The Application of Machine Learning to Consolidate Critical Success Factors of Lean Six Sigma

Achinthya D. Perera,Nigel P. Grigg,Amardeep Singh,Mark Tunnicliffe,Nihal P. Jayamaha

doi:10.1109/access.2021.3103931

Achinthya D. Perera, Nigel P. Grigg + Show 3 more

Open Access

https://doi.org/10.1109/access.2021.3103931

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Abstract

Lean six sigma (LSS) is a quality improvement phenomenon that has captured the attention of the industry. Aiming at a capability level of 3.4 defects per million opportunities (Six Sigma) and efficient (lean) processes, LSS has been shown to improve business efficiency and customer satisfaction by blending the best methods from Lean and Six Sigma (SS). Many businesses have attempted to implement LSS, but not everyone has succeeded in improving the business processes to achieve expected outcomes. Hence, understanding the cause and effect relationships of the enablers of LSS, while deriving deeper insights from the functioning of the LSS strategy will be of great value for effective execution of LSS. However, there is little research on the causal mechanisms that explain how expected outcomes are caused through LSS enablers, highlighting the need for comprehensive research on this topic. LSS literature is overwhelmed by the diverse range of Critical Success Factors (CSFs) prescribed by a plethora of conceptual papers, and very few attempts have been made to harness these CSFs to a coherent theory on LSS. We fill this gap through a novel method using artificial intelligence, more specifically Natural Language Processing (NLP), with particular emphasis on cross-domain knowledge utilization to develop a parsimonious set of constructs that explain the LSS phenomenon. This model is then reconciled against published models on SS to develop a final testable model that explains how LSS elements cause quality performance, customer satisfaction, and business performance.

Highlights

T he growth of customer demand for high-quality products and services with speedy delivery, and increased competition due to globalization have forced organizations to explore profitable solutions to gain a competitive advantage [1], [2]
The causal mechanisms explaining how Lean Six Sigma (LSS) constructs are related to quality improvement project success and bottom line results of organizations remain sketchy and the Lean element of LSS is absent in almost all explanations
When explaining LSS outcomes, it is not possible to ignore Critical Success Factors (CSFs) since these are critical to the implementation of LSS

Summary

Introduction

T he growth of customer demand for high-quality products and services with speedy delivery, and increased competition due to globalization have forced organizations to explore profitable solutions to gain a competitive advantage [1], [2]. Toward a state of perfection, resulting in little or no unnecessary wastage in a production or service delivery system [5], [10], [11]. Both methodologies have been popular since the 1980s, while their amalgamation as ‘Lean Six Sigma’ has been discussed in SCOPUS since 2000 [12]. The increase in LSS applications in industry over the past two decades is indicative of the industry’s interest in this approach [3], [13]–[15]

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