Assembly Line Balancing under Uncertain Task Time and Demand Volatility

This book provides mathematical models and methods for assembly line balancing with uncertain task times and demand volatility, using stochastic programming. It presents a case study of mask production during the COVID-19 pandemic.

Format: Hardback
Length: 152 pages
Publication date: 11 September 2022
Publisher: Springer Verlag, Singapore

This comprehensive book delves into the realm of assembly line balancing, employing mathematical models rooted in stochastic programming. It presents precise and heuristic approaches to tackle these complex problems. An assembly line system is a pivotal manufacturing process where components are sequentially assembled from workstation to workstation, culminating in the final product. In the context of assembly line balancing, tasks from various product models are strategically assigned to workstations based on their processing times and interdependencies. This intricate process incorporates two key features: uncertain task times and demand volatility, which are addressed separately and concurrently within the conventional assembly line balancing model. To demonstrate the practical application of the proposed framework and methodology, a real-life case study related to mask production during the COVID-19 pandemic is presented. This case study showcases the effectiveness of the proposed approach in optimizing assembly line operations under uncertain conditions. The book is specifically designed for advanced graduate students with a keen interest in combinatorial optimizations in manufacturing, particularly in the context of dealing with uncertain input. By exploring these mathematical models and their practical applications, readers gain valuable insights into the optimization of assembly line processes, enhancing efficiency and productivity in the manufacturing industry.

Weight: 418g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811942143
Edition number: 1st ed. 2022