• Management Science and Financial Engineering
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• v.3 no.1
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• pp.57-74
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• 1997

An EOQ-like inventory model for a manufacturing process is studied. The system is assumed to deteriorate during the production process. The results are either the production of a number of defective items, or the breakdown of the production machine. The optimal production lot size is derived. The model is extended to the case in which the probabilities of making defective items and machine breakdowns are a function of both the quantity (amount) and quality (performance) of the consumed setup cost (including the preventive maintenance cost). We further assume that the setup performance can be improved by investing in the performance improvement program. Hence, the same or a better setup outcome can be achieved with a lower setup cost. We then investigate the optimal setup cost and investment policy simultaneously, thereby achieving a better process quality and setup cost reduction concurrently.

• IE interfaces
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• v.13 no.2
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• pp.217-224
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• 2000

This paper analyzes the effects of setup cost reduction in a dynamic lot-sizing model for a single-facility multi-product problem. In the model, demands for each product are known, no backlogging is allowed, and a single resource is employed. Also, setup cost is defined as a function of capital expenditure to invest in setup cost reduction. Furthermore, in each production period the facility (or plant) produces many products, each representing a fixed part of the involved production activity (or input resource quantity). In this paper, the structure of the optimal solution is characterized and an efficient algorithm is proposed for simultaneously determining the optimal lot size with reduced setup cost and the optimal investment in setup cost reduction. Also, the proposed algorithm is illustrated by a numerical example with a linear and an exponential setup reduction functions.

• Management Science and Financial Engineering
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• v.13 no.2
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• pp.117-139
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• 2007

This paper contributes by incorporating works addressing supply chain coordination and investing in setup reduction program. Consider a two-echelon, EOQ-like inventory system consisting of a supplier and a buyer. We assume that both the supplier and the buyer can invest in setup cost reduction programs in order to benefit from small order sizes. However, the costs of investing in setup cost reduction programs are different for the two parties, leading to mismatches in individually optimal setup costs and order cycle times. We propose a supply chain coordination contract that makes use of quantity discount as an incentive transfer scheme for supply chain coordination.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.3
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• pp.49-64
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• 2000

A vendor supplies a product to a sole/major buyer on a lot-for-lot basis under deterministic inventory control conditions. The basic premise is that the setup cost reduction technologies are available to both the buyer and the vendor, and that the vendor's inventory and setup reduction investment costs differ from the buyer's. Therefore, an individually designed ordering and setup cost reduction policy will likely cause mismatches between the vendor's and the buyer's optimal cycle times. For this situation, we show that a joint optimal setup cost reduction and ordering policy, together with an appropriate side payment(quantity discount or premium price) schedule, can be designed in a spirit in a spirit of coordination to eliminate mismatches in individual optimal cycle times.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.74-83
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• 2011

In this paper, we consider a new lot-sizing and scheduling problem (LSSP) that minimizes the sum of production cost, setup cost and inventory cost. Setup carry-over, setup overlapping, state dependent setup time as well as demand splitting are considered. For this LSSP, we develop a mixed integer programming (MIP) model, of which the size does not increase even if we divide a time period into a number of micro time periods. Also, we develop an efficient heuristic algorithm by combining a decomposition scheme with a local search procedure. Test results show that the developed heuristic algorithm finds a good quality (in practice, even better) feasible solution using far less computation time compared with the CPLEX, a competitive MIP solver.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.3
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• pp.95-108
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• 2013

The problem of constrained sequencing of a set of jobs on a conveyor system with the objective of minimizing setup cost is investigated in this paper. A setup cost is associated with extra material, labor, or energy required due to the change of attributes in consecutive jobs at processing stations. A finite set of attributes is considered in this research. Sequencing is constrained by the availability of conveyor junctions. The problem is motivated by the paint purge reduction problem at a major U.S. automotive manufacturer. We first model a diverging junction with a sequence-independent setup cost and predefined attributes as an assignment problem and this model is then extended for a more general situation by relaxing the initial assumptions in various ways.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.171-176
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• 2021

This paper deals with bid evaluation problem that chooses the vendors and quantity with minimum purchasing cost for bid information of setup cost and unit price. For this problem, the branch-and-bound(BB) and branch-and-cut(BC) methods are well-known. But these methods can be fail to obtain the optimal solution. This paper gets the initial feasible solution with procuring quantity assignment principle in accordance with the unit price or setup cost rank-first. Then procuring quantity moving optimization(vendor change) is execute take account of unit price or setup cost rank. As a result of experimentation, the propose algorithm is significantly lower compared to BB and BC.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.11-28
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• 2009

Intelligent investment in setup cost reduction and process reliability improvement is crucial to an emerging integrated lean six sigma practice today. This study examines a cost-minimizing problem of jointly determining production lot size, setup cost reduction, and process reliability improvement decisions for a manufacturer with an imperfect production process. We develop models for previously untapped discrete shipping in a supply chain context as well as continuous shipping and solve them optimally using differential calculus and nonlinear programming. We also conduct analytic and numerical sensitivity analyses to provide various important managerial insights into practices.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.06a
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• pp.129-134
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• 2003

In this paper, we determine optimal reduction in the lead time and setup cost for some stochastic inventory models. And we propose more general model that allow the backorder rate as a control variable. We first assume that the lead time demand follows a normal distribution. And we assume that the backorder rate is dependent on the length of lead time through the amount of shortages. The stochastic models analyzed in this paper are the classical continuous and periodic review policy models with a mixture of backorders and lost sales. For each of these models, we provide a sufficient conditions for the uniqueness of the optimal operating policy. We also develop algorithms for solving these models and provide illustrative numerical examples.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.3
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• pp.93-104
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• 1994

One of the typical assumptions of the studies to determine economic production quantity is that yield rate of a given manufacturing process is 100% or constant after setup. However, in the real world, there are many manufacturing processes of which yield rates are quite low just after setup and then increasing with time until they reach the target rates which are set strategically. This period is usually called "stabilization period". During the stabilization period, defectives are produced, which incur cost (defective cost). In this study, an optimal production quantity for this situation is presented. Also, it is shown that defective cost acts like setup cost and therefore, increases the economic production quantity.