1 CROV1 KEYWY CHMF2 GROV2 HOLE DIAM1 DIAM2 DIAM3 Raw Material Regular seminar in 1st semester of 1999

  10. Methodology of integration (2/2) 4. Create alternative setups (1) Minimize number of setups (2) Minimize number of processing steps (3) Improve machining accuracy 5. Find the feasible process plans by fuzzy set modeling 6. Scheduling module • expert system based on the system performance measurements • dynamic priority rule selection • compute start and finish time for selected jobs • compute start and finish time for each job/machine pair Regular seminar in 1st semester of 1999

  11. Conclusion • Pioneering research that presents the scheme of integration • Its components(modules) uses the AI techniques • Scheduling module applies priority rules based on the dynamic shop floor status but which measure ? • Feature recognition of complex part is still difficult. Regular seminar in 1st semester of 1999

  12. Process Net Model Approach for Multiple Process Plans Ji-Hyung Park and Min-Hyoung Kang CAD/CAM Research Center, KIST KSME International Journal, Vol. 12, No. 4, 659-664, 1998

  13. Process Net (1/2) • AND-OR Graph • and-split (a_s) • and-join (a_j) • or-split (o_s) • or-join (o_j) • Multiple process plans can be extracted from process net • Input data for NLPP system • process net can store multiple process plans in condensed form • Net search should be carried out from the head node to tail node Regular seminar in 1st semester of 1999

  14. Process Net (2/2) Alternative process plans Regular seminar in 1st semester of 1999

  15. System Configuration Feature input module Feature file Process net generating module Feature process net file Process net file Machine net generating module Machine data file Machine net file Feature precedence matrix Graphic output module Process plan generating module Process Plans Process Plans Regular seminar in 1st semester of 1999

  16. Example Process plan (#5) Process net Regular seminar in 1st semester of 1999

  17. Conclusion • Process net representation can save significant storage for the process plan. • This system can be used as a part of the integrated process planning system and can be a input to the scheduling system. • Structure of process net needs to be extended to a various process types, for example plastic processing, heat treatment and non-conventional processes. Regular seminar in 1st semester of 1999

  18. Mathematical model for job shop scheduling with multiple process plan consideration per job Kun-Hyung Kim Hanyon Technology, Inc., Seoul, Korea Pius J. Egbelu Dept. of Systems Engineering, Iowa State Univ P.P.C., 1998, Vol. 9, No. 3, 250-259

  19. Introduction • Incorporating process planning and scheduling can produce schedule’s flexibility and adaptability. • This model simultaneously selects a process plan for each job and generates job shop schedule. • Objective is Min. makespan • System output • a set of selected process plans containing one plan per job • schedule of the jobs on the machines based on the selected process plans Regular seminar in 1st semester of 1999

  20. Math. Model (1/3) i : job j : process plan belonging to a job m : machine h : hth operation in a process plan of a job tijhm : processing time of operation h in process plan j of job i on machine m Tijhm: completion time of operation h in process plan j of job i Yijhpqsm : 1, if operation h in process plan j of job i precedes operation s in process plan q of job p where operation h and s are on machine m : 0, otherwise Xij : 1, if process plan j of job i is selected : 0, otherwise H : A very large positive number Regular seminar in 1st semester of 1999

  21. Math. Model (3/2) MinZ (1) s.t.: For the last operation in process plan j of job i, Tijhm - H(1-Xij)  Z (2) For every operation in process plan j of job i which has direct successor operation, Tijhm - Tij(h-1)g + H(1-Xij)  tijhm i,j,m,h (3) where for the first operation (h=1) in process plan j of job i, Tijhm + H(1-Xij)  tijhm i,j,m,h (4) For every pair of operations that use machine m in process plan j of job i and the process plan q of job p, Tijhm - Tpqsm + HYijhpwsm + H(1-Xij) + (1-Xpq)  tijhm (5) Tpqsm - Tijhm + H(1-Yijhpwsm) + H(1-Xij) + (1-Xpq)  tijhm (6) Regular seminar in 1st semester of 1999

  22. Math. Model (3/3) For every process plan in job i, jXij = 1 (7) For the operations that use machine m in every process plan of job i and job p, -Xij + qYijhpwsm  0 (8) -Xpq+ jYijhpwsm  0 (9) For every operation process plan j of job i, Tijhm 0 (10) Regular seminar in 1st semester of 1999

  23. Preprocessing Method Input all process plan combinations Bounding Module Select a process plan Sn with the lowest lower bound on makespan and set T= Apply mathematical Method (MPSX) Select a process plan combination, Y, whose Lower bound < T and let Y=Sn Makespan Tn of Sn Tn<T NO YES YES Is there a process plan whose lower bound < T? T=Tn NO END Regular seminar in 1st semester of 1999

  24. Bounding procedure (1/2) Step 0: Compute the total number of process plan combinations, R, R=iOi, where Oi = |Pi| for i Step 1: For each Sn and n = 1, 2, …, R, Input data for process plan (Pij) Compute total processing time, Tij, Tij=ht(m,i,j,h) Compute cumulative processing time Mijm for  Pij and m Compute (i) Gn(m) =  Mijn  m (ii) Gn() = Maxm{Gn(m)}  m Regular seminar in 1st semester of 1999

  25. Bounding procedure (2/2) Step 2: For each process plan PijSn considered separately, determine the possible start time STn(m,i,j,h) and completion time CTn(m,i,j,h). Step 3: Compute Earliest start time NSTn(m), NSTn(m)=MinPij{STn(m,i,j,h)} Latest completion time XCTn(m), XCTn(m)=MaxPij{CTn(m,i,j,h)} Step 4: Lower bound LCn(m) of completion time on machine m, LCn(m) = Gn(m) + NSTn(m) Lower bound of makespan, XC(n), XC(n)=Maxm{LCn(m)} Regular seminar in 1st semester of 1999

  26. Experimental Results Regular seminar in 1st semester of 1999

  27. Conclusions • Process planning is the integrator of CAD/CAM/CIM. • Process planning’s flexibility enriches the production planning and control’s quality. • Through the recognition of the relationship between scheduling and process planning, it is advisable to maintain multiple process plans for a job. • But computational effort for Simultaneous process planning and scheduling problem grows exponentially as the problem size increases. Regular seminar in 1st semester of 1999

  28. Conclusions • Heuristic method should be developed to solve problems that involve a large number of parts, process plans and machines • Research Area • multiple process plan generation and representation • efficient and fast process plan selection algorithm • efficient and fast algorithm for simultaneous process planning and scheduling Regular seminar in 1st semester of 1999

  29. References • Hong-Chao Zhang, IPPM-A Prototype to Integrate Process Planning and Job Shop Scheduling Functions,Annals of the CIRP Vo. 42/1/1993, 513-518 • Khoshnevis, 1990, Integration of process planning and scheduling functions, Journal of Intelligent Manufacturing, 1, 165-176 • Paolo Brandimarte, Exploiting process plan flexibility in production scheduling: A multi-objective approach, E.J.O.R. 114 (1999) 59-71 • M. K. Tiwari and N. K. Vidyarthi, An integrated approach to solving the process plan selection problem in an automated manufacturing system, I.J.P.R. 1998, Vol., 36, No. 8, 2167-2184 Regular seminar in 1st semester of 1999

More Related