Abstract
For many manufacturing firms, the ability to match demand and supply is key to their success. Failure to do so could lead to loss of revenue, reduced service levels, negative impact on reputation, and decline in the company’s market share. Unfortunately, recent developments, such as intense market competition, product proliferation, and the increase in the number of products with a short life cycle, have created an environment where customer demand is volatile and unpredictable. In such an environment, traditional operations strategies such as building inventory, investing in capacity buffers, or increasing committed response time to consumers do not offer manufacturers a competitive advantage. Therefore, many manufacturers have started to adopt an operations strategy known as process flexibility to better respond to market changes without significantly increasing cost, inventory, or response time (see Simchi-Levi 2010).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chou, M., Teo, C., & Zheng, H. (2008). Process flexibility: design, evaluation, and applications. Flexible Services and Manufacturing J., 20(1): 59–94.
Chou, M., Chua, G., Teo, C., & Zheng, H. (2010). Design for process flexibility: efficiency of the long chain and sparse structure. Operation Research, 58, 43–58.
Chou, M., Chua, G., Teo, C., & Zheng, H. (2011). Processs flexibility revisited: the graph expander and its applications. Operation Research, 59, 1090–1105.
Chou, M., Chua, G., Teo, C., & Zheng, H. (2012). On the performance of sparse process structures in partial postponement production systems. Working Paper.
Gale, D., & Politof, T. (1981). Substitutes and complements in network flow problems. Discrete Applied Mathematics, 3, 175–186.
Graves, S. C. (2008). Flexibility principles. In Building intuition: insights from basic operations management models and principles (Chapter 3, pp. 33–51) New York: Springer.
Hopp, W., Tekin, E., & Van Oyen, M. (2004). Benefits of skill chaining in serial production lines with cross-trained workers. Management Science, 50, 83–98.
Jordan, W., & Graves, S. C. (1995). Principles on the benefits of manufacturing process flexibility. Management Science, 41, 577–594.
Murota, K., & Shioura, A. (2005). Substitutes and complements in network flows viewed as discrete convexity. Discrete Mathematics, 2, 256–268.
Simchi-Levi, D. (2010). Operations rules: delivering customer value through flexible operations. Cambridge, MA: MIT Press.
Simchi-Levi, D., Wei, Y. (2012) Understanding the Performance of the Long Chain and Sparse Designs in Process Flexibility. Operations Research, 60(5):1125–1141
Strassen, V. (1969). Gaussian elimination is not optimal. Nmerische Mathematik, 13, 354–356.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media New York
About this chapter
Cite this chapter
Simchi-Levi, D., Chen, X., Bramel, J. (2014). Process Flexibility. In: The Logic of Logistics. Springer Series in Operations Research and Financial Engineering. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-9149-1_13
Download citation
DOI: https://doi.org/10.1007/978-1-4614-9149-1_13
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-9148-4
Online ISBN: 978-1-4614-9149-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)