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Semiconductor supply planning by considering transit options to take advantage of pre-productions and order cancellations
Affiliation:1. Department of Information and Communication Sciences, Sophia University, 7-1 Kioi-Cho, Chiyoda-Ku, Tokyo, Japan;2. Infineon Technologies AG, Am Campeon 1-12, 85579 Neubiberg, Germany;1. School of Nuclear Science and Technology, Xi’an Jiao Tong University, 28 Xianning West Road, Xi’an 710049, China;2. State Nuclear Power Technology R&D Center, Beijing 100190, China;1. Department of Industrial Management, National Taiwan University of Science & Technology, Taipei 106, Taiwan;2. Department of Information Management, Central Police University, Taoyuan 33304, Taiwan;1. Hospital Universitario de Gran Canaria Dr Negrín, Las Palmas de Gran Canaria, España;2. Hospital Universitario Severo Ochoa, Leganés, Madrid, España;3. Comité Científico, Comisión de Proteínas, Sociedad Española de Bioquímica Clínica y Patología Molecular;1. Institute of Environmental and Animal Hygiene, University of Hohenheim, Garbenstr. 30, D-70599 Stuttgart, Germany;2. Cardiff School of Pharmacy and Pharmaceutical Science, Cardiff University, King Edward VII Avenue, Cardiff CF10 3NB, UK
Abstract:One of the objectives of supply planning is to find when and how many productions have to be started to minimize total cost. We aim to find the optimum. Base data like the length of transit time are important parameters to plan for the optimum start of production. In this research, we considered two kinds of transit options: normal transit and emergency transit, and we distinguished between planned and executed transit. The decision regarding which transit option to choose for the execution is trivial because emergency is only used when it is needed since normal transit is more cost efficient. However, for planning purpose, it is more difficult to decide which transit option should be used since the uncertainty in demand and supply between plan and execution can allow to plan an emergency transit but to execute the delivery with normal transit, which is a huge benefit in the competitive capital intensive semiconductor industry. If we planned an emergency, we can save inventory and production cost as we can delay the start of production. In contrast, we need pay additional transit cost in case that emergency transit is actually executed. Many characteristics of the semiconductor industry, which might be the front runner for many other industries, are considered in this model such as demand uncertainty, supply uncertainty and economic volatility. In our numerical experiments, we could gain the optimum, depending on each economic situation. Furthermore, we conducted sensitivity analysis of the effect of demand and supply uncertainties on total cost.
Keywords:Semiconductor  Supply planning  Simulation  Supply chain management
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