Data analytics in zero defect manufacturing: a systematic literature review and proposed framework

Abstract

Data analytics (DA) has gained significant attention within the context of Zero-Defect Manufacturing (ZDM), as it holds the potential to enhance product quality through the utilisation of large-scale operational data in manufacturing industries. However, the existing literature on product-oriented ZDM lacks a standardised approach to DA, as independent studies employ diverse methods to structure the data analytics process. This fragmentation impedes the development of a cohesive understanding of the field. To address this gap, this study undertakes a systematic literature review to identify current trends of DA within ZDM. The analysis encompasses 188 recent academic papers, presenting the results of a content analysis across six key dimensions. Furthermore, the study examines the challenges associated with implementing DA in ZDM and proposes a generic framework encompassing essential components. The framework aims to provide guidance to practitioners and academicians seeking to leverage data analytics within the ZDM domain. In addition to the practical framework, the study contributes to existing knowledge by outlining four potential areas for future research. The proposed framework and identified research areas serve as valuable resources for industry professionals and researchers, facilitating a more standardised and informed approach to data analytics in the pursuit of ZDM.