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We study a hybrid push-pull manufacturing system that the IBM Systems Group implemented as a response to a complex configuration environment and increasing pressure for responsive order fulfillment lead times. This is a two-stage (fabrication and fulfillment center) manufacturing process, which builds and stocks tested subassemblies for just-in-tim...
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In many productive processes, two important problems arise in the production planning: the lot-sizing problem and the cutting stock problem. Generally, companies deal with these problems separately but, by considering them in an integrated way, better results can be obtained. In this paper, the integrated lot-sizing and three-dimensional cutting st...
Citations
... Delayed differentiation strategies are typically are employed in two-stage production systems involving a common intermediate product in the first part and a simple localization operation (typically the final assembly) in the second part of the manufacturing process (Cheng et al., 2005). For this reason, a hybrid push-pull production systems is the perfect production environment to couple with postponement (Atan et al., 2016). ...
The present work shows the benefits associated with a postponement strategy and proposes a decision
making framework that aids companies in their choice between Make-To-Stock and Assemble-To-Order at
a location closer to the target market. An accompanying analysis tool is created with the purpose of
ultimately identifying the costs and benefits associated with postponement. The tool applies principles of
the Normative Cost Model proposed by Zinn and Bowersox (1988) and includes a demand forecasting and
inventory replenishment feature.
The model is applied to the supply chain of professional luminaires. The mathematical model employed
within the support tool confirms previous findings related to the cost benefits of component commonality
and validates the hypotheses formulated in regards to the financial benefits associated with postponement.
Based on the results yielded by the model, recommendations for model extensions and further research
are formulated.
... There are many applications of MTO systems with multiple demand classes, differing in lead time requirement and profit margin to the firm. For instance, IBM produces its server computers by using the assemble-to-order (ATO) strategy for corporate customers who may have different fulfilment time requirements and different marginal profit contribution to IBM (Cheng et al. 2005). Gupta and Wang (2007) provide another example in which a firm builds products using MTO strategy for two types of customers with different profit margin and lead time requirement: contractual and transactional customers. ...
This paper examines capacity rationing policies in a make-to-order production system with two demand classes differing in profit margin and lead time sensitivity. Motivated by the complexity of the optimal rationing policy, an easy-to-implement state-independent critical level (SIC) policy is proposed. We also investigate the benefit of capacity rationing and effectiveness of the SIC policy. Results show that the complicated optimal policy can significantly increase profit in many cases when compared with the policy without capacity rationing, and the easy-to-implement SIC policy performs quite well, compared with the optimal policies. Important managerial insights including the effect of maximal acceptable lead times on the profit are also obtained.
... The dataset resembles a typical real-world problem compiled from actual IBM server data (Cheng et al., 2005). It consists of 12 machine types (product), i.e., Model 1... Model 12. ...
... Also, product demands are heavily skewed towards the later periods. As mentioned by Cheng et al. (2005), in practice, they observed that often up to 60% of customer orders are shipped in the last three weeks of a quarter. Because of limited production capacity, components are produced ahead of time during early periods. ...
... For cost and demand data, please refer to Cheng et al. (2005). We assume the following: h it = 0.2 c it , w it = 0.15 c it , b it = 0.6 c it , p it = 0.45 c it . ...
Assemble-to-order (ATO) systems enable manufacturing firms to be cost-effective and at the same time responsive to changing customer orders. In this paper, we study an assemble-to-order (ATO) system, where raw materials are released into a capacitated production stage. Inventory of produced components is kept in stock ready for final assembly once specific orders for products are received. An important planning issue is to find an optimal trade-off between capacity utilisation and components inventory holding cost with the aim to meet uncertain demand of end products. In this paper, we formulate two integrated production/inventory planning models using clearing functions while considering demand uncertainty. In the first model, we assume that demand is normally distributed and propose a chance constrained formulation. In the second model, we consider the case of unknown demand distributions and use a robust optimisation approach. The proposed models are linear programmes that provide safe production plans. We illustrate the proposed models using a real case study from the literature and analyse the effect of congestion and demand uncertainty.
... ATO systems with multiple customer classes are increasingly common in industry. For example, IBM has recently restructured the manufacturing of its server computers into two stages (Cheng et al., 2005). ...
We consider the optimal production and inventory control of an assemble-to-order system with m components, one end-product, and n customer classes. A control policy specifies when to produce each component and, whenever an order is placed, whether or not to satisfy it from on-hand inventory. We formulate the problem as a Markov decision process and characterize the structure of an optimal policy. We show that a base-stock production policy is optimal, but the base-stock level for each component is dynamic and depends on the inventory level of all other components (more specifically, it is nondecreasing). We show that the optimal inventory allocation for each component is a rationing policy with different rationing levels for different demand classes. The rationing levels for each component are dynamic and also nondecreasing in the inventory level of all other components. We compare the performance of the optimal policy to heuristic policies, including the commonly used base-stock policy with fixed base-stock levels, and find them to perform surprisingly well, especially for systems with lost sales.
This research presents an integrated simulation modeling-design for six sigma (DFSS) framework to study the design and process issues in a server manufacturing environment. The server assembly process is characterized by long cycle times, high fall-out rates and extremely complex assembly operations. To ensure on-time customer delivery, these enterprises adopt a make-to-plan and build-to-order philosophy. However, this model is extremely complex, resulting in wastes and inefficiencies in the associated processes. Lean and six sigma approaches have been successful in improving performance by eliminating waste in the design and operational processes. In this study, an integrated simulation modeling - DFSS framework is proposed to (i) address effects of variation, (ii) assess interactions effects between various sub-systems, and (iii) study proposed process (or design) changes, while performing ¿what-if¿ analysis. This framework was then used to identify opportunities for improving the operational and design issues in a server manufacturing environment.
In this paper, we study a decentralized assembly system consisting of a single assembler who buys complementary components from independent suppliers under two contracting schemes: push and pull. In both schemes, the component suppliers are allowed to freely form coalitions (or alliances) among themselves to better coordinate their pricing or production decisions. We show that the sole driver of the inefficiency in a push system, which is due to horizontal decentralization of suppliers, is the number of alliances that were formed. Specifically, it is shown that in a push system, the assembler's profit, the total profit of all suppliers and the consumers' surplus are all decreasing in the number of coalitions, and are thus maximized when the grand coalition is formed. We further carry out a stability analysis of coalition structures to verify to what extent suppliers can reduce or eliminate the inefficiency due to their decentralization by forming alliances. We show that in a push system with more than two suppliers and a power demand distribution, myopic suppliers would act independently, resulting with a least efficient channel, which makes all channel members, as well as the end consumers, worse off. On the other hand, we prove that farsighted suppliers would form the grand coalition and thus be able to completely eliminate the inefficiency stemming from their decentralization. Finally, it is shown that, in contrast to a push system, in a pull system the suppliers can easily coordinate their production quantities to eliminate the inefficiency due to their decentralization.
