Inventory allocation and cycle time estimation in manufacturing and supply systems

Manufacturing and supply systems (MSS) in many industries, such as home electronic products, personal computers and automobiles, usually take the form of networks of suppliers, fabrication/assembly locations, distribution centres and customer locations, through which materials, components, products and information flow (Ettl et al. 2000, Liu et al. 2004). Throughout such a network, there are different sources of uncertainties associated with supplies (availability, quality and delivery times), processes (transportation times, machine breakdown and human performance) and demands (arrival times, batch sizes and types). These uncertainties and other factors affect the performance of an MSS, including its service level in terms of fill rate or delivery lead time, which in turn affects the bottom line of an enterprise in today’s competitive environment. Among other things, inventories can be used to hedge uncertainties and achieve a target service level. Because inventories placed at different locations usually incur different costs and have different effects on the service level for end 504customers, efficient allocation and control of inventory assets present enormous opportunities and, at the same time, pose a great challenge to many companies. To cope with this challenge, formal methods are needed to help understand system dynamics and various trade-offs and to provide decision-making guidelines.