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Currently, the intensity of enterprise competition has increased as a result of a greater diversity of customer needs as well as the persistence of a long-term recession. The results of competition are becoming severe enough to determine the survival of company. To survive global competition, each firm must focus on achieving innovation excellence and operational excellence as core competency for sustainable competitive advantage. Supply chain management is now regarded as one of the most effective innovation initiatives to achieve operational excellence, and its importance has become ever more apparent. However, few companies effectively manage their supply chains, and the greatest difficulty is in achieving supply chain visibility. Many companies still suffer from a lack of visibility, and in spite of extensive research and the availability of modern technologies, the concepts and quantification methods to increase supply chain visibility are still ambiguous. Based on the extant researches in supply chain visibility, this study proposes an extended visibility concept focusing on a process capability perspective and suggests a more quantitative model usingZscore in Six Sigma methodology to evaluate and improve the level of supply chain visibility.

In most Make-To-Order manufacturing, work-in-process (WIP) inventory is usually piled up at almost every station in the factory in order to quickly meet the urgent request from the immediate downstream station. Depending on the station network configuration and lead time at each station, some of the WIP inventories do not contribute to reducing the manufacturing lead time of the final product at all. Therefore, it is important to identify the minimum set of stations to hold WIP inventory such that the total inventory holding cost is minimized, while the required due date for the final product is met. In this study, we present a model to determine the optimal position and quantity of WIP inventory for a given bill of material using the actively synchronized replenishment (ASR) lead time; and present a solution procedure using genetic algorithm.

In order to meet the lead time that the customers require, work-in-process inventory (WIPI) is necessary at almost every station in most make-to-order manufacturing. Depending on the station network configuration and lead time at each station, some of the WIPI do not contribute to reducing the manufacturing lead time of the final product at all. Therefore, it is important to identify the optimal set of stations to hold WIPI such that the total inventory holding cost is minimized, while the required due date for the final product is met. The authors have presented a model to determine the optimal position and quantity of WIPI for a given simple bill of material (S-BOM), in which any part in the BOM has only one immediate parent node. In this paper, we extend the previous study to the general BOM (G-BOM) in which parts in the BOM can have more than one immediate parent and present a new solution procedure using genetic algorithm.

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