Optimization of semi-automated assembly line operations for enhanced operational efficiency and environmental sustainability
Xin Yuan Lee, Joshua Prakash, Mosè Gallo, Chew Keat CheahPurpose
This study proposes an optimization framework aimed at enhancing both operational and environmental performance in semi-automated manufacturing processes, addressing a critical gap in existing research.
Design/methodology/approach
The framework comprises five stages: Identify, Data Collection, Investigate, Optimization and Monitor. It integrates insights from the literature and applies these to a case study in a semi-automated semiconductor plant. Key tools include a Smart Andon Dashboard and a Manufacturing Execution System, as well as the Analytic Hierarchy Process (AHP) for improvement selection.
Findings
The implementation of the framework resulted in a 32% improvement in operational efficiency and a 70% reduction in machine idle time. These changes significantly reduced energy consumption and improved the plant's carbon footprint. Notably, the study highlights the long-term benefits of optimizing non-bottleneck processes for resource conservation and CO2 emission reduction.
Practical implications
This research provides a practical methodology for manufacturers to achieve dual objectives of operational efficiency and sustainability. The use of AHP enhances decision-making in the improvement selection process, making it adaptable to various manufacturing environments.
Originality/value
This study bridges the gap between operational and environmental performance improvements in semi-automated manufacturing. It demonstrates the potential of targeted optimizations to yield substantial benefits for both efficiency and sustainability.