A fuzzy-based leanness evaluation model for manufacturing organisations

Abstract

In order to evaluate and monitor the impacts of improvement initiatives in terms of the overall leanness level, it is important to identify right performance metrics to measure the current and desired leanness level. Currently, there is a lack of proper methodology to accurately measure the impact of implementation of lean strategies on overall leanness of an organisation. This paper proposes an effective leanness measurement model using the triangular linguistic fuzzy membership function. The effectiveness of the model was demonstrated by a case study. The leanness value of the organisation before implementing lean was 0.12, which was improved to 0.19 after implementing a lean tool. The optimum leanness value of that organisation was calculated to be 0.64. These leanness values provided a quantitative indication of the impacts of improvement initiatives in terms of the overall leanness level, which was found to be highly beneficial as recognised by the case organisation.

Keywords:

• Lean manufacturing
• leanness
• optimum lean range
• performance metrics
• fuzzy
• case study

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1 For reasons of confidentiality, the name of the manufacturer cannot be disclosed. ABC is pseudonym.

Additional information

Notes on contributors

M. A. Amin

Dr. M. A. Amin has been working as a Process Engineer, Lean Maintenance Engineer, Operations Manager and Project Manager in different manufacturing Organisations in Australia. He has over 10 years experiences in implementing lean and continuous improvement strategies in various organisations. He has completed his B.Sc. in Mechanical Engineering during 2008 from Bangladesh University of Technology (BUET), Bangladesh. He received his PhD in Industrial Engineering during 2012 from Queensland University of Technology (QUT), Australia. He is currently working as a Project Manager (Engineering Technical Services) at Tritium, a world leader in e-mobility technology solutions. Amin is currently responsible for delivering a greenfield test facility at Tritium R&D facility, Brisbane, Australia investing more than AUD$10millions which includes complete new infrastructure development with setting up fully compliant Electromagnetic Compatibility (EMC) Testing laboratory along with Environmental Chamber for high voltage electric charging (360kW) station and recognized to be the first high power EMC laboratory in the entire Southern Hemisphere. He presented his research works in a number of conferences and published his research outcomes in various reputed international journals. His research interest includes Optimisation, Fuzzy Multi Criteria Decision-Making, Lean Product Development, Production and Operations Management, Lean Production Systems, Value Added and Value Engineering (VAVE) and the Supply Chain Management.

M. R. Alam

Dr M. R. Alam has been working as a Quality Manager and a Senior Quality Manager for the last 10 years at NOJA Power^®, a leading organization in Australia which designs and manufactures medium and high voltage equipment for electrical distribution networks. He contributed significantly in developing the best practices in design, manufacturing and business processes at NOJA Power and its subsidiaries in Brazil, Mexico and South Africa. He completed his Bachelor Degree in Mechanical Engineering in 1993 from Bangladesh University of Engineering and Technology (BUET), Bangladesh and received his PhD in Mechanical Engineering in 2003 from National University of Singapore (NUS), Singapore. In addition to his full-time employment in industry, he has been lecturing engineering units at Queensland University of Technology (QUT), Australia as a part-time lecturer since 2009 and conducting research in lean manufacturing, operations management, TQM, new product development, risk management and engineering assets management. He presented his research works in a number of conferences and published his research outcomes in various reputed international journals. He has over 18 years work experiences in world-renowned industries in Australia and Singapore. His research interests include Lean Manufacturing, Optimization, Artificial Intelligence in Manufacturing, New Product Development, Risk Management, Engineering Assets Management and Supply Chain Management.

H. Alidrisi

Dr H. Alidrisi is working as an Associate Professor of Industrial Engineering at King Abdulaziz University (KAU), Saudi Arabia. His research interest is in Decision Making and Analysis (Multi-Criteria Decision Making (MCDM).

M. A. Karim

Dr M. A. Karim is currently working as an Associate Professor in the Mechanical Engineering Discipline, Science and Engineering Faculty, Queensland University of Technology, Australia. He received his PhD degree from Melbourne University in 2007. Through his scholarly, innovative, high quality research, he has established a national and international standing. He has authored over 175 peer-reviewed articles, including 90 high quality journal papers, 13 peer-reviewed book chapters, and four books. His papers have attracted about 2800 citations with h-index 26. He is an editor/board member of six reputed journals including Drying Technology and Nature Scientific Reports and supervisor of 26 past and current PhD students. He has been keynote/distinguished speaker at scores of international conferences and invited/keynote speaker in seminars in many reputed universities worldwide. He has won multiple international awards for his outstanding contributions in multidisciplinary fields. His research is directed towards solving acute food industry problems by advanced multiscale and multiphase food drying models of cellular water using theoretical/computational and experimental methodologies. Due to the multidisciplinary framework of food drying models, his research spans engineering, mathematics, biology, physics and chemistry. To address this multidisciplinary challenge, he established the ‘Energy and Drying’ Research Group consisting of academics and researchers across disciplines. He is the recipient numerous national and international competitive grants amounting $2.68 million. He is also a leader in innovatively applying ‘Lean Manufacturing’ concepts in hospital emergency departments to reduce long waiting times and optimize resources. Currently, he is leading research projects with two local (RBWH and RCH) and two international hospitals. His current research areas are food drying, multiscale and multiphase modelling of food drying, Nano fluid solar thermal storage, concentrating PV-thermal collector, and Lean Healthcare Systems.