A Machine Learning Classification Model for Process Waste Types Identification and Business Process Re-Engineering Automation

Abstract

Machine learning applications in solving business and industrial challenges are indisputable, and the results are of great value. Similarly, business process re-engineering brings excellent value, yet it is an ongoing challenge to continuous improvement strategies. That is because of its implementation complexity, the lack of required relevant expertise and domain knowledge, and the enormously expensive implementation costs. Having in mind digital transformation and the data it generates. This paper proposes a machine learning model to identify and classify waste types in business processes based on Lean Six Sigma to re-engineer the business processes. The Lean Six Sigma concepts inspired the Machine Learning model development in eliminating waste. The paper proposes input attributes for the machine learning model identified through interviewing experts in implementing business process re-engineering projects and Lean Six Sigma Black Belt holders. The paper presents the evaluation criteria and an implementation case study results. In future, the researcher intends to implement the model in selected case studies in aviation.