Abstract
The increasing popularity of lean thinking has made the analysis of value-adding (VA) and non-value adding (NVA) a popular activity to eliminate waste and improve productivity. Despite the great success of the Taiichi Ohno’s waste taxonomy and its adaptation and diffusion into the maintenance sector, a systematic classification of VA and NVA remains as a significant challenge for lean practitioners. The aim of this research is to develop a system to classify VA and NVA activities for lean applications in turnaround maintenance (TAM) projects. First, a comprehensive literature review was conducted on existing methods of defining and classifying value and waste. As a result of this review, an initial system to classify VA and NVA in TAM was proposed, which was then refined in three focus group studies conducted with a group of TAM participants. The improved classification system was evaluated by applying value stream mapping (VSM) in terms of the ontology effectiveness and efficiency using a sample case. The classification system contributes to an accurate classification of value, and waste and the relevant root causes in the TAM processes. The classification system provides an insight on a consolidated understanding and classification of VA and NVA in TAM projects.
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No potential conflict of interest was reported by the authors.
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Notes on contributors
Wenchi Shou
Dr Wenchi Shou, PhD, is a Lecturer in School of Computing, Engineering and Mathematics at Western Sydney University Her research interests are in value stream mapping, lean construction, Building Information Modelling, and simulation, exploring the application of digital lean to improve construction and operation performance across building, infrastructure, and oil and gas industries. She received a PhD degree in construction management from Curtin University in 2018.
Jun Wang
Dr Jun Wang, PhD, is a Lecturer in Construction Management at Deakin University. He received his PhD in 2018 from Curtin University. During the last 5 years, his research interests focus mainly on leveraging emerging technologies, such as Building Information Modelling, Internet of Things, Linked Data and Blockchain, to improve construction and operation performance across building, infrastructure, and oil and gas industries. As a Chief Investigator, he has been involved in two Australian Research Council funded projects. He received the PhD degree in construction management from Curtin University in 2018.
Peng Wu
Dr Peng Wu, PhD, is an Associate Professor with the Department of Construction Management, and an Associate Director with the Australasian Joint Research Centre for Building Information Modelling, Curtin University. His research areas include sustainable construction, lean production and construction, production and operations management, and life cycle assessment. In 2016, he received the Discovery Early Career Research Award from the Australian Research Council, which is a prestigious award to support excellent basic and applied research by early career researchers. He received the PhD degree in project management from National University of Singapore, Singapore, in 2012.
Xiangyu Wang
Dr Xiangyu Wang, PhD, is a Professor with the Department of Construction Management, and Director with the Australasian Joint Research Centre for Building Information Modelling, Curtin University. He is an expert and leading researcher on automation in construction. He received five Linkage grants, five Discovery grants and one Training Centre grant from Australia Research Council from 2013 to 2019. He is on the Board of Directors and country representatives of International Society of Computing in Civil and Building Engineering (ISCCBE) and International Association of Automation and Robotics in Construction (IAARC), two most highly regarded academic societies in Automation in Construction. He received the PhD degree from Purdue University in 2015.