Abstract
The onset of Industry 4.0 has led to an increased research interest in mass customization production systems. Reconfigurable jigs and fixtures are expected to facilitate customer-driven manufacturing. Scheduling of such fixtures in a mass customization system is yet to be comprehensively investigated. The chapter presents a three-stage method for the optimal scheduling of a two-cell just-in-time manufacturing system that recirculates fixtures for customized parts. The first two stages implemented clustering to produce fixture-part mappings, and intracluster sequencing to enable efficient successive fixture reconfigurations, respectively. The third stage implemented a Mixed Integer Linear Programming (MILP) model to synchronously schedule operations in the two specialized cells, such that total idle time was minimized. A heuristic was developed as an alternative to the MILP model. The paper discusses the three-stage method, with emphasis on the MILP model and Stage 3 Heuristic (S3H). The solutions were compared, and the goodness of the S3H solutions was evaluated in comparison to the optimal solutions. The S3H was found to produce solutions within a range of 5–35% of the corresponding optimal solutions, with far superior solutions times and problem size capabilities.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Yao, F., Lin, Y.: Emerging manufacturing paradigm shifts for the incoming industrial revolution. Int. J. Advanc. Manufact. Technol. 85(5), 1665–1676 (2016)
Fogliatto, F.S., da Silveira, G.J.C., Borenstein, D.: The mass customization decade: An updated review of the literature. Int. J. Prod. Econ. 138(1), 14–25 (2012)
Kowang, T.O., Mohd Hamel, N., Long, C.S., Mohd Rasli, A.: Operation management: project management in jig and fixture industries. Adv. Mater. Res. 931–932, 1621–1625 (2014)
Nee, A.Y.C., Tao, Z., Senthil Kumar, A.: An Advanced Treatise on Fixture Design and Planning, 1st edn. World Scientific Publishing Co., Singapore (2004)
Bakker, O.J., Papastathis, T.N., Ratchev, S.M., Popov, A.A.: Recent research on flexible fixtures for manufacturing processes. Recent Patents Mech. Eng. 6(2), 107–121 (2013)
Bi, Z.M., Zhang, W.J.: Flexible fixture design and automation: review, issues and future directions. Int. J. Prod. Res. 39(13), 2867–2894 (2001)
Groover, M.P.: Automation, Production Systems, and Computer-Integrated Manufacturing, 2nd edn. Prentice-Hall, Pennsylvania (2001)
Liao, T.W.: Group Technology and Cellular Manufacturing. In: Exploring Advanced Manufacturing Technologies, pp. 10-3-1–10-3-11. Industrial Press, New York (2003)
Ouelhadj, D., Petrovic, S.: A survey of dynamic scheduling in manufacturing systems. J. Sched. 12(4), 417–431 (2009)
Ku, W.-Y., Beck, J.C.: Mixed Integer Programming models for job shop scheduling: a computational analysis. Comput. Oper. Res. 73, 165–173 (2016)
Branke, J., Nguyen, S., Pickardt, C., Zhang, M.: Automated design of production scheduling heuristics: A review. IEEE Trans. Evol. Comput. 20(1), 110–124 (2016)
Gen, M., Lin, L.: Multiobjective evolutionary algorithm for manufacturing scheduling problems: State-of-the-art survey. J. Intell. Manuf. 25(5), 849–866 (2014)
Shiihara, M.: Genetic algorithm on job shop scheduling problem under the batch splitting environment. Int. J. Japan Associat. Manag. Syst. 5(1), 1–7 (2013)
Saidi-Mehrabad, M., Fattahi, P.: Flexible job shop scheduling with tabu search algorithms. Int. J. Advanc. Manufact. Technol. 32, 563–570 (2007)
Zhou, R., Nee, Y.C., Lee, H.P.: Performance of an ant colony optimisation algorithm in dynamic job shop scheduling problems. Int. J. Prod. Res. 47(11), 2903–2920 (2009)
Lim, T.L., Kow, M.Y., Nooh, A.B., Yip, M.W.: Case studies in implementing dynamic production planning and scheduling system in make-to-order high-mix-low-volume small and medium-scaled industries for production efficiency. Int. J. Innovat. Comput. 5(1), 5–8 (2015)
Doh, H.-H., Yu, J.-M., Lee, D.-H.: Priority scheduling for a flexible job shop with a reconfigurable manufacturing cell. Indust. Eng. Manag. Syst. 15(1), 11–18 (2016)
Da Silva, B.J.V., Morabito, R., Yamashitaa, Yanasse, H.H.: Production scheduling of assembly fixtures in the aeronautical industry. Comput. Indust. Eng. 67, 195–203 (2014)
Thörnblad, K.S., Strömberg, A.-B., Patriksson, M., Almgren, T.: Scheduling optimization of a real flexible job shop including side constraints regarding maintenance, fixtures, and night shifts. 1st edn. Department of Mathematical Sciences, Division of Mathematics, Chalmers University of Technology and University of Gothenburg, Sweden (2001)
Wong, T.C., Chan, F.T.S., Chan, L.Y.: A resource-constrained assembly job shop scheduling problem with Lot Streaming technique. Comput. Ind. Eng. 57(3), 983–995 (2009)
Yu, J.-M., Doh, H.-H., Kim, J.-S., Lee, D.-H., Nam, S.-H.: Scheduling for a reconfigurable manufacturing system with multiple process plans and limited pallets/fixtures. Int. J. Mechanic. Aerospace. Indust. Mechatr. Manufact. Eng. 6(2), 232–237 (2012)
Naidoo, E., Padayachee, J., Bright, G.: Optimal scheduling of an on-demand fixture manufacturing cell for mass customisation production systems—model formulation, presentation and validation. In: 14th International Conference on Informatics in Control, Automation and Robotics, pp. 17–24. SCITEPRESS, Portugal (2017)
Rokach, L., Maimon, O.: Data Mining and Knowledge Discovery Handbook, 2nd edn. Springer, New York (2010)
Lloyd, S.P.: Least squares quantization in PCM. IEEE Trans. Inf. Theor. 28(2), 129–137 (1982)
Kruskal, J.B.: Nonmetric multidimensional scaling: a numerical method. Psychometrika 29(2), 115–129 (1964)
Bar-Joseph, Z., Gifford, D.K., Jaakkola, T.S.: Fast optimal leaf ordering for hierarchical clustering. Bioinformatics 17(1), S22–S29 (2001)
Wolsey, L.A.: An analysis of the greedy algorithm for the submodular set covering problem. Combinatorica 2(4), 385–393 (1981)
Ibaraki, T.: On the computational efficiency of branch-and-bound algorithms. J. Operat. Res. Soc. Japan 20(1), 16–35 (1977)
Sturrock, K., Rocha, J.: A multidimensional scaling stress evaluation table. Field Methods 12(1), 49–60 (2000)
Cordeau, J., Laporte, G., Savelsbergh, M.W.P., Vigo, D.: Chapter 6 Vehicle Routing, vol. 14, pp. 367–428 (2007)
Acknowledgements
The financial assistance of the National Research Foundation (NRF) towards this research is hereby acknowledged (via the Blue Sky Research Grant: 91339). Opinions expressed and conclusions arrived at are those of the authors, and are not necessarily to be attributed to the NRF.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Naidoo, E., Padayachee, J., Bright, G. (2020). Scheduling of an On-Demand Fixture Manufacturing Cell for Mass Customization: Optimal Method Vs. Heuristic. In: Gusikhin, O., Madani, K. (eds) Informatics in Control, Automation and Robotics . ICINCO 2017. Lecture Notes in Electrical Engineering, vol 495. Springer, Cham. https://doi.org/10.1007/978-3-030-11292-9_1
Download citation
DOI: https://doi.org/10.1007/978-3-030-11292-9_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-11291-2
Online ISBN: 978-3-030-11292-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)