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Capacity investment and the value of operational flexibility in manufacturing systems with product blending

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  • Shailesh S. Kulkarni
  • David Francas

Abstract

A distinct feature of process industries such as food, chemical and consumer packaged goods is the blending of intermediates into finished goods. In the context of such manufacturing systems the levels of different inputs that can be blended to process a final good define the range of flexibility. Likewise, the cost for using (blending) different inputs defines the mobility element of flexibility. In this paper, we investigate capacity investment and the value of flexibility in the presence of such product blending constraints. We are motivated by recent case studies of food manufacturers, in particular, those manufacturers that seek to increase flexibility via blending of intermediates. We analyse stochastic programs under demand uncertainty of such manufacturing systems. We provide analytical insights into trade-offs when range and mobility are interdependent. Our analytical work gives structural insights into subtle complementarity and substitution effects between dedicated and shared resources in the presence of blending. We analytically show that there is a degradation in the cost performance of such systems with an increase in correlation. We characterise the optimal blending fraction that balances the benefits of higher range with higher costs (lower mobility). Our numerical work shows that a moderate level of blending can significantly improve flexibility and that well-known guidelines for designing limited flexibility change in the presence of blending. For example, blending, even if optimally designed, weakens the appeal of chaining configurations. Overall our work guides resource configuration in industries where product blending is an integral part of the production process.

Suggested Citation

  • Shailesh S. Kulkarni & David Francas, 2018. "Capacity investment and the value of operational flexibility in manufacturing systems with product blending," International Journal of Production Research, Taylor & Francis Journals, vol. 56(10), pages 3563-3589, May.
  • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:10:p:3563-3589
    DOI: 10.1080/00207543.2017.1374576
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    Cited by:

    1. Changzheng Gao & Xiuna Wang & Dongwei Li & Chao Han & Weiyang You & Yihang Zhao, 2023. "A Novel Hybrid Power-Grid Investment Optimization Model with Collaborative Consideration of Risk and Benefit," Energies, MDPI, vol. 16(20), pages 1-23, October.
    2. Marta Pérez-Pérez & Canan Kocabasoglu-Hillmer & Ana María Serrano-Bedia & María Concepción López-Fernández, 2019. "Manufacturing and Supply Chain Flexibility: Building an Integrative Conceptual Model Through Systematic Literature Review and Bibliometric Analysis," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(1), pages 1-23, December.
    3. Somen Dey & R. R. K. Sharma & Balbir Kumar Pandey, 2019. "Relationship of Manufacturing Flexibility with Organizational Strategy," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(3), pages 237-256, September.
    4. Song, Sangcheol, 2021. "When do multinational corporations adjust production volume flexibly among in-network subsidiaries?," Journal of Business Research, Elsevier, vol. 135(C), pages 532-542.
    5. Wang, Liangliang & Yu, Junli & Chan, Kam C., 2021. "Product line transformation, foreign sales, and firm value: Evidence from COVID-19 pandemic governance in urban China," Research in International Business and Finance, Elsevier, vol. 58(C).
    6. J. Prince Vijai, 2021. "Production network, technology choice, capacity investment and inventory sourcing decisions: operational hedging under demand uncertainty," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 1164-1191, December.

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