Simulation modeling and analysis of job release policies in scheduling an agile job shop with process sequence dependent setting time

  • Abstract
  • Keywords
  • References
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  • Abstract

    This paper analyses the effects of job release policies, priority scheduling rules and setup times on the performance of a dynamic job shop in a sequence dependent setup time environment. Two job release policies namely, immediate job release and job release based on a specified work-in-process are investigated. A simulation model of a realistic manufacturing system is developed for detailed analysis. The dynamic total work content method is adopted to assign the due dates of jobs. Six priority rules are applied for prioritizing jobs for processing on machines. Several performance criteria are considered for analyzing the system performance. The simulation results are used to conduct statistical tests. Analytical models have been formulated to represent the simulation model for post-simulation studies. These models are found to yield a satisfactory estimation of the system outputs.

  • Keywords

    Dynamic Job Shop, Sequence Dependent Setup, Job Release, Simulation, Regression Models.

  • References

      [1] Allahverdi A & Soroush HM, “The significance of reducing setup times/setup costs”, European Journal of Operational Research, Vol.187, No.3, (2008), pp.978-984.

      [2] Allahverdi A, “The third comprehensive survey on scheduling problems with setup times/costs”, European Journal of Operational Research, Vol. 246, No.2, (2015), pp.345-378.

      [3] Anderson EJ & Nyirenda JC, “Two new rules to minimize tardiness in a job shop”, International Journal of Production Research, Vol.28, No.12, (1990), pp.2277-2292.

      [4] Bergamaschi D, Cigolini R, Perona M & Portioli A, “Order review and release strategies in a job shop environment: A review and a classification”, International Journal of Production Research, Vol.35, No.2, (1997), pp.399-420.

      [5] Cheng TCE & Jiang J, “Job shop scheduling for missed due-date performance”, Computers &Industrial Engineering, Vol.3 No.2, (1998), pp.297-307.

      [6] Demir H.I, Uygun O, Cil I, Ipek M & Sari M, “Process Planning and Scheduling with SLK Due-Date Assignment where Earliness, Tardiness and Due-Dates are Punished”, Journal of Industrial and Intelligent Information,Vol.3, No.3, (2015), pp.173-180.

      [7] Enns ST, “A dynamic forecasting model for job shop flow time prediction and tardiness control”, International Journal of Production Research, Vol. 33, No.5, (1995), pp.1295-1312.

      [8] Friedman LW & Pressman I, “The meta model in simulation analysis:can it be trusted?”, Journal of Operational Research Society, Vol.39 No.10, (1998), pp.939-948.

      [9] Gentile F & Rogers KJ, “Order release and dispatching in a sequence dependent job shop”, Portland International Conference on Management of Engineering & Technology, (2009), pp.1185-1196.

      [10] Hill T, Production/Operations Management, Text and Cases, Prentice Hall, New York, (1991).

      [11] Hill JA, Berry WL & Schilling DA, “Revising the master production schedule in sequence dependent processes”, International journal of production research, Vol.41, No.9, (2003), pp.2021-2035.

      [12] Hall NG & Posner ME, “Generating experimental data for computational testing with machine scheduling applications”, Operations Research, Vol.49, No.6, (2001), pp.854-865.

      [13] Kaplan AC & Unal AT, “A probabilistic cost-based due date assignment model for job shops”, International Journal of Production Research, Vol.31, No.12, (1993), pp.2817-2834.

      [14] Kim SC & Bobrowski PM, “Impact of sequence-dependent setup time on job shop scheduling performance”, International Journal of Production Research, Vol.32, No.7, (1994), pp.1503-1520.

      [15] Kim SC & Bobrowski PM, “Evaluating order release mechanisms in a job shop with sequence‐dependent setup times”, Production and operations management, Vol.4, No.2, (1995), pp.163-180.

      [16] Levin RI & Rebind’s, Statistics for Management, Seventh Edition, Prentice Hall of India, New Delhi, (1998).

      [17] Lu HL, Huang GQ & Yang HD, “Integrating order review/release and dispatching rules for assembly job shop scheduling using a simulation approach”, International Journal of Production Research, Vol.49, No.3, (2011), pp.647-669.

      [18] Madu CN & Chanin MN, “A regression meta model of a maintenance float problem with Erlang-2 failure distribution”, International Journal of Production Research, Vol.30, No.4, (1992), pp.871-885.

      [19] Negahban A & Smith JS, “Simulation for manufacturing system design and operation: Literature review and analysis”, Journal of Manufacturing Systems, Vol.33, No.2, (2014), pp.241-261.

      [20] Naderi B, Zandieh M & FatemiGhomi SM, “Scheduling sequence-dependent setup time job shops with preventive maintenance”, The International Journal of Advanced Manufacturing Technology, Vol.43, No.1, (2009), pp.170-181.

      [21] Nguyen S, Zhang M, Johnston M & Tan KC, “Genetic programming for evolving due-date assignment models in job shop environments”, Evolutionary computation, Vol. 22, No.1, (2014), pp.105-138.

      [22] Philipoom PR, “The choice of dispatching rules in a shop using internally set due-dates with quoted leadtime and tardiness costs”, International Journal of Production Research, Vol.38, No.7, pp.1641-1655, (2000).

      [23] Rangsaritratsamee R, Ferrell WG & Kurz MB, “Dynamic rescheduling that simultaneously considers efficiency and stability”, Computers & Industrial Engineering, Vol.46, No.1, (2004), pp.1-15.

      [24] Saad SM, Pickett N & Kittiaram K, “An integrated model for order release and due-date demand management”, Journal of Manufacturing Technology Management, Vol.15, No.1, (2004), pp.76-89.

      [25] Sabuncuoglu I & Karapınar HY, “Analysis of order review/release problems in production systems”, International Journal of Production Economics, Vol.62, No.3, (1999), pp.259-279.

      [26] Sharma P & Jain A, “Analysis of dispatching rules in a stochastic dynamic job shop manufacturing system with sequence-dependent setup times”, Frontiers of Mechanical Engineering, Vol.9, No.4, (2014), pp.380-389,.

      [27] Sha DY & Liu CH, “Using data mining for due date assignment in a dynamic job shop environment”, International Journal of Advanced Manufacturing Technology, Vol.25, No.11, (2005), pp.1164-1174.

      [28] Slotnick SA, “Order acceptance and scheduling: A taxonomy and review”, European Journal of Operational Research, Vol.212, No.1, (2011), pp.1-11.

      [29] Thürer M, Stevenson M, Silva C, Land MJ & Fredendall LD, “Workload Control and Order Release: A Lean Solution for Make‐to‐Order Companies”, Production and Operations Management, Vol.21, No.5, (2012), pp.939-953.

      [30] Vinod V & Sridharan R, “Dynamic job-shop scheduling with sequence-dependent setup times: simulation modeling and analysis”, International Journal of Advanced Manufacturing Technology, Vol.36, No.3-4, (2008), pp.355-372.




Article ID: 9285
DOI: 10.14419/ijet.v7i1.1.9285

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