 Statistical investigation of Lean Six Sigma for waste reduction in Indian SMES by identify rank define analyse improve control modelP.N. Ramkumar and K.P. Satish International Journal of Productivity and Quality Management, 2020, vol. 30, issue 2, 252-277 Abstract: Lean manufacturing is capable of reducing the existing rates of production to a reasonable amount and also to raise the productivity by improving the quality of the material, and hence to maximise the number of customers. In this research paper, the LSS is practiced in the small and medium scale industries for improving the productivity of the firm. For that, a new statistical method named identify rank define analyse improve control (IRDAIC) model is actualised in the Indian SMEs for handling the survey. For optimising the industrial parameters multiple nonlinear regression analysis and enhanced grey wolf optimisation is used in this paper. The proposed hybrid statistical assessment and optimisation process is executed and evaluated in the working platform of MATLAB in terms of production cost. Ultimately, from the evaluation the proposed novel statistical optimisation technique is optimal for improving the productivity of the Lean Six Sigma manufacturing firm respectively. Keywords: industrial production; optimisation; metaheuristic algorithm; regression analysis. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpqma:v:30:y:2020:i:2:p:252-277 Access Statistics for this article More articles in International Journal of Productivity and Quality Management from Inderscience Enterprises Ltd |
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