• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.151-160
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• 2021

The purposes of this research were: 1) to analyze the confirmatory factors with the business operational model of entrepreneurs of small and medium enterprises (SMEs) in the textile and clothing industry, and 2) to verify the congruence of the model with the operational ways of the entrepreneurs of SMEs in the textile and clothing industry. The sample consisted of 500 small and medium enterprise entrepreneurs in the textile and clothing industry. This study was quantitative research and the instrument used to collect the data was a questionnaire. The data was analyzed using 1^st order and 2^nd order of confirmatory analysis (CFA). The findings of this research revealed that the model of SMEs in the textile and clothing industry was overall at a high level. Four main factors were used for the model of SMEs in the textile and clothing industry by their importance in descending order as follows: marketing mix (MM), collaboration network (CN), production inventory management (PIM), and creativity (CT). The results of verification of model congruence revealed the model of SMEs in the textile and clothing industry was fit and in accordance with the empirical data.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.151-157
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• 1993

In this paper, we investigate the effects of yield randomness for lot-sizing in a multi-stage production system. The practical importance of incorporating yield randomness into production models has been emphasized by many researchers. Yield randomness, especially in semiconductor manufacturing, poses a mojor challenge for production planning and control. The task becomes even more difficult if the demand for final product is uncertain. An attempt to meet the demand with a higher level of confidence forces one to release more input in the fabrication line. This leads to excessive work-in-process (WIP) inventories which cause jobs to spend unpredictably longer time waiting for the machines. The result is that it is more difficult to meet demand with exceptionally long cycle time and puts further pressure to increase the safety stocks. Due to this spiral effect, it is common to find that the capital tied in inventory is the msot significant factor undermining profitability. We propose a policy to determine the quantity to be processed at each stage of a multi-stage production system in which the yield at each stage may be random and may need rework.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.3-6
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• 2007

In the traditional inventory problem, market parameters such as demand and selling price are exogenous. But incorporating these factors into the model can provide an opportunity for increasing the total profit. So we investigate the joint price-inventory policy in a supply chain consisting of a single retailer and a single manufacturer. Demand at the retailer depends on the retail price. The retailer and the manufacturer cooperate closely each other to maximize overall profit of the supply chain. The mathematical model is presented and the solution procedure is developed in order to jointly determine the optimal policy including the retail price, the production lot sizes, and the delivery frequency from the manufacturer to the retailer.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.119-126
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• 2008

Growth and yield prediction methods, ranging from whole-stand models to individual-tree models, have been developed for forest types managed for wood production. The resultant models are used for a host of purposes including inventory updating, management planning, evaluation of silvicultural alternatives, and harvest scheduling. Because of the large investment in developing growth and yield models for improved genotypes and silvicultural practices for loblolly pine (Pinus taeda) in the Southern United States, this region serves to illustrate approaches for modelling intensively managed forests. Analytical methods and computing power generally do not restrict development of reliable growth and yield models. However, long-term empirical observations on stand development, which are time consuming and expensive to obtain, often limit modelling efforts. Given that growth and yield models are used to project present volumes and to evaluate alternative treatment effects, data of both the inventory type and the experimental type are needed. Data for developing stand simulators for loblolly pine plantations have been obtained from a combination of permanent plots in operational forest stands and silvicultural experiments; these data collection efforts are described and summarized. Modelling is essential for integrating and synthesizing diverse information, identifying knowledge gaps, and making informed decisions. The questions being posed today are more complex than in the past, thus further accentuating the need for comprehensive models for stand development.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.2
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• pp.17-33
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• 1996

Automatic transfer defined as an integrated system with a number of workstations, interstation storage buffers, automatic device and a control system, play a major role in ass production systems. Due to high capital investment needed for an automatic transferline, greater care should be taken in its design so as to maximize the system performance. One may to control the system performance is to control buffer storage. To control the interstation work-in-process inventory, we propose dual limit switches which control the buffer storage with two parameters, R and r. Under the policy, proceding station is forced down when the inventory level in the buffer reaches R until the level falls to r. For the model developed, we analyze the system characteristics and find the optimal control parameters with a serach procedure.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.161-170
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• 2019

Multi-product mass production small and medium enterprise factories have a wide variety of products and a large number of products, wasting manpower and expenses for inventory management. In addition, there is no way to check the status of inventory in real time, and it is suffering economic damage due to excess inventory and shortage of stock. There are many ways to build a real-time data collection environment, but most of them are difficult to afford for small and medium-sized companies. Therefore, smart factories of small and medium enterprises are faced with difficult reality and it is hard to find appropriate countermeasures. In this paper, we implemented the contents of extension of existing inventory management method through character extraction on label with barcode and QR code, which are widely adopted as current product management technology, and evaluated the effect. Technically, through preprocessing using OpenCV for automatic recognition and classification of stock labels and barcodes, which is a method for managing input and output of existing products through computer image processing, and OCR (Optical Character Recognition) function of Google vision API. And it is designed to recognize the barcode through Zbar. We propose a method to manage inventory by real-time image recognition through Raspberry Pi without using expensive equipment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.109-116
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• 2015

This paper is concerned with the single vendor single buyer integrated production inventory problem. To make this problem more practical, space restriction and lead time proportional to lot size are considered. Since the space for the inventory is limited in most practical inventory system, the space restriction for the inventory of a vendor and a buyer is considered. As product's quantity to be manufactured by the vendor is increased, the lead time for the order is usually increased. Therefore, lead time for the product is proportional to the order quantity by the buyer. Demand is assumed to be stochastic and the continuous review inventory policy is used by the buyer. If the buyer places an order, then the vendor will start to manufacture products and the products will be transferred to the buyer with equal shipments many times. The mathematical formulation with space restriction for the inventory of a vendor and a buyer is suggested in this paper. This problem is constrained nonlinear integer programming problem. Order quantity, reorder points for the buyer, and the number of shipments are required to be determined. A Lagrangian relaxation approach, a popular solution method for constrained problem, is developed to find lower bound of this problem. Since a Lagrangian relaxation approach cannot guarantee the feasible solution, the solution method based on the Lagrangian relaxation approach is proposed to provide with a good feasible solution. Total costs by the proposed method are pretty close to those by the Lagrangian relaxation approach. Sensitivity analysis for space restriction for the vendor and the buyer is done to figure out the relationships between parameters.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.197-207
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• 2018

SMEs manufacturing Factory, which are small-scale production systems of various types, mass-produce and sell products in order to meet customer needs. This means that the company has an excessive amount of material supply to reduce the loss due to lack of inventory and high inventory maintenance cost. And the products that fail to respond to the demand are piled up in the management warehouse, which is the reality that the storage cost is incurred. To overcome this problem, this paper uses ARIMA model, a time series analysis technique, to predict demand in terms of seasonal factors. In this way, demand forecasting model based on economic order quantity model was developed to prevent stock shortage risk. Simulation is carried out to evaluate the effectiveness of the development model and to demonstrate the effectiveness of the development model as applied to SMEs in the future.

• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.259-264
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• 2012

Automobile market was grown up by 1.7% at the first half of 2012 comparison with 2011 in China and this growth trend will be continued for a while. Under this market environment the China automobile companies expand the production capacity and result in heightening the intense competition for companies. This paper deals with the more efficient production line and production logistics through SPS(Synchronized Production System) with construction of MES(Manufacturing Execution System) in H automobile company in China. In plastic painting line we can simultaneously prepare the production quantity and delivery time according to assembly production plan by introducing MES. We can reduce the excess production and result in extreme reduction of inventory.

• Industrial Engineering and Management Systems
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• v.14 no.4
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• pp.401-412
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• 2015

In this paper, we present a modeling approach to production planning for an actual production line and a heuristic method. We also illustrate the successful implementation of the proposed method on the production line. A heuristic algorithm called the push-back algorithm was designed for a single machine earliness/tardiness production planning with distinct due date. It was developed by combining a minimum slack time rule and shortest processing time rule with a push-back procedure. The results of a numerical experiment on the heuristic's performance are presented in comparison with the results of IBM ILOG CPLEX. The proposed algorithm was applied to an actual case of production planning at Woongjin Chemical, a leading manufacturer of filter products in South Korea. The seven-month execution of our algorithm led to a 24.5% decrease in the company's inventory level, thus demonstrating its practicality and effectiveness.