Integrating Six Sigma Culture and TPM Framework to Improve Manufacturing Performance in SMEs

Integrating Six Sigma Culture and TPM Framework to Improve Manufacturing Performance in SMEs

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Article ID: iaor201523848
Volume: 30
Issue: 5
Start Page Number: 745
End Page Number: 765
Publication Date: Jul 2014
Journal: Quality and Reliability Engineering International
Authors: ,
Keywords: manufacturing industries
Abstract:

Worldwide, small and medium enterprises (SMEs) have been accepted as the engine of economic growth, especially in the emerging economies, and for promoting equitable development their contribution as a component to nation's infrastructure is relatively high. Global competition forces SMEs to improve their competitiveness by enhancing their manufacturing performance. Hence, they have to pay attention to the reliability of their production processes as well as their commitment to quality management practices. In present times, because of automation and large‐scale mechanization, higher plant availability, better product quality and longer equipment life had assumed considerable significance among the SMEs. In order to meet the above challenges, adoption and practice of proactive maintenance strategies along with execution of best management practices, i.e. lean Six Sigma (LSS), has become essential for organizations to bring down maintenance and production costs. As evident from literature, both total productive maintenance (TPM) and Six Sigma are key business process strategies employed by SMEs to enhance their manufacturing performance. However, whilst there is significant research information available on implementing these systems in an independent manner, there is little information available relating to the integration of these approaches to provide a unified and highly effective implementation framework. The purpose of this paper is thus to develop an integrated model based on Six Sigma and TPM framework focusing on adding performance indicators. The goals of the study were achieved by utilizing various tools such as ‘brainstorming sessions, pareto analysis fish‐bone diagrams, histograms, FMEA, box plots, control charts and process capability plots for analysis’. While implementation of such twin framework requires greater management commitment in terms of training, resources and integration, they are also expected to provide higher levels of equipment and plant performance as evident from the results. The results show significant improvement in OEE level (Before 50, 54 and after 76, 83 for M/C –I and M/c‐II), reduction in rework (from 22% to 10%), reduction in maintenance versus operation cost (from 30% to 10%) and reduction in defect rate (from 24.82% to 5%) and average outgoing quality level (from 30% to 5%). The substantial improvement in sigma level from 2.16 and 2.64 to 4.01 and 4.12 for M/C –I and M/C‐II resulted in financial savings of approximately $2 m per annum.

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