• IE interfaces
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• v.21 no.3
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• pp.343-353
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• 2008

Vendor-managed inventory(VMI) is a supply chain strategy to improve the inventory turnover and customer service in supply chain management. Unfortunately, many VMI programs fail because they simply transfer the transactional aspects of placing replenishment orders from customer to vendor. In fact, such VMI programs often degrade supply chain performance because vendors lack capability to plan the VMI operations effectively in an integrated way under the dynamic, complex, and stochastic VMI supply chain environment. This paper presents a decision support system, termed DSSV, for VMI in the retail supply chain. DSSV supports the market forecasting, vendor's production planning, retailer's inventory replenishment planning, vehicle routing, determination of the system operating parameter values, retailer's purchase price decision, and what-if analysis. The potential benefits of DSSV include the provision of guidance, solution, and simulation environment for enterprises to reduce risks for their VMI supply chain operations.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.09a
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• pp.359-359
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• 1995

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.231-238
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• 2014

Optimum lot size calculation for real world manufacturing environment has been focused since last few decades. Several extensions have been made to the basic economic order and production order quantity models to realize the possible practical situations in industry. However, focus on work-in-process inventory has been ignored relatively. This paper provides a comprehensive review of the models developed for group technology based manufacturing environment focusing on work-in-process inventory. Models have been extended from a perfect manufacturing conditions to an imperfect manufacturing situation considering rework, rejection and inspection. Optimum lot size has been evaluated using a simple algebraic optimization approach. Significant parameters are highlighted using sensitivity analysis for the developed models. Numerical example is used to illustrate the utilization of such models in day-to-day production setups and the impact of significant factors' variation on total cost and optimum lot size.

• Proceedings of the Safety Management and Science Conference
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• 2001.05a
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• pp.185-188
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• 2001

Many production management systems for increasing productivity, minimizing inventory, keeping due dates and maximizing use of resources have been proposed, and GT, MRP and JIT are frequently used among these systems. The three systems have merits and demerits through comparing with each other. Because each system has mutual dependence, a hybrid production system is necessary for using their merits maximally. In this study, a hybrid production system is designed by combining GT, MRP and JIT, which is suitable in the domestic production system.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.111-127
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• 2004

We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.237-244
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• 2018

The Smart Factory level of manufacturing factories of SMEs now lacks a system for grasping the accurate inventory amount associated with inventory movements in managing warehouses at the basic level. Also, it is difficult to manage accurate materials for loss of data due to worker manual work and production method due to experience. In order to solve this problem, in this paper, automatic acquisition of inventory to minimize manual work to grasp workers' Inventory and improve automation is done. In the smart warehouse management system using the IoT-based autonomous mobile module, the autonomous mobile module acquires the data of the inventory storage while moving through the line. In order to grasp the material of the Inventory storage, The Camera module recognizes the name of the inventory storage. And Then, If output matches, the data measured by the sensor is transferred to the server. This data can be processed, saved in a database, and real-time inventory quantity and location can be grasped in a web-based monitoring environment for administrators. The Real-time Automatic Inventory (RAIC) systems is reduce manual tasks and expect the effects of automated inventory management systems.

• Journal of the Korea Safety Management & Science
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• v.3 no.1
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• pp.35-44
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• 2001

Today's environment of enterprise is changing. They have to face customers' demands with the right product, the right service and supply them at the right time. And aIso cut down logistics and inventory cost and bring up the Profit as much as they can. This means the change of putting enterprise first in importance to putting customer first in importance. therefore to correspond to customer's demand, shorting lead time is becoming a essential condition. The answer to this changes of environment is supply chain management In this study, we use Goldratt's drum-buffer-rope scheduling in between manufacturer and supplier. And when shortage of inventory occur, search for the supply chain's CCR. Pressing CCR for more production, and supply Inventory from logistic center to guide for inventory buffing. using logistic warehouse between manufacturer and supplier, can execute function of buffer.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.58
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• pp.89-100
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• 2000

There use many production management systems for increasing productivity, minimizing inventory, keeping due dates and maximizing use of resources. MRP, GT and JIT are popular among these systems. There use many production management systems for increasing productivity, minimizing inventory, keeping due dates and maximizing use of resources. MRP, GT and JIT are popular among these systems. In this study, we had designed mixed production system which integrated searching and grouping function of GT, purchasing function of JIT and based on MRP and developed related algorithms and applied systems. The developed system was based on appling renewed algorithms for existing MRP system. To test efficiency operated real-data but we have tested renewed algorithms using sample-data because of massive real-data.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.6 s.171
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• pp.135-143
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• 2005

The shoes process management monitoring system for supporting SCM is developed in this study. This system consists of a monitoring program, a conveyer system, a pneumatic unit, a controller, an USB camera, and a server and a client computer. To operate the developed system easily, the monitoring program using LabVIEW in the Windows environment is developed. This program consists of 5 modules: production management, inventory control, media management, defective management, and communication management. The developed system has several advantages: reduced time for managing process work, decreased labor costs, effective operation, and continuous work without an operator. Nowadays advanced manufacturing companies are trying to find a way to check the performance of their production equipments and plants from remote sites. Thus, to manage the developed system from remote sites, communication network is constructed. In order to evaluate the performance of the monitoring system, experiments were performed. The experimental results showed that the developed system provided a reliable performance and a stable communication.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.158-167
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• 1989

In this paper, a model is presented which incoporates the possibility of quality control at each of the production stages. We consider the TYPE I error and the TYPE II error in inspection procedures. In addition to alternative quality control configurations, the model integrates the carrying costs of in-process and finished inventory, quality of production process, reprocessing including fixed and variable cost. Our policy determines the value of optimal lot-size and reprocessing batch size in reducing the total costs. A numerical example illustrates the model framework and highlights the role of the decision variables.