THE SELECTION OF PROCESS SEQUENCE FOR MULTI MACHINE ARRANGED IN SERIES IN THE JOB SHOP INDUSTRY
DOI:
https://doi.org/10.33373/icms.v1i1.15Keywords:
Dispatching, LPT, Johnson Algorithm, Series, SPTAbstract
PT. KOP operates within the oil and gas drilling sector, utilizing job shop production scheduling. The company produces 4 primary product types, employing 2 identical machines operated in parallel, as is common in the job shop industry. However, production planning faces challenges, notably delivery delays stemming from inefficient scheduling, indicated by high work-in-process inventory and machine tooling availability issues. This research proposes a series-based machine scheduling method, evaluating dispatching methods such as SPT (Shortest Processing Time), LPT (Longest Processing Time), and the Johnson algorithm. Results demonstrate that the Johnson method outperforms SPT and LPT, minimizing delay times to 1 hour in the first week, 16 hours in the second, 48 hours in the third, and 86 hours in the fourth. By arranging machines in series, tooling requirements are reduced by 50%. Specifically, series machines only require 4 tooling per product, while parallel machines require 8.
References
Baker, K. R. and Scudder, G. D. (1990) ‘Sequencing with earliness and tardiness penalties. A review’, Operations Research, 38(1), pp. 22–36. doi: 10.1287/opre.38.1.22.
Benttaleb, M., Hnaien, F. and Yalaoui, F. (2018) ‘Two-machine job shop problem under availability constraints on one machine: Makespan minimization’, Computers and Industrial Engineering, 117, pp. 138–151. doi: 10.1016/j.cie.2018.01.028.
Branke, J., Hildebrandt, T. and Scholz-Reiter, B. (2015) ‘Hyper-heuristic evolution of dispatching rules: A comparison of rule representations’, Evolutionary Computation, 23(2), pp. 249–277. doi: 10.1162/EVCO_a_00131.
Davari, M. et al. (2020) ‘Minimizing makespan on a single machine with release dates and inventory constraints’, European Journal of Operational Research, 286(1), pp. 115–128. doi: 10.1016/j.ejor.2020.03.029.
Golmohammadi, D. and Mansouri, S. A. (2015) ‘Complexity and workload considerations in product mix decisions under the theory of constraints’, Naval Research Logistics, 62(5), pp. 357–369. doi: 10.1002/nav.21632.
Grundstein, S., Freitag, M. and Scholz-Reiter, B. (2017) ‘A new method for autonomous control of complex job shops – Integrating order release, sequencing and capacity control to meet due dates’, Journal of Manufacturing Systems, 42, pp. 11–28. doi: 10.1016/j.jmsy.2016.10.006.
Hildebrandt, T., Heger, J. and Scholz-Reiter, B. (2010) ‘Towards improved dispatching rules for complex shop floor scenarios’, Proceedings of the 12th annual conference on Genetic and evolutionary computation - GECCO ’10, p. 257.
Holthaus, O. and Rajendran, C. (2000) ‘Efficient jobshop dispatching rules: Further developments’, Production Planning and Control, 11(2), pp. 171–178. doi: 10.1080/095372800232379.
Irwan, H. (2020) ‘A Study Review of Completion Multi Job on Job Shop Scheduling Technique To Minimize Make Span’, PROFISIENSI: Jurnal Program Studi Teknik Industri, 8(1), pp. 7–14. doi: 10.33373/profis.v8i1.2554.
Irwan, H. (2022) ‘A review of integration model of lot-sizing-scheduling problem’, Malaysian Construction Research Journal, 17(3), pp. 160–174. Available at: https://www.cream.my/usr/product.aspx?pgid=88&id=58&lang=en.
Jayamohan, M. S. and Rajendran, C. (2000) ‘New dispatching rules for shop scheduling: A step forward’, International Journal of Production Research, 38(3), pp. 563–586. doi: 10.1080/002075400189301.
Lin, D.-Y. and Huang, T.-Y. (2021) ‘A Hybrid Metaheuristic for the Unrelated Parallel Machine Scheduling Problem’, Mathematics, 9(7), p. 768. doi: 10.3390/math9070768.
Mansouri, S. A., Golmohammadi, D. and Miller, J. (2019) ‘The moderating role of master production scheduling method on throughput in job shop systems’, International Journal of Production Economics, 216(April), pp. 67–80.
Mönch, L. et al. (2005) ‘Heuristic scheduling of jobs on parallel batch machines with incompatible job families and unequal ready times’, Computers and Operations Research, 32(11), pp. 2731–2750. doi: 10.1016/j.cor.2004.04.001.
Pfund, M. E., Mason, S. J. and Fowler, J. W. (2006) ‘Semiconductor Manufacturing Scheduling and Dispatching’, Handbook of Production Scheduling, pp. 213–241. doi: 10.1007/0-387-33117-4_9.
Pinedo, M. L. (2008) Scheduling: Theory, algorithms, and systems, Scheduling: Theory, Algorithms, and Systems. Springer New York. doi: 10.1007/978-0-387-78935-4.
Shady, S. et al. (2021) ‘Evolving Dispatching Rules Using Genetic Programming for Multi-objective Dynamic Job Shop Scheduling with Machine Breakdowns’, in Procedia CIRP. Elsevier B.V., pp. 411–416. doi: 10.1016/j.procir.2021.11.069.
Sharda, R. (ed.) (2013) Production Planning and Control for Semiconductor Wafer Fabrication Facilities. Springer New York Heidelberg Dordrecht London. doi: 10.1007/978-1-4614-4472-5.
Supithak, W., Liman, S. D. and Montes, E. J. (2010) ‘Lot-sizing and scheduling problem with earliness tardiness and setup penalties’, Computers and Industrial Engineering, 58(3), pp. 363–372. doi: 10.1016/j.cie.2008.10.005.
Waschneck, B. et al. (2017) ‘Production scheduling in complex job shops from an industrie 4.0 perspective: A review and challenges in the semiconductor industry’, CEUR Workshop Proceedings, 1793.
