Organisations are striving to increase their overall performance efficiency to cope with growing process complexity due to the development of advanced manufacturing technologies. Lean Six Sigma 4.0 (LSS4.0) approach is a hybrid technique adopted in industries, integrating new technologies with existing LSS approaches to reduce waste. The selection of best-fit projects by industries determines the success of an organisation. This study aims to evaluate and prioritise project alternatives using the inter-valued neutrosophic analytic network process (ANP)-technique for order of preference by similarity to ideal solution (TOPSIS).
An automotive component manufacturing organisation is identified to carry out a case study. The prioritisation problem is modelled as a multi-criteria decision-making problem. Thirty sub-criteria are identified from a literature review and grouped into six dimensions. The global weights of sub-criteria are obtained using the ANP technique, and the alternative projects are evaluated using the TOPSIS method.
The management dimension is found to have a high-priority score of 0.32, followed by the technological dimension with 0.26 score. The project with a closeness coefficient index of 0.97 is concluded as the best-fit project.
Results of the analysis clearly depict the role and necessity of management commitment and technological infrastructural requirements for LSS4.0 projects in an organisation. The results/inferences of this study aid management and senior managers to identify and focus on significant criteria that have a strong influence on project selection.
Development of a structured approach for LSS4.0 project selection in manufacturing organisations by describing project evaluation as a decision-making problem and deriving solutions using a neutrosophic number set.
