An optimal integrated QSMS model from cluster analysis
Abstract
Purpose
The purpose of this paper is to develop an optimal model of an integrated quality and safety management system (QSMS).
Design/methodology/approach
Keywords related with these systems were identified from international standards and subsequently mined from a selection of peer reviewed articles that discuss and propose varying forms of integrated models for both systems. Cluster analysis was used to establish the degree to which integrated models, as described in the articles were quality dominant vs safety dominant. Word counts were utilized for establishing content and attributes for each category. An optimal integrated model was developed from the final cluster analysis and substantiated by a one-way analysis of variance. Experts from industry were consulted to validate and fine-tune the model.
Findings
It was determined that characteristics of an optimal integrated model include the keywords “risk,” “safety,” “incident,” “injury,” “hazards,” as well as “preventive action,” “corrective action,” “rework,” “repair,” and “scrap.” It also combines elements of quality function deployment as well as hazard and operability analysis meshed into a plan-do-check-act type work-flow.
Research limitations/implications
Given the vast array of clustering algorithms available, the clusters that resulted were dependent upon the algorithm deployed and may differ from clusters resulting for divergent algorithms.
Originality/value
The optimized model is a hybrid that consists of a quality management system as the superordinate strategic element with safety management system deployed as the supporting tactical element. The model was implemented as a case study, and resulted in 13 percent labor-hour saving.
Keywords
Citation
Odigie, M.E., Badar, M.A., Sinn, J.W., Moayed, F. and Shahhosseini, A.M. (2017), "An optimal integrated QSMS model from cluster analysis", The TQM Journal, Vol. 29 No. 3, pp. 438-466. https://doi.org/10.1108/TQM-12-2015-0150
Publisher
:Emerald Publishing Limited
Copyright © 2017, Emerald Publishing Limited