journal article·2024-12

Multi-factor integrated configuration model and three-layer hybrid optimization algorithm framework: turnkey project-oriented rapid manufacturing system configuration

Shu-Lian Xie, Feng Xue, Wei-Min Zhang, Jia-Wei Zhu, Zi-Wei Jia

Advances in Manufacturing· Volume 12· Issue 4
Publisher page

Abstract

No abstract is available for this record. The assistant can identify its topic from the title, but cannot infer the study’s results.

Source: Not provided · Quality: missing

Research context

OpenAlex topics: Manufacturing Process and Optimization · Flexible and Reconfigurable Manufacturing Systems · Scheduling and Optimization Algorithms

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (48)

Show source-provided references
1. Sabioni RC, Daaboul J, Le Duigou J (2021) An integrated approach to optimize the configuration of mass-customized products and reconfigurable manufacturing systems. Int J Adv Manuf Technol 115:141–16310.1007/s00170-021-06984-w ↗
2. Eynaud ABD, Klement N, Roucoules L et al (2022) Framework for the design and evaluation of a reconfigurable production system based on movable robot integration. Int J Adv Manuf Technol 118:2373–238910.1007/s00170-021-08030-1 ↗
3. Mo F, Rehman HU, Monetti FM et al (2023) A framework for manufacturing system reconfiguration and optimisation utilising digital twins and modular artificial intelligence. Rob Comput Integr Manuf 82:102524. https://doi.org/10.1016/j.rcim.2022.10252410.1016/j.rcim.2022.102524 ↗
4. Shivdas R, Sapkal S (2023) Proposed composite similarity metric method for part family formation in reconfigurable manufacturing system. Int J Adv Manuf Technol 125:2535–254810.1007/s00170-023-10849-9 ↗
5. Koren Y, Heisel U, Jovane F et al (1999) Reconfigurable manufacturing systems. CIRP Ann 48:527–54010.1016/S0007-8506(07)63232-6 ↗
6. Bennulf M, Danielsson F, Svensson B et al (2021) Goal-oriented process plans in a multiagent system for plug & produce. IEEE Trans Ind Inf 17:2411–242110.1109/TII.2020.2994032 ↗
7. Dahmani A, Benyoucef L, Mercantini JM (2022) Toward sustainable reconfigurable manufacturing systems (SRMS): past, present, and future. Procedia Comput Sci 200:1605–161410.1016/j.procs.2022.01.361 ↗
8. Nilsson A, Danielsson F, Svensson B (2023) Customization and flexible manufacturing capacity using a graphical method applied on a configurable multi-agent system. Rob Comput Integr Manuf 79:102450. https://doi.org/10.1016/j.rcim.2022.10245010.1016/j.rcim.2022.102450 ↗
9. Cerqueus A, Delorme X (2023) Evaluating the scalability of reconfigurable manufacturing systems at the design phase. Int J Prod Res. https://doi.org/10.1080/00207543.2022.216437410.1080/00207543.2022.2164374 ↗
10. Zhang Y, Yu X, Sun J et al (2022) Intelligent STEP-NC-compliant setup planning method. J Manuf Syst 62:62–7510.1016/j.jmsy.2021.11.002 ↗
11. Xie S, Zhang W, Xue F et al (2022) Industry 4.0-oriented turnkey project: rapid configuration and intelligent operation of manufacturing systems. Machines 10:983. https://doi.org/10.3390/machines1011098310.3390/machines10110983 ↗
12. Fleischer J, Albers A, Ovtcharova J et al (2022) Sino-german Industry 4.0 factory automation platform. https://publikationen.bibliothek.kit.edu/1000143693
13. Gönnheimer P, Kimmig A, Mandel C et al (2019) Methodical approach for the development of a platform for the configuration and operation of turnkey production systems. Procedia CIRP 84:880–88510.1016/j.procir.2019.04.260 ↗
14. Najid NM, Castagna P, Kouiss K (2020) System engineering-based methodology to design reconfigurable manufacturing systems. In: Benyoucef L (ed) Reconfigurable manufacturing systems: from design to implementation. Springer, Cham, pp 29–55. https://doi.org/10.1007/978-3-030-28782-5_310.1007/978-3-030-28782-5_3 ↗
15. Sabioni RC, Daaboul J, Le Duigou J (2022) Concurrent optimisation of modular product and reconfigurable manufacturing system configuration: a customer-oriented offer for mass customisation. Int J Prod Res 60:2275–229110.1080/00207543.2021.1886369 ↗
16. Hou SX, Gao J, Wang C (2022) Design for mass customisation, design for manufacturing, and design for supply chain: a review of the literature. IET Collab Intell Manuf 4:1–1610.1049/cim2.12041 ↗
17. Wang Y, Li X (2021) Mining product reviews for needs-based product configurator design: a transfer learning-based approach. IEEE Trans Ind Inf 17:6192–619910.1109/TII.2020.3043315 ↗
18. Dong L, Ren M, Xiang Z et al (2023) A novel smart product-service system configuration method for mass personalization based on knowledge graph. J Cleaner Prod 382:135270. https://doi.org/10.1016/j.jclepro.2022.13527010.1016/j.jclepro.2022.135270 ↗
19. Yoo JJW (2023) Computational modular system configuration with backward compatibility. Int J Adv Manuf Technol 125:3349–336210.1007/s00170-023-10987-0 ↗
20. da Cunha C, Cardin O, Gallot G et al (2021) Designing the digital twins of reconfigurable manufacturing systems: application on a smart factory. IFAC PapersOnline 54(1):874–87910.1016/j.ifacol.2021.08.103 ↗
21. Ameer M, Dahane M (2021) Reconfiguration effort based optimization for design problem of reconfigurable manufacturing system. Procedia Comput Sci 200:1264–127310.1016/j.procs.2022.01.327 ↗
22. Kutin A, Turkin M, Kliuev M (2021) Multivariate manufacturing process planning for aircraft airframe production based on weighted criteria analysis. Int J Adv Manuf Technol 117:2263–226810.1007/s00170-021-07144-w ↗
23. Gonnermann C, Hashemi-Petroodi SE, Thevenin S et al (2022) A skill- and feature-based approach to planning process monitoring in assembly planning. Int J Adv Manuf Technol 122:2645–267010.1007/s00170-022-09931-5 ↗
24. Nwodu A, Pasha J, Jiang ZQ et al (2022) Co-optimization of supply chain reconfiguration and assembly process planning for factory-in-a-box manufacturing. J Manuf Sci E-T ASME 144:101006. https://doi.org/10.1115/1.405451910.1115/1.4054519 ↗
25. Mansour H, Afefy IH, Taha SM (2023) Simultaneous layout design optimization with the scalable reconfigurable manufacturing system. Prod Eng-Res Dev 17:565–573.10.1007/s11740-022-01168-1 ↗
26. Demir L, Koyuncuoğlu MU (2021) The impact of the optimal buffer configuration on production line efficiency: a VNS-based solution approach. Expert Syst Appl 172:114631. https://doi.org/10.1016/j.eswa.2021.11463110.1016/j.eswa.2021.114631 ↗
27. Yazdani MA, Khezri A, Benyoucef L (2022) Process and production planning for sustainable reconfigurable manufacturing systems (SRMSs): multi-objective exact and heuristic-based approaches. Int J Adv Manuf Technol 119:4519–454010.1007/s00170-021-08409-0 ↗
28. Cantini A, Peron M, De Carlo F et al (2022) A decision support system for configuring spare parts supply chains considering different manufacturing technologies. Int J Prod Res. https://doi.org/10.1080/00207543.2022.204175710.1080/00207543.2022.2041757 ↗
29. Zhou B, Bao JS, Li J et al (2021) A novel knowledge graph-based optimization approach for resource allocation in discrete manufacturing workshops. Rob Comput Integr Manuf 71:102160. https://doi.org/10.1016/j.rcim.2021.10216010.1016/j.rcim.2021.102160 ↗
30. Zhang CX, Dong SL, Chu HY et al (2021) Layout design of a mixed-flow production line based on processing energy consumption and buffer configuration. Adv Manuf 9:369–38710.1007/s40436-021-00354-1 ↗
31. Zeid IB, Doh HH, Shin JH et al (2021) Fast and meta heuristics for part selection in flexible manufacturing systems with controllable processing times. Proc Inst Mech Eng Part B-J Eng Manuf 235(4):650–66210.1177/0954405420968172 ↗
32. Soufi Z, David P, Yahouni Z (2021) A methodology for the selection of material handling equipment in manufacturing systems. In: The 17th IFAC symposium on information control problems in manufacturing (INCOM), Budapest, Hungary, 7–9 June. https://doi.org/10.1016/j.ifacol.2021.08.19310.1016/j.ifacol.2021.08.193 ↗
33. Khettabi I, Benyoucef L, Boutiche MA (2021) Sustainable reconfigurable manufacturing system design using adapted multi-objective evolutionary-based approaches. Int J Adv Manuf Technol 115:3741–375910.1007/s00170-021-07337-3 ↗
34. Gianessi P, Cerqueus A, Lamy D et al (2021) Using reconfigurable manufacturing systems to minimize energy cost: a two-phase algorithm. In: The 17th IFAC symposium on information control problems in manufacturing (INCOM), Budapest, Hungary, 7–9 June. https://doi.org/10.1016/j.ifacol.2021.08.04210.1016/j.ifacol.2021.08.042 ↗
35. Battaia O, Dolgui A, Guschinsky N (2021) Design of reconfigurable machining lines: a novel comprehensive optimisation method. CIRP Ann Manuf Technol 70:393–39810.1016/j.cirp.2021.04.088 ↗
36. Naderi B, Azab A (2021) Production scheduling for reconfigurable assembly systems: mathematical modeling and algorithms. Comput Ind Eng 162:107741. https://doi.org/10.1016/j.cie.2021.10774110.1016/j.cie.2021.107741 ↗
37. Luo S, Zhang LX, Fan YS (2022) Real-time scheduling for dynamic partial-no-wait multiobjective flexible job shop by deep reinforcement learning. IEEE Trans Autom Sci Eng 19:3020–303810.1109/TASE.2021.3104716 ↗
38. Han Y, Chen X, Xu M et al (2021) A multi-objective flexible job-shop cell scheduling problem with sequence-dependent family setup times and intercellular transportation by improved NSGA-II. Proc Inst Mech Eng Part B– J Eng Manuf 236:540–55610.1177/09544054211044660 ↗
39. Ren WB, Yan Y, Hu YG et al (2021) Joint optimisation for dynamic flexible job-shop scheduling problem with transportation time and resource constraints. Int J Prod Res. https://doi.org/10.1080/00207543.2021.196852610.1080/00207543.2021.1968526 ↗
40. Dou J, Su C, Zhao X (2020) Mixed integer programming models for concurrent configuration design and scheduling in a reconfigurable manufacturing system. Concurrent Eng 28:32–4610.1177/1063293X19898727 ↗
41. Dou J, Li J, Xia D et al (2020) A multi-objective particle swarm optimisation for integrated configuration design and scheduling in reconfigurable manufacturing system. Int J Prod Res 59:3975–399510.1080/00207543.2020.1756507 ↗
42. Moussa M, ElMaraghy H (2021) Multiple platforms design and product family process planning for combined additive and subtractive manufacturing. J Manuf Syst 61:509–52910.1016/j.jmsy.2021.09.019 ↗
43. Wikarek J, Sitek P (2021) Model of multidimensional resource configuration in production scheduling: proactive and reactive approach. In: The 17th IFAC symposium on information control problems in manufacturing (INCOM), Budapest, Hungary, 7–9 June. https://doi.org/10.1016/j.ifacol.2021.08.12710.1016/j.ifacol.2021.08.127 ↗
44. Barkokebas B, Al-Hussein M, Hamzeh F (2023) Assessment of digital twins to reassign multiskilled workers in offsite construction based on lean thinking. J Constr Eng Manage 149:04022143. https://doi.org/10.1061/(asce)co.1943-7862.000242010.1061/(asce)co.1943-7862.0002420 ↗
45. Zhang Y, Tang DB, Zhu HH et al (2021) A flexible configuration method of distributed manufacturing resources in the context of social manufacturing. Comput Ind 132:103511. https://doi.org/10.1016/j.compind.2021.10351110.1016/j.compind.2021.103511 ↗
46. Zhou BH, Liao XM (2020) Particle filter and levy flight-based decomposed multi-objective evolution hybridized particle swarm for flexible job shop greening scheduling with crane transportation. Appl Soft Comput 91:106217. https://doi.org/10.1016/j.asoc.2020.10621710.1016/j.asoc.2020.106217 ↗
47. Zhou BH, Shen CY (2018) Multi-objective optimization of material delivery for mixed model assembly lines with energy consideration. J Cleaner Prod 192:293–30510.1016/j.jclepro.2018.04.251 ↗
48. While L, Hingston P, Barone L et al (2006) A faster algorithm for calculating hypervolume. IEEE Trans Evol Comput 10:29–3810.1109/TEVC.2005.851275 ↗