This publication showcases the 7th Asia-Pacific Conference on Manufacturing System and 6th International Manufacturing Engineering Conference (iMEC-APCOMS 2024) proceedings. It emphasizes the UN Sustainable Development Goals in recent developments and significant challenges in manufacturing industry, along with the emergence of intelligent manufacturing engineering and technology, which are critical for adopting Industry 4.0. The book discusses both traditional and advanced approaches used in various intelligent manufacturing applications. Readers can expect to gain a comprehensive understanding of current trends, challenges, solutions, and mitigating factors from this publication.
chapter 1. Enhancing Machining Efficiency: Exploring the Optimal MQL
parameters for Turning AA6061-T6 with the Taguchi Method.- chapter 2. The
Support Vector Regression Method with The Grid Search Algorithm in
Forecasting Sales of Milk Product.- chapter
3. Knowledge Management Strategic
and Implementations for Sustainable Tourism Industry: Evaluating Stakeholder
Engagement and Organizational Performance Using an Interpretative Structural
Modelling (ISM).- chapter
4. An Aggregate Production Planning Model under
Carbon Trading Constraints for Sustainable Operations .- chapter
5.
Supersonic Separator Nozzle: A Review.- chapter
6. Prioritized Performance of
Circular Economy in Batik SMEs Performance: Interpretive Structural Modeling
Approach.- chapter
7. Effect of Correlated Color Temperature on Human
Attention as a Measure of Power Spectral Density Using EEG.- chapter
8.
Design of Printing Tools for Food Packaging Made from Rice Husk Using the
Quality Function Deployment Method.- chapter
9. Process Signature in
Machining of 316L Stainless Steel Under Dry and Flood Condition.- chapter
10.
Human Cyber Physical System in Manufacturing 4.0: An Application for
Intelligent SCADA-Based Manufacturing.- chapter
11. A Hybridized Artificial
Bee Colony and Electric Eel Foraging Algorithm for Constrained Engineering
Problem.- chapter
12. Enhancing Experiential Learning in Manufacturing
Engineering Technology Courses: A Case Study of TVET Education in Malaysia
Technical University Network (MTUN).- chapter
13. Classification of Anabas
testudineus and Oreochromis niloticus Using Deep Learning.- chapter
14.
Enhancing Performance of Batik SMEs through Cleaner Production Adoption:
Insights from Clustering Algorithm Analysis.- chapter
15. A Multi-Echelon
Fish Supply Chain Model with Waste Recycling.- etc.
Siti Nadiah Mohd Saffe Siti Nadiah Mohd Saffe is a Senior Lecturer at the Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA), Pekan, Malaysia. She pursued her PhD at the University of Tokushima, Japan, and received her Doctor of Engineering in Intelligent Structures and Mechanics Systems Engineering in 2015. Her research interests focus on advanced manufacturing techniques and Finite Element Method (FEM), with an emphasis on integrating sustainability and innovation into manufacturing practices.
Siti Zubaidah Ismail Siti Zubaidah Ismail is a Senior Lecturer at the Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA), Pekan, Malaysia. She received her PhD in Mechanical Engineering (Manufacturing) from Loughborough University, UK, in 2016. Her research primarily involves developing manufacturing processes and technologies to improve efficiency and material properties in industrial applications. She is committed to advancing engineering education and research.
Cucuk Nur Rosyidi Cucuk Nur Rosyidi is a Professor in the Department of Industrial Engineering at the Faculty of Engineering, Universitas Sebelas Maret (UNS), Surakarta, Indonesia. He obtained his PhD in Industrial Engineering and Management from the Institut Teknologi Bandung (ITB), Bandung, Indonesia, in 2010. Professor Cucuk is actively involved in teaching within the Industrial Engineering Program. His research interests lie in production planning and control, industrial optimization, and sustainable manufacturing. He is dedicated to improving industrial processes through innovative engineering solutions.
Mohammad Osman Tokhi Mohammad Osman Tokhi is a Professor at the School of Engineering, London South Bank University (UK). He received his B.Sc. degree in Electrical Engineering from Kabul University, Afghanistan, in 1978, and his Ph.D. from Heriot-Watt University, UK, in 1988. His research interests include active noise and vibration control, adaptive/intelligent control, assistive robotics, and bio/nature-inspired computational intelligence. He has published over 700 papers in these areas and has led numerous successful research projects. Professor Tokhi is a founding member and current chair of the Climbing and Walking Robots (CLAWAR) Association. Additionally, he has been active in advancing international robot standardization within ISO and IEC committees, contributing to the development of new standards for robotics applications in industry.
