Simulation-based Six Sigma value function for system-level performance assessment and improvement
Raid Al-Aomar and
Sohail Chaudhry
International Journal of Productivity and Performance Management, 2018, vol. 67, issue 1, 66-84
Abstract:
Purpose - The purpose of this paper is to develop a simulation-based value function (VF) that combines multiple key performance indicators (KPIs) into a unified Sigma rating (SR) for system-level performance assessment and improvement. Design/methodology/approach - Simulation is used as a platform for assessing the multiple KPIs at the system level. A simple additive VF is formed to combine the KPIs into a unified SR using the analytical hierarchy process and the entropy method. Value mapping is utilized to resolve the conflict among KPIs and generate a unified value. These methods are integrated into the standard Six Sigma define-measure-analyze-improve-control (DMAIC) process. Findings - Simulation results provided the Six Sigma DMAIC process with system-level performance measurement and analysis based on multiple KPIs. The developed VF successfully generated unified SRs that were used to assess various performance improvement plans. Research limitations/implications - The accuracy and credibility of the results obtained from using the proposed VF are highly dependent on the availability of pertinent data and the accuracy of the developed simulation model. Practical implications - The proposed approach provides Six Sigma practitioners and performance mangers with a mechanism to assess and improve the performance of production and service system based on multiple KPIs when conducting Six Sigma studies. Originality/value - This paper contributes to the previous research by handling multiple KPIs in Six Sigma studies conducted at the system level using simulation and VF. The research also provides guidelines for using the different methods of weights assessment to form the VF within the DMAIC process.
Keywords: Six Sigma; Performance management; Analytical hierarchy process; Simulation; Entropy method; Value function (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (text/html)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (application/pdf)
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:eme:ijppmp:ijppm-01-2016-0007
DOI: 10.1108/IJPPM-01-2016-0007
Access Statistics for this article
International Journal of Productivity and Performance Management is currently edited by Dr Luisa Huatuco and Dr Nicky Shaw
More articles in International Journal of Productivity and Performance Management from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().