A new model to implement Six Sigma in small- and medium-sized enterprises

Taieb Ben Romdhane, Ahmed Badreddine and Manel Sansa

International Journal of Production Research, 2017, vol. 55, issue 15, 4319-4340

Abstract: The Six Sigma approach improves the quality of products in order to ensure customers’ satisfaction. This approach has yielded to interesting results for large enterprises. However, its implementation remains difficult for small- and medium-sized enterprises (SME). In fact, the use of the same tools is insufficient to achieve the objectives when considering financial constraints and the lack of data. The regular tools are complex for SMEs which require an adapted model to implement the approach successfully. In this paper, we propose a new model having the objective to facilitate the integration of Six Sigma in SMEs by avoiding the use of Black Belts, optimising the implementation costs and period, simplifying the Six Sigma structure and enhancing the communication between staff and managers. The model includes two imbricated loops: the first offers immediate improvement actions by estimating the capability and the stability of the process, while the second provides profound improvement actions using the fuzzy logic system and the analytic hierarchical process (AHP) method. An example illustrates the application of the proposed model in an SME.

Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2016.1249430 (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:55:y:2017:i:15:p:4319-4340

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

DOI: 10.1080/00207543.2016.1249430

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 ().