This book 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.

Presents selected papers from the iMEC-APCOMS 2024 in manufacturing engineering and other related topics Includes papers written by leading experts covering advances in global manufacturing systems and technology Provides an overview of sustainable development goals through innovative manufacturing engineering

Autorentext

Mohamad Rusydi Mohamad Yasin is a senior lecturer at the Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA), specializing in manufacturing and materials engineering. He earned his Bachelor's and Master's degrees from the University of Auckland NZ and a PhD from Purdue University USA. His research focuses on alloy development, material processing techniques, die casting, and metallurgy, with contributions to microstructural evolution and fatigue strength studies of aluminum-silicon alloys. Beyond teaching and research, he is actively involved in academic publishing and advanced materials innovation.

Zulhelmi Ismail is a senior lecturer at the Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA). He earned his Bachelor's degree in Mechanical Engineering from Fachhochschule Gummersbach (Cologne University of Applied Sciences) in Germany in 2011. He then completed his Master's and Ph.D. in Mechanical Engineering (Manufacturing) at Universiti Malaysia Pahang (UMP) in 2013 and 2018, respectively. His research interests include structural materials and degradation, advanced manufacturing processes, and innovative materials. Dr. Zulhelmi has published and is actively engaged in advancing the field of manufacturing and materials engineering.

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 Ph.D. 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 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.

Inhalt
Air Quality Prediction Using Deep Learning Approaches.- Utilizing Accelerometer Data and LSTM Model for Road Surface Detection.- Air Passenger Forecasting: Leveraging the Power of Autoregressive Models.- Performance Of Machine Learning For Predicting Load-Carrying Capacity Of Nonlinear Steel Trusses.- Evaluating Regression And Classification Surrogate Models For Sizing Optimization Of Nonlinear Steel Trusses.- Fuzzy Structural Analysis using Rao-kNNC-based Approach.- Multi-objective optimization of I-shaped steel plate girders using NSGA-II.- Using Classification and ANN Model to Predict Slump and Compressive Strength of Normal and High-Early Strength Concrete: A Study at a Concrete Batching Plant in Binh Thuan, Vietnam.- Etc....