Meeting Due Dates by Reserving Partial Capacity in MTO Firms

Noh, Seung J.; Rim, Suk-Chul; Lee, Heesang

doi:10.1007/978-3-540-30585-9_64

Cited by 2 publications

(3 citation statements)

References 11 publications

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“…However, they do not provide rigorous details of how many "emergency slots" and where to place them in the sequence. Noh et al [23] present an approach for reserving capacity for urgent orders in a MTO system and through a simulation study show the benefits of capacity reservation on system profits. However, they also do not investigate how to determine the optimal capacity reservation quantity.…”

Section: Due-date Quoting and Order Allocation Modelsmentioning

confidence: 99%

Dynamic capacity reservation and due date quoting in a make‐to‐order system

Pibernik

Yadav

2008

Naval Research Logistics

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Abstract:We consider a make-to-order manufacturer facing random demand from two classes of customers. We develop an integrated model for reserving capacity in anticipation of future order arrivals from high priority customers and setting due dates for incoming orders. Our research exhibits two distinct features: (1) we explicitly model the manufacturer's uncertainty about the customers' due date preferences for future orders; and (2) we utilize a service level measure for reserving capacity rather than estimating short and long term implications of due date quoting with a penalty cost function.We identify an interesting effect ("t-pooling") that arises when the (partial) knowledge of customer due date preferences is utilized in making capacity reservation and order allocation decisions. We characterize the relationship between the customer due date preferences and the required reservation quantities and show that not considering the t-pooling effect (as done in traditional capacity and inventory rationing literature) leads to excessive capacity reservations. Numerical analyses are conducted to investigate the behavior and performance of our capacity reservation and due date quoting approach in a dynamic setting with multiple planning horizons and roll-overs. One interesting and seemingly counterintuitive finding of our analyses is that under certain conditions reserving capacity for high priority customers not only improves high priority fulfillment, but also increases the overall system fill rate.

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Section: Due-date Quoting and Order Allocation Modelsmentioning

confidence: 99%

Dynamic capacity reservation and due date quoting in a make‐to‐order system

Pibernik

Yadav

2008

Naval Research Logistics

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“…Kilger and Schneeweiss [2] classified order fulfillment situations and presented the simple rules that can be applied in both the allocation planning and ATP capacity consumption. Noh et al [16] presented an approach for reserving capacity for urgent orders in a MTO system and showed its impact on system profit through a simulation experiment; Pibernik and Yadav [17] developed a service-level based MTO system to determine capacity reservation that could meet the due date requirement of important customers; Ponsignon and Mönch [18] proposed heuristic approaches for solving master planning problems in semiconductor manufacturing; Tsai and Wang [19] developed a multi-site three-stage ATP model with different cost structure that is appropriate for MTO manufacturing. Also, Meyr [20] proposed a deterministic linear programming model for ATP allocation and consumption in the lighting industry and showed that customer segmentation can indeed improve profits substantially.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The objective function (15) maximizes the total profit which equals the profit obtained from the consumed committed ATP capacity deducted by the cost attributed from earliness, which is computed by multiplying ATPC cfgti by its associated HC f i and elapsed time between the order item completion date t and due date t d (i). In constraint (16), QTY cfgti represents the remaining, if any, unsatisfied order item quantity updated from constraint (11), and we use the set I u cfgt to denote the collection of such order items from customer c with predefined technology code g at factory f in required time period t. Thus, constraint (16) means that the total ATPC cfgti quantity before the due date of an order item should be less than or equal to the order item quantity QTY cfgti , and C fgt in (17)is to be calculated in expression (22) below at stage C. Table III describes the differences between stages B-1 and B-2 in more detail.…”

Section: ) Stage Amentioning

confidence: 99%

An Order Fulfillment Model With Periodic Review Mechanism in Semiconductor Foundry Plants

Chiang¹,

Hsu

2014

IEEE Trans. Semicond. Manufact.

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In today's globalization competition, manufacturing firms are using an order fulfillment system to give available-topromise (ATP) capacity efficiently. An ordinary order fulfillment system will plan capacity based on forecasts and assign ATP quotas to incoming orders. Its basic idea is to enhance capacity utilization and avoid poor customer service. However, in the semiconductor industry, demand is highly volatile, and a maketo-order (MTO) manufacturer often runs the risk of cancelled committed demands. In this research, we propose an integrated order fulfillment model for a MTO semiconductor foundry fab to maximize corporate profit. Specifically, we suggest a periodic allocation review mechanism to reallocate unused ATP quotas. We examine the model performance based on different data sets. Results showed that capacity utilization and profitability are improved substantially with the periodic review mechanism, especially when demand forecast is not reliable.Index Terms-Available-to-promise, linear programming, management information systems, order fulfillment, production management.

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Meeting Due Dates by Reserving Partial Capacity in MTO Firms

Cited by 2 publications

References 11 publications

Dynamic capacity reservation and due date quoting in a make‐to‐order system

Dynamic capacity reservation and due date quoting in a make‐to‐order system

An Order Fulfillment Model With Periodic Review Mechanism in Semiconductor Foundry Plants

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