Modelling short-term manufacturing flexibility by human intervention and its impact on performance

Ton G. de Kok

International Journal of Production Research, 2018, vol. 56, issue 1-2, 447-458

Abstract: Short-term manufacturing flexibility is the capability to respond to unforeseen short-term and immediate events during operation. Explicitly modelling short-term manufacturing flexibility is extremely hard as it implies that it is possible to prescribe responses to all possible events in all possible states of the system under consideration. We propose an implicit modelling approach where we only model the frequency of responses to unforeseen events and the impact of the response on the evolution of the process under consideration. This allows us to dramatically reduce model complexity while preserving empirical validity of the model. We introduce the concepts of intervention–independent performance (IIP) and intervention–dependent performance (IDP). We present a methodology to gather IIP and IDP indicator information. We propose another process to use this information together with historical transactional data and forecasts to make tactical trade-offs that result in control policy parameters. We illustrate our modelling approach by a generic inventory control model with replanning of replenishment orders. We apply the model in a case study characterised by highly utilised production lines, high set-up times and dynamic demand. We provide empirical evidence of the validity of the proposed methodologies.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2017.1401750 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:447-458

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2017.1401750

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().