INTEGRATION OF LEAN SIX SIGMA AND K-MEANS CLUSTERING TECHNOLOGY FOR ENROLLMENT IMPROVEMENT IN INDIAN HIGHER EDUCATION INSTITUTIONS

Abstract
The technical higher education sectors in India currently face intense competition and are greatly impacted by the fastest rate of increase in the number of educational institutions. Following the COVID-19 pandemic, traditional engineering branches in technical higher education institutions such as mechanical engineering, civil engineering, and electrical engineering, are under serious threat of closure due to unexpected demand in the fields of computer science and engineering and related branches. The World Economic Forum anticipates a shortage of over two million skilled mechanical engineers by 2030, intensifying talent shortages in crucial areas including aerospace and automobile manufacturingThe purpose of this article is to investigate whether the Lean Six Sigma - define-measure-analyse-improve-control methodology may be integrated with the K-means clustering method of Group Technology to increase student enrollment in higher education institutions in India. During the research, the admission process was thoroughly examined to identify the reasons for poor admission using statistical tools and techniques. Action research is applied in the admission process of a Mechanical Engineering programme of a higher educational institution in India. The presented concept demonstrates how the Six Sigma DMAIC methodology is applied in conjunction with K-Means clustering directly to admission procedures at higher education institutions to improve enrolment. Integration of Lean Six Sigma and Group Technology for enrolment improvement presented in this paper is a novel approach. The chosen methodology should be applied to other institutions to validate the results and make necessary changes to this approach.