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Design of the optimal feeding policy in an assembly system

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  • Battini, Daria
  • Faccio, Maurizio
  • Persona, Alessandro
  • Sgarbossa, Fabio

Abstract

This paper describes an innovative and integrated approach to component management optimization within a production/assembly system. In a mixed-models assembly process the handling of parts and components for each work station represents a substantial variable that can greatly affect job duration and efficiency. This paper is strictly related to Assembly to Order/Manufacturing to Order (ATO and MTO) systems, where lead time has to be very short and flexibility is at its maximum level. In Assembly to Order (ATO) or Make to Order (MTO) systems, the production is increasingly getting more customized in response to the demand, thanks to the progresses reached in both manufacturing and information technologies. It is becoming increasingly possible to assemble or make products specifically in response to the requests of either end customers or retailers. As a consequence of such customization, the design of the whole system must take into direct account several elements: parts warehouses location, feeding policies and feeding systems. In some cases the collection of parts and components required picking activities, in other the movement of entire units load. In several instances experts have analyzed the problems about material centralization/decentralization, storage policies and assembly feeding problem in different and independent ways, while the problem needs an integrated approach. While many researches regarding components allocation problems in ATO and MTO systems, did not consider feeding policies, material picking, packing activities and vehicles optimization, this paper cover focuses on filling such gap using an integrated framework that considers both aspects of the problem: the centralization/decentralization of components in order to minimize the total storage costs and the right feeding policies. Feeding problems in assembly lines are some of the most important aspects to consider during the analysis and design of an assembly system, to allow the maximization of efficiency and flexibility. To reach such goals, a multi-factorial analysis has been carried out during this experiment and will validate the introduced framework. An industrial application of the introduced framework is illustrated to explain its real significant production implication.

Suggested Citation

  • Battini, Daria & Faccio, Maurizio & Persona, Alessandro & Sgarbossa, Fabio, 2009. "Design of the optimal feeding policy in an assembly system," International Journal of Production Economics, Elsevier, vol. 121(1), pages 233-254, September.
    • Handle: RePEc:eee:proeco:v:121:y:2009:i:1:p:233-254
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    References listed on IDEAS

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    Cited by:

    1. Boysen, Nils & Bock, Stefan, 2011. "Scheduling just-in-time part supply for mixed-model assembly lines," European Journal of Operational Research, Elsevier, vol. 211(1), pages 15-25, May.
    2. Emilio Moretti & Elena Tappia & Veronique Limère & Marco Melacini, 2021. "Exploring the application of machine learning to the assembly line feeding problem," Operations Management Research, Springer, vol. 14(3), pages 403-419, December.
    3. Boysen, Nils & Emde, Simon & Hoeck, Michael & Kauderer, Markus, 2015. "Part logistics in the automotive industry: Decision problems, literature review and research agenda," European Journal of Operational Research, Elsevier, vol. 242(1), pages 107-120.
    4. de Vries, Jan, 2013. "The influence of power and interest on designing inventory management systems," International Journal of Production Economics, Elsevier, vol. 143(2), pages 233-241.
    5. Mustapha Sali & Evren Sahin, 2016. "Line feeding optimization for Just in Time assembly lines: an application to the automotive industry," Post-Print hal-01265041, HAL.
    6. Maurizio Faccio & Mauro Gamberi & Alessandro Persona & Alberto Regattieri & Fabio Sgarbossa, 2013. "Design and simulation of assembly line feeding systems in the automotive sector using supermarket, kanbans and tow trains: a general framework," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 24(2), pages 187-208, July.
    7. Naliaka V.W. & G.S. Namusonge, 2015. "Role of Inventory Management on Competitive Advantage among Manufacturing Firms in Kenya: A Case Study of Unga Group Limited," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 5(5), pages 87-104, May.
    8. Schmid, Nico André & Limère, Veronique & Raa, Birger, 2021. "Mixed model assembly line feeding with discrete location assignments and variable station space," Omega, Elsevier, vol. 102(C).
    9. Emilio Moretti & Elena Tappia & Martina Mauri & Marco Melacini, 2022. "A performance model for mobile robot-based part feeding systems to supermarkets," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 580-613, September.
    10. Sternatz, Johannes, 2015. "The joint line balancing and material supply problem," International Journal of Production Economics, Elsevier, vol. 159(C), pages 304-318.
    11. Emde, Simon & Boysen, Nils, 2012. "Optimally locating in-house logistics areas to facilitate JIT-supply of mixed-model assembly lines," International Journal of Production Economics, Elsevier, vol. 135(1), pages 393-402.
    12. Adenipekun, Ebenezer Olatunde & Limère, Veronique & Schmid, Nico André, 2022. "The impact of transportation optimisation on assembly line feeding," Omega, Elsevier, vol. 107(C).
    13. Sali, Mustapha & Sahin, Evren, 2016. "Line feeding optimization for Just in Time assembly lines: An application to the automotive industry," International Journal of Production Economics, Elsevier, vol. 174(C), pages 54-67.
    14. Francesco Lolli & Rita Gamberini & Claudio Giberti & Bianca Rimini & Federica Bondi, 2016. "A simulative approach for evaluating alternative feeding scenarios in a kanban system," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4228-4239, July.
    15. Hanson, Robin & Finnsgård, Christian, 2014. "Impact of unit load size on in-plant materials supply efficiency," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 46-52.

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