A wafer design problem in semiconductor manufacturing for reliable customer service

Singh, Maneesh Kumar; Abraham, C. T.; Akella, Ram

doi:10.1109/33.52855

Cited by 28 publications

(7 citation statements)

References 2 publications

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“…For the former, see Harrison and Van Mieghem (1999), Van Mieghem (1998), Rudi and Zheng (1997), and Van Mieghem and Rudi (2002). The latter stream of papers was initiated by Yao (1988) and includes Singh et al (1990), Gerchak et al (1994), Lee (1996), and Gurnani et al (1996Gurnani et al ( , 2000 as important contributions. Yao (1988), for example, considered the problem of minimizing the cost of procuring the components subject to a service-level constraint, i.e., subject to achieving a fixed target quantity from the assembly stage with a minimum probability.…”

Section: Literature Reviewmentioning

confidence: 99%

Selecting a Portfolio of Suppliers Under Demand and Supply Risks

Federgruen

Yang

2008

Operations Research

189

102

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We analyze a planning model for a firm or public organization that needs to cover uncertain demand for a given item by procuring supplies from multiple sources. Each source faces a random yield factor with a general probability distribution. The model considers a single demand season. All supplies need to be ordered before the start of the season. The planning problem amounts to selecting which of the given set of suppliers to retain, and how much to order from each, so as to minimize total procurement costs while ensuring that the uncertain demand is met with a given probability. The total procurement costs consist of variable costs that are proportional to the total quantity delivered by the suppliers, and a fixed cost for each participating supplier, incurred irrespective of his supply level. Each potential supplier is characterized by a given fixed cost and a given distribution of his random yield factor. The yield factors at different suppliers are assumed to be independent of the season's demand, which is described by a general probability distribution. Determining the optimal set of suppliers, the aggregate order and its allocation among the suppliers, on the basis of the exact shortfall probability, is prohibitively difficult. We have therefore developed two approximations for the shortfall probability. Although both approximations are shown to be highly accurate, the first, based on a large-deviations technique (LDT), has the advantage of resulting in a rigorous upper bound for the required total order and associated costs. The second approximation is based on a central limit theorem (CLT) and is shown to be asymptotically accurate, whereas the order quantities determined by this method are asymptotically optimal as the number of suppliers grows. Most importantly, this CLT-based approximation permits many important qualitative insights.

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Section: Literature Reviewmentioning

confidence: 99%

Selecting a Portfolio of Suppliers Under Demand and Supply Risks

Federgruen

Yang

2008

Operations Research

189

102

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“…The literature on the supply chain with random yield usually focuses on the centralised system, where a single decision-maker chooses all production quantities and incurs all the costs (Singh, Abraham, and Akella 1990;Gerchak, Wang, and Yano 1994;Lehoczky 1996, 2000). However, each player in the supply chain is primarily concerned with optimising his own objective, which decreases entire supply chain profit due to the double marginalisation.…”

Section: Literature Reviewmentioning

confidence: 99%

Random yield and coordination mechanisms of a supply chain with emergency backup sourcing

Chen

Yang

2014

International Journal of Production Research

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This paper considers a supply chain in which a buyer purchases finished items from a contracting supplier to satisfy a stochastic market demand, where the supplier's production is subject to random yield. We assume that the buyer can make up the shortage by sourcing from an emergency backup supplier. We develop two Stackelberg game models, i.e. buyer-Stackelberg (BS) model and supplier-Stackelberg (SS) model, and find that the decentralised BS model results in a higher stocking factor of supplier's input than the decentralised SS model. Compared with BS model, the buyer in SS model performs more explicit order plan, and we find that only when the actual yield of the supplier is insufficient, the buyer would use emergency backup sourcing to make up the shortage. When the manufacturing operation of the supplier is in the good state, the buyer only orders a certain amount and has some leftover. When the actual yield of the supplier is moderate, the buyer uses up every item produced from the supplier regardless of the yield rate. Comparing both channel structures, SS operation is a more effective way of controlling both inventory cost and backup sourcing cost, and it can be beneficial for each player as well as for the whole channel. Finally, we develop the coordination mechanism for each channel to investigate the issues of risk handling and risk sharing for uncertain demand and uncertain yield.

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“…To the best of our knowledge, most literature under random component yield has focused on centralized system where the price is ex-ante selected [33][34][35][36][37]. Some have studied establishing properties of the profit function of the chain and found the optimal order quantity but without pricing control [38].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Pricing and Supply Coordination with Reimbursement Contract under Random Yield and Demand

Ran

Yue

et al. 2013

Discrete Dynamics in Nature and Society

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This paper investigates the dynamic pricing and supply chain coordination in a decentralized system that consists of one supplier and one manufacturer, in which both the market demand and production yield are stochastic. We show that the centralized expected profit is jointly concave in the production quantity and order quantity when the price is ex-ante selected. We also derive the equilibrium strategies in the decentralized system and prove that the entire profit of supply chain is inevitably lower than that under centralized system. Based on this, we propose a reimbursement contract to coordinate the decentralized supply chain so as to achieve the maximized profit. It is worth mentioning that, under reimbursement contract, the equilibrium production and order quantities are irrelevant to the manufacturer's risk sharing coefficient but are only determined by the supplier’s risk sharing coefficient.

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A wafer design problem in semiconductor manufacturing for reliable customer service

Cited by 28 publications

References 2 publications

Selecting a Portfolio of Suppliers Under Demand and Supply Risks

Selecting a Portfolio of Suppliers Under Demand and Supply Risks

Random yield and coordination mechanisms of a supply chain with emergency backup sourcing

Dynamic Pricing and Supply Coordination with Reimbursement Contract under Random Yield and Demand

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