Many of companies have made significant improvements for globalization and competitive business environment The supply chain management has received many attentions in the area of that business environment. The purpose of this study is to generate realistic production and distribution planning in the supply chain network. The planning model determines the best schedule using operation sequences and routing to deliver. To solve the problem a hybrid approach involving a genetic algorithm (GA) and computer simulation is proposed. This proposed approach is for: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, and (3) minimizing the completion time for each order. This study developed mathematical model for production, distribution, production-distribution and proposed GA-Simulation solution procedure. The results of computational experiments for a simple example of the supply chain network are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production and distribution planning in the manufacturing supply chain network. The proposed approach can be used to generate realistic production and distribution planning considering stochastic natures in the actual supply chain and support decision making for companies.

Up to date cosmetic OEM/ODM (original equipment manufacturing/original development manufacturing) industry receives attention as a future growth engine due to steady growth. However, because of limited research and development capability, many companies have employed commercial management platforms specialized for large-sized companies; thus, overall system effectiveness and efficiency is low. Especially, MRP (material requirement planning) system introduced originally in 1970s is employed to calculate the requirement of the parts. However, dynamic nature of production lead time usually results in incorrect requirements. In addition, its algorithm does not consider the capability of the production resources. Also, because the commercial MRP system calculates all subcomponent for fixed period, the more goods have subcomponent, the slower calculation is. Therefore, conventional MRP system cannot respond complicated situation in time. In this study, we will suggest a new method that can respond to complicated situations resulting from short lead time and urgent production order in Korean cosmetic market. In particular, a distributed MRP system is proposed, that consists of multi-functional and operational modules, based on the characteristic of the BOM (bill of material). The distributed MRP system divides components (i.e. products and parts) into several fields and decrease the problem size; thus, we can respond to dynamically changed data any time. Through this solution, we can order components quickly, adjust schedules and planned quantity, and manage stocks reasonably. In addition, a prototype of the distributed MRP system is presented in this paper, in which ERP (enterprise resource planning) sever data is associated with an excel spreadsheet via MSsql. System user interface is implemented by a VBA (visual basic for applications) tool. According to a case study, response rate for delivery and planning achievement rate were enhanced about 20%, and inventory turnover was also decreased. Consequently, the proposed system improves overall profit.

The diesel engine generate many pollutants such as PM(Particulate matter) and NOx(Nitrogen oxide). So the SCR(Selective catalytic reduction) must be required to meet the emission standard. The SCR catalyst market is growing rapidly, and the automobile markets using alternative energy sources are growing rapidly. This study deals with optimization of the calcination process the manufacturing process of SCR catalyst to be competitive. The calcination process is a bottleneck and it is required to optimize productivity and accept to be safety, But we cannot trade off anything in terms of safety. We applied DOE(Design of experiments) among many research methods performed in various fields. In order to achieve quality and productivity optimization. The dependent variables in the DOE were selected as NO Conversion(%). The independent variables were selected as the calcination temperature, soaking time and fan speed RPM. the CCD(Central composite designs) constructs response surface using the data onto experience and finds optimum levels within the fitted response surfaces. Our tests are our stability guarantee and efficient together with operation.

The manufacturing companies under Make-To-Order (MTO) production environment face highly variable requirements of the customers. It makes them difficult to establish preemptive production strategy through inventory management and demand forecasting. Therefore, the ability to establish an optimal production schedule that incorporates the various requirements of the customers is emphasized as the key success factor. In this study, we suggest a process of designing the simulation model for establishing production schedule and apply this model to the case of a flat glass processing company. The flat glass manufacturing industry is under MTO production environment. Academic research of flat glass industry is focused on minimizing the waste in the cutting process. In addition, in the practical view, the flat glass manufacturing companies tend to establish the production schedule based on the intuition of production manager and it results in failure of meeting the due date. Based on these findings, the case study aims to present the process of drawing up a production schedule through simulation modeling. The actual data of Korean flat glass processing company were used to make a monthly production schedule. To do this, five scenarios based on dispatching rules are considered and each scenario is evaluated by three key performance indicators for delivery compliance. We used B2MML (Business To Manufacturing Markup Language) schema for integrating manufacturing systems and simulations are carried out by using SIMIO simulation software. The results provide the basis for determining a suitable production schedule from the production manager's perspective.

This study deals with optimization of the calcination process the manufacturing process of SCR catalyst to be competitive. The calcination process is a bottleneck and it is required to optimize productivity and quality. We applied DOE(Design of experiments) among many research methods performed in various fields. In order to achieve quality and productivity optimization. The dependent variables in the DOE were selected as NO Conversion (%). The independent variables were selected as the calcination temperature, soaking time and fan speed RPM. The CCD(Central composite designs) constructs response surface using the data onto experience and finds optimum levels within the fitted response surfaces.

We consider a wafer lot transfer/release planning problem from semiconductor wafer fabrication facilities to probing facilities with the objective of minimizing the deviation of workload and total tardiness of customers’ orders. Due to the complexity of the considered problem, we propose a two-level hierarchical production planning method for the lot transfer problem between two parallel facilities to obtain an executable production plan and schedule. In the higher level, the solution for the reduced mathematical model with Lagrangian relaxation method can be regarded as a coarse good lot transfer/release plan with daily time bucket, and discrete-event simulation is performed to obtain detailed lot processing schedules at the machines with a priority- rule-based scheduling method and the lot transfer/release plan is evaluated in the lower level. To evaluate the performance of the suggested planning method, we provide computational tests on the problems obtained from a set of real data and additional test scenarios in which the several levels of variations are added in the customers’ demands. Results of computational tests showed that the proposed lot transfer/planning architecture generates executable plans within acceptable computational time in the real factories and the total tardiness of orders can be reduced more effectively by using more sophisticated lot transfer methods, such as considering the due date and ready times of lots associated the same order with the mathematical formulation. The proposed method may be implemented for the problem of job assignment in back-end process such as the assignment of chips to be tested from assembly facilities to final test facilities. Also, the proposed method can be improved by considering the sequence dependent setup in the probing facilities.

Because land based aquaculture is restricted by high investment per rearing volume and control cost, good management planning is important in Land-based aquaculture system case. In this paper master production planning was made to decide the number of rearing, production schedule and efficient allocation of water resources considering biological and economic condition. The purpose of this article is to build the mathematical decision making model that finds the value of decision variable to maximize profit under the constraints. Stocking and harvesting decisions that are made by master production planning are affected by the price system, feed cost, labour cost, power cost and investment cost. To solve the proposed mathematical model, heuristic search algorithm is proposed. The model Input variables are (1) the fish price (2) the fish growth rate (3) critical standing corp (4) labour cost (5) power cost (6) feed coefficient (7) fixed cost. The model outputs are (1) number of rearing fish (2) sales price (3) efficient allocation of water pool.

This paper deals with the production plan for the foaming process, the core part of the refrigerator manufacturing process. In accordance with this change, the refrigerator manufacturing process has also been converted into the mixed-model production system and it is necessary to optimize the production release pattern for the foaming process. The pattern optimization is to create a mixed-model combination which can minimize the number of setup operations and maintain mixed-model production. The existing method is a simple heuristic that depends on the demand priority. Its disadvantages are low mixed-model configuration rate and high setup frequency. Therefore, demand partitioning occurs frequently. In this study, we introduce the tolerance concept and propose a new pattern optimization algorithm based the large neighborhood search (LNS). The proposed algorithm was applied to a refrigerator plant and it was found that mixed-model configuration rate can be improved without demand partitioning.

This paper considers a scheduling problem in a two-machine flowshop with outsourcing strategy incorporated. The jobs can be either processed in the first machine or outsourced to outside subcontractors. This paper wants to determine which jobs to be processed in-house and which jobs to be outsourced. If any job is decided to be outsourced, then an additional outsourcing cost is charged The objective of this paper is to minimize the sum of scheduling cost and outsourcing cost under a budget constraint. At first this paper characterizes some solution properties, and then it derives solution procedure including DP (Dynamic Programming) and B&B (Branch-and-Bound) algorithms and a greedy-type heuristic. Finally the performance of the algorithms are evaluated with some numerical tests.

In this paper, we deal with a single machine scheduling problems integrating with step deterioration effect and a rate-modifying activity (RMA). The scheduling problem assumes that the machine may have a single RMA and each job has the processing time of a job with deterioration is a step function of the gap between recent RMA and starting time of the job and a deteriorating date that is individual to all jobs. Based on the two scheduling phenomena, we simultaneously determine the schedule of step deteriorating jobs and the position of the RMA to minimize the makespan. To solve the problem, we propose a hybrid typed genetic algorithm compared with conventional GAs.

Supply Chain Management(SCM) is getting important, because size of the company is getting bigger and the kinds of product are various. In the case of manufacturing corporation, for the optimization of SCM, we have to make production and distribution plan by considering the various fluctuation in the aspect of integration. In this paper, first, It proposed the reasonable operational way of the SCM about when the customer’s demanding is various and demanding expectation fluctuates in capacity standardization of producer stage. Second, the paper proposed the management way for demanding by considering confirmed demanding information, related inventory expense and demanding shortage expense when we make production and distribution plan. The paper applied the genetic algorithm proved for current usefulness. it proposed the optimal operational way for SCM by dividing into 2 ways for dealing with the duration of confirmed demanding information and various fluctuation.

조선소의 생산성은 제한된 자원을 얼마나 효율적이고 체계적으로 관리하고 사용하는가에 달려있다. 최근 들어 조선소에서는 생산관리 시스템을 고도화하기 위해 시뮬레이션 기법을 적용한 연구가 활발히 진행되고 있다. 본 논문에서는 시뮬레이션 기법을 생산관리에 적용한 조선소의 시뮬레이션 기반 생산 개념을 연구하였다. 이는 조선소 현장에서 경험과 직관에 의한 의사결정을 지양하고, 정량적이고 구체적인 데이터에 기반을 둔 개선방안을 확립할 수 있게 한다. 본 논문에서는 조선소의 생산 계획 중 선표 계획 영역에 대한 시뮬레이션 적용 연구를 수행하였으며, 이를 위해 조선소의 생산 계획 프로세스와 시스템을 분석하고 상용 시뮬레이션 소프트웨어를 이용한 시뮬레이션 시스템의 설계를 수행하였다. 이러한 시뮬레이션 시스템은 현재 조선소 생산관리 시스템의 운용환경을 고려하여 웹 환경에서 운용가능한 구조를 갖고 있으며, 이를 통해 조선소에서는 보다 손쉽게 생산 계획을 시뮬레이션하고 결과를 분석함으로써 보다 신뢰도 높은 생산 계획을 수립할 수 있을 것으로 기대한다.

The demand for facility used in producing multi-products is changed dynamically for discrete and finite time periods. The excess or the shortage for facility is occurred according to difference of the facility capacity size and demand for facility through given time periods. The shortage facility is met through the outsourcing production. The excess facility cost is considered for the periods that the facility capacity is greater than the demand for the facility, and the outsourcing production cost is considered for the periods that the demand for facility is greater than the facility capacity. This paper addresses to determine the facility capacity size, outsourcing production products and amount that minimizes the sum of the facility capacity cost, the excess facility cost and the outsourcing production cost. The characteristics of the optimal solution are analyzed, and an algorithm applying them is developed. A numerical example is shown to explain the problem.

본 논문은 (1 : 1 : N) 재고모형에 대한 복수제품의 순환생산 및 배송 일정계획을 수립하는 연구를 수행하였다. 세부적으로 공급자가 원자재를 생산자에게 배송하면, 생산자는 순환생산방식을 활용하여 복수의 제품을 생산하여 N 구매자에게 배송하는 상황을 고려하고 있다. 본 연구의 목적은 공급자, 생산자, 구매자를 포함하는 시스템 전체의 비용을 최소화하는 계획을 수립하는 것이다. 최적해가 가지는 몇 가지 특성들을 분석하고, 이를 통해서 단계적인 휴리스틱 절