Application of heuristics for packing problems to optimise throughput time in fixed position assembly islands

Thomas Henke and Jochen Deuse

International Journal of Productivity and Quality Management, 2022, vol. 36, issue 1, 150-168

Abstract: Accompanied with globalisation, companies are confronted with new competitors and price competitions. In order to meet these challenges manufactures strive to increase their efficiency throughout the value stream. Especially special machine manufactures assembling in fixed position assembly islands show a high non-value adding share, since their assembly and logistical processes are characterised by a low degree of standardisation and maturity. This leads to a high spread of throughput times and increases the risk of delivery delays. To improve this weakness, this paper presents an approach to increase the degree of standardisation and to lower and stabilise the throughput time. The new approach bases on heuristics for packing problems and applies them to the material supply. By that, the allocation of the supplied components is optimised, as a result of which search times and path lengths for walking and transporting are shortened and the value adding time share is increased.

Keywords: large scale production; fixed position assembly; fixed position assembly island; packing problems; rectangle packing area minimisation problem; RPAMP; strip packing problem; SPP; stack ceiling algorithm; heuristics; throughput time. (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=124387 (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:ids:ijpqma:v:36:y:2022:i:1:p:150-168

Access Statistics for this article

More articles in International Journal of Productivity and Quality Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().