Journal article
Managing uncertainty in demand through inventory and workforce development
International journal of production research, Vol.59(21), pp.6507-6527
11/02/2021
DOI: 10.1080/00207543.2020.1818861
Abstract
This paper studies whether and how a manufacturer can mitigate the effects of demand uncertainty during production ramp up by jointly managing inventory and capacity development, determined by the productivity of a heterogeneous workforce. One way the manufacturer can direct its capacity development is by recognising that workers become more productive as they gain experience when making scheduling decisions. We consider a situation in which demands for multiple products are periodically revealed and a manufacturer must decide what each individual does in the production process, how much inventory is accumulated, and how demands are met. To study the potential benefits, we formulate a Markov decision process model which we solve using a one-step lookahead approximation. Results of an extensive computational study show that, given the effectiveness associated with both directing capacity and holding inventory, manufacturers should consider the workforce's capacity to learn when making job assignments during production ramp up. Analysis of the results suggests that inventory and capacity building patterns depend on product value and the workforce's experience levels. Further analysis shows that slower learners and those with the potential to achieve higher productivity should specialise more. Faster learners, on the other hand, are best suited for cross training.
Details
- Title: Subtitle
- Managing uncertainty in demand through inventory and workforce development
- Creators
- Silviya Valeva - Rice UniversityMike Hewitt - Loyola University ChicagoBarrett W. Thomas - University of Iowa
- Resource Type
- Journal article
- Publication Details
- International journal of production research, Vol.59(21), pp.6507-6527
- Publisher
- Taylor & Francis
- DOI
- 10.1080/00207543.2020.1818861
- ISSN
- 0020-7543
- eISSN
- 1366-588X
- Grant note
- DOI: 10.13039/100000147, name: Division of Civil, Mechanical and Manufacturing Innovation, award: 1266010
- Language
- English
- Date published
- 11/02/2021
- Academic Unit
- Bus Admin College; Business Analytics
- Record Identifier
- 9984380499202771
Metrics
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