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Evaluation of enterprise-level benefits of manufacturing flexibility

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  • Chandra, Charu
  • Everson, Mark
  • Grabis, Janis

Abstract

An enterprise-level flexible manufacturing approach for a multi-product manufacturer like an automotive company requires a cost-effective mix of many key enablers, including flexible assembly plants, part commonality between products, and supply base flexibility. This paper develops a strategic planning model that determines the overall business value of flexible manufacturing systems. The model is designed to be capable of dealing with problems of realistic size and scope. Interpretation of results of the model gives important strategic insights on factors influencing manufacturing flexibility and capacity requirements in the presence of these factors. The model is applied to study a flexibility evaluation problem faced by a major automotive company. The experimental results show that flexibility enablers such as flexible product to manufacturing facility assignments and part commonality can lead to improved profitability. Increases in profitability of up to 17% (>$300 M/year) are seen in the modeled system. Increased commonality and/or flexibility also result in a reduction of the optimal capacity for the assembly system while simultaneously slightly improving sales. These results are robust with respect to introduction of the regulatory compliance issue of fuel economy standards, although the incremental profits from improved flexibility and commonality are reduced by approximately 25% when fuel economy standards are included.

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  • Chandra, Charu & Everson, Mark & Grabis, Janis, 2005. "Evaluation of enterprise-level benefits of manufacturing flexibility," Omega, Elsevier, vol. 33(1), pages 17-31, February.
  • Handle: RePEc:eee:jomega:v:33:y:2005:i:1:p:17-31
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    2. Hallgren, Mattias & Olhager, Jan, 2009. "Flexibility configurations: Empirical analysis of volume and product mix flexibility," Omega, Elsevier, vol. 37(4), pages 746-756, August.
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    4. Gong, Zhejun & Hu, Sun, 2008. "An economic evaluation model of product mix flexibility," Omega, Elsevier, vol. 36(5), pages 852-864, October.
    5. Tognetti, Alice & Grosse-Ruyken, Pan Theo & Wagner, Stephan M., 2015. "Green supply chain network optimization and the trade-off between environmental and economic objectives," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 385-392.
    6. Dipankar Bose & A. K. Chatterjee & Samir Barman, 2016. "Towards dominant flexibility configurations in strategic capacity planning under demand uncertainty," OPSEARCH, Springer;Operational Research Society of India, vol. 53(3), pages 604-619, September.
    7. Francas, David & Löhndorf, Nils & Minner, Stefan, 2011. "Machine and labor flexibility in manufacturing networks," International Journal of Production Economics, Elsevier, vol. 131(1), pages 165-174, May.
    8. Wang, Sinan & Zhao, Fuquan & Liu, Zongwei & Hao, Han, 2017. "Heuristic method for automakers' technological strategy making towards fuel economy regulations based on genetic algorithm: A China's case under corporate average fuel consumption regulation," Applied Energy, Elsevier, vol. 204(C), pages 544-559.
    9. Wu, Y. & Frizelle, G. & Efstathiou, J., 2007. "A study on the cost of operational complexity in customer-supplier systems," International Journal of Production Economics, Elsevier, vol. 106(1), pages 217-229, March.
    10. Francas, David & Kremer, Mirko & Minner, Stefan & Friese, Markus, 2009. "Strategic process flexibility under lifecycle demand," International Journal of Production Economics, Elsevier, vol. 121(2), pages 427-440, October.
    11. Volling, Thomas & Matzke, Andreas & Grunewald, Martin & Spengler, Thomas S., 2013. "Planning of capacities and orders in build-to-order automobile production: A review," European Journal of Operational Research, Elsevier, vol. 224(2), pages 240-260.
    12. Gong, Zhejun, 2008. "An economic evaluation model of supply chain flexibility," European Journal of Operational Research, Elsevier, vol. 184(2), pages 745-758, January.

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