Quality process control and resourcing in manufacturing firms

Abstract

Statistical Process Control (SPC) is employed to support the effective quality performance of production and manufacturing processes. The control chart is a type of SPC utilized to reduce variability in key quality parameters, leading to the production of quality conforming products. Control charts, such as the Exponentially Weighted Moving Average (EWMA) are widely used to reduce variation, improve productivity, and ensure quality. However, small manufacturers face challenges that may prevent their effective use of quality control charts. One such challenge relates to resource constraints. These constraints tend to inhibit the conduct of quality inspections at high rates. With this in mind, the present study sets out to develop and present an improved EWMA control chart for effective quality control that takes into consideration significant resource constraints in a small aluminium manufacturing firm. The findings suggest that adopting the improved EWMA chart can enhance the detection of any increase in defectives without the need for additional resources. The improved EWMA control chart provides small manufacturers with an enhanced quality conforming tool developed based on practical realities. Implications for both practice and theory are also highlighted.

Keywords:

• Quality
• process control
• control chart
• resource constraints
• small manufacturing firms

Additional information

Notes on contributors

Salah Haridy

Salah Haridy is an Associate Professor in the Department of Industrial Engineering and Engineering Management at University of Sharjah, UAE. He received his PhD from the Nanyang Technological University, Singapore in 2014. He is the recipient of the 2013 Mary G. and Joseph Natrella Scholarship awarded by the American Statistical Association (ASA) and the 2014 Richard A. Freund International Scholarship awarded by the American Society for Quality (ASQ). He is an ASQ Certified Six Sigma Green Belt. His research interests cover quality engineering, Six Sigma, statistical process control, applied statistics and design of experiments.

Udechukwu Ojiako

Udechukwu Ojiako is Professor of Engineering Management at the University of Sharjah, United Arab Emirates. Udi currently serves as an Associate Editor of Production Planning & Control. He holds a PhD in Project Management (from the University of Northumbria – 2005), a PhD in Business (from University of Hull – 2015) and a PhD in Law (from Aberystwyth University – 2023). Udi is a qualified Barrister-at-Law (Honourable Society of the Middle Temple). Udi’s research interest is broad. It spans comparative decision-making and cross-disciplinary research situated in project-centric operational and business environments.

Ahmed Maged

Ahmed Maged is an Assistant Professor at the Department of Mechanical Engineering Benha University, Egypt. He received his Ph.D. in 2022 from the City University of Hong Kong in Advanced Design and Systems Engineering. Ahmed’s research interest is focused on Quality Engineering, Machine Learning, and Lean Six Sigma.

Mezoon Al Remeithi

Mezoon Al Remeithi is a senior engineer in Dubai Electricity and Water Authority (DEWA). She obtained her Bachelor of Science degree in Electrical Engineering from the American University of Sharjah, United Arab Emirates. She received her MSc degree in Engineering Management with honours from University of Sharjah, United Arab Emirates. Her research interests cover quality engineering, statistical process control and improvement.

Hamdi Bashir

Hamdi Bashir holds a PhD degree from McGill University, Canada. Currently, he is a Professor of Industrial Engineering and Engineering Management at the University of Sharjah, UAE. Prior to joining this university, he held faculty positions at Sultan Qaboos University, University of Alberta, and Concordia University. Bashir’s research interest focuses on modeling and analyzing complexity in engineering management using data mining and graph theory related techniques. He is a senior member of the Institute of Industrial and Systems Engineers.

Mohammad Shamsuzzaman

Mohammad Shamsuzzaman is a Professor of Industrial Engineering and Engineering Management at the University of Sharjah, United Arab Emirates. He received his MEng and PhD degrees in Industrial Engineering from Asian Institute of Technology, Thailand and Nanyang Technological University, Singapore in 2000 and 2005, respectively. His current research focuses on statistical process control, process improvement using Lean Six Sigma, quality in maintenance, design of experiments, applied statistics, and multi-criteria decision-making. He is a member of the American Society for Quality (ASQ) and Industrial Engineering and Operations Management (IEOM) Society International, USA.