Risk-based analysis of manufacturing systems
Igor Lazov
International Journal of Production Research, 2019, vol. 57, issue 22, 7089-7103
Abstract:
A manufacturing system considered here consists of a machine that processes parts and an automatic conveyor that transports immediately a finished part to an assembly cell (i.e. a single workstation facility is examined). The system can hold a maximum number of processed parts on the conveyor, which determines its size. Modelling the system as a family of Birth–Death Processes with finite size in equilibrium, indexed by the system utilisation parameter, and depending on the concepts of system information and system entropy (i.e. mean information), we promote a risk-based analysis of manufacturing systems. The current number of processed parts on the conveyor determines the system particular states. The performance measures of a system are: risk (i.e. uncertainty) of the system (represented by system entropy), throughput of the system, utilisation of the machine, utilisation of the conveyor, and information range of the system. They are simultaneously investigated with respect to the system utilisation parameter, in order for an optimal trade-off among them to be established. This analysis is illustrated on the information linear, Erlang, Binomial and Pascal held manufacturing systems. Regarding the managerial insights, a use case of a system target output is considered, comparing the above system types. This approach can also be used for analysis of an assembly line consisting of multiple machines that have different operation times and buffers between them.
Date: 2019
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2019.1577564 (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:57:y:2019:i:22:p:7089-7103
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2019.1577564
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 ().