• IE interfaces
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• v.21 no.4
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• pp.418-434
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• 2008

This paper studied issues in decision making on the production control policy of a cathode plate manufacturing process in zinc refining plant. The present production system has a long lead time from raw materials (aluminum plate) to products (cathode plate) due to many WIP inventories. Because WIP inventories are stocked at each process and moved from one place to another frequently, they are the main cause of inefficiency in the process. In this paper, to solve this problem, several production control policies have been identified and studied. Several simulation models are used to compare the performances of these production control policies. The output lead time and WIP (Work In Process) of real production system are compared with those of simulation models. PUSH, CONWIP, DBR, KANBAN and CONWIP-DBR models have been used to simulate and review the optimized production control policy that achieves the target output quantities with decreased lead time and WIP. The simulation results of each production control policy show that CONWIP and CONWIP-DBR models are the good production control policy under the present production system. Especially in present production system, CONWIP with one parameter is easier control policy than CONWIP-DBR with two parameters. Therefore CONWIP has been selected as the best optimum production control policy. With CONWIP, lead time has been reduced by 97% (from 6,653 to 187 minute) and WIP has been reduced from 1,488 to 53, compared to the present system.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.1
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• pp.47-57
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• 2010

There have been many problems to apply SPC(Statistical Process Control) which is a traditional process control technology to the process of multi-product, small-sized production because a machine in the process manufactures small numbers, but various kinds of products. Therefore, we need the new process control system that can flexibly control the process by setting up the SPEC rules and the KNOWHOW rules. The SPEC rule contains the combination of diverse conditions to specify the characteristics of various products. The KNOWHOW rule is based on engineers' know-how. The study suggests the Rule-base Process Control that can be optimized to the multi-product, small-sized production. It was validated in the process of semiconductor production.

• Journal of the Korea Institute of Building Construction
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• v.5 no.4 s.18
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• pp.153-164
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• 2005

This study aims at establishing JIT production management system to enable manage the resources input into from procurement through construction based on correct identification of the process, an analysis on the amount of input materials and information sharing. This study has focused on the process control and working process of rebar work in domestic apartment house construction where the overall scope of Process from the planning phase to the construction phase has been analyzed in this study. Also construction phase was selected for the application of a sample case. A basic model for JIT production was generated with these processes. Furthermore A questionnaire and the on-site survey with process, checklist and control data were prepared and performed for the application of JIT production management model into rebar work. The governing scopes of JIT production management system include process management, material management, yard loading and moving management and inventory control, and the operation of each control item

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.102-109
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• 2018

This paper seeks to present a multi-control method that can contribute to effective control of the production line with multiple bottleneck processes. The multi-control method is the production system that complements shortcomings of CONWIP and DBR, and it is designed to determine the raw material input according to the WIP level of two bottleneck processes and WIP level of total process. The effectiveness of the production system developed by applying the multi-control method was verified by the following three procedures. Raw material input conditions of the multi-control method are as follows. First, raw materials are go into the production line when the number of the total process WIP is lower than established number of WIP in total process and first process is idle. Second, raw materials are introduced when the number of WIP of two bottleneck processes is lower than the established number of WIP of each bottleneck process. Third, raw materials are introduced when the first process and in front of bottleneck process are idle even if the number of WIP in the total process is less than established number of WIP of the total process. The production line with two bottleneck processes was selected as the condition for production environment, and the production process modeling of CONWIP, DBR and multi-control production method was defined according to the production condition. And the optimum limited WIP level suitable for each system was obtained by applying a genetic algorithm to determine the total limited number of WIP of CONWIP, the limited number of WIP of DBR bottleneck process, the number of WIP in the total process of multi-control method and the limited number of WIP of bottleneck process. The limited number of WIP of CONWIP, DBR and multi-control method obtained by the genetic algorithm were applied to ARENA modeling, which is simulation software, and a simulation was conducted to derive result values on the basis of three criteria such as production volume, lead time and number of goods in-progress.

• Journal of the Korea Safety Management & Science
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• v.8 no.6
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• pp.109-118
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• 2006

This paper proposes service layout strategy considering service characteristics by the use of benchmarking production system such as layout by P-Q chart, improvement tool, automated system, Toyota production system and lean production system. This paper represents operation methodology of statistical process control using control chart for service performance outcomes.

• Korean Management Science Review
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• v.31 no.3
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• pp.27-39
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• 2014

We derive a generalized statistic form of Q control chart, which is especially suitable for short run productions and start-up processes, for the detection of process mean shifts. The generalization means that the derived control chart statistic concurrently uses within lot variability and between lot variability to explain the process variability. The latter variability source is noticeably prevalent in lot type production processes including semiconductor wafer fabrications. We first obtain the generalized Q control chart statistic when both the process mean and process variance are unknown, which represents the case of implementing statistical process control charting for short run productions and start-up processes. Also, we provide the corresponding generalized Q control chart statistics for the rest of three cases of previous Q control chart statistics : (1) both the process mean and process variance are known (2) only the process mean is unknown and (3) only the process variance is unknown.

• International Journal of Quality Innovation
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• v.3 no.2
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• pp.46-56
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• 2002

The presence of imprecise measurement may seriously affect the efficiency of process control and production cost. A cost model is derived to determine the design parameters of the economic asymmetric $\bar{X}$ and S control charts including measurement errors. The effects of imprecise measurement on the performance of the economic asymmetric $\bar{X}$ and S control charts and production cost are examined for the case where the process mean and process standard deviation may change. Application of the proposed control charts is demonstrated through an example. Numerical examples illustrate the effects of imprecise measurement on the design parameters of the proposed control charts. It shows that the imprecision measurement may seriously affrct the ability of the proposed control charts to detect process disturbances quickly, change the sampling frequency, and increase the production cost compared to the control charts excluding measurement errors.

• Journal of the Korea Management Engineers Society
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• v.23 no.4
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• pp.73-86
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• 2018

Most electric products produced during the manufacturing process are produced after design and mass production under a given control standard. In particular, the development phase should present the criteria for the production process by setting appropriate limits based on the performance being targeted. Even if the standard of performance is set considering the performance of the process, measuring the performance of the product after actual production results will cause nonconformities with the expected results. Among the performance of electrical products, Energy standards represented by energy consumption efficiency continue to be of importance, and are mandatory standards that correspond to national standards in most countries. Therefore, statistical quality control of these standards shall basically have a large number of test equipment for each product, ensure sufficient test time and continuous sampling of product samples. In the end, companies that produce and sell electric appliances are striving to control mass production at a great cost, but this is not acceptable. This study presents basic characteristics of the energy efficiency of electrical products and proposes and conducts a case study on statistical production control methods for performance variation across products under the standards about domestic and international regulations.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.2
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• pp.89-97
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• 2012

This paper considers a manufacturer with a two-station make-to-stock and make-to-order serial production system. The MTS facility produces a single type of component and provides components for the MTO facility that produces customized products. In addition to the internal demand from the MTO facility, the MTS facility faces demands from the spot market with the option of to accept or reject each incoming demand. This paper addresses a joint component inventory rationing and batch production control which maximizes the manufacturer's profit. Using the Markov decision process model, we investigate the structural properties of the optimal inventory rationing and batch production policy, and present two types of heuristics. We implement a numerical experiment to compare the performance of the optimal and heuristic policies and a simulation study to examine the impact of the stochastic process variability on the inventory rationing and batch production control.

• Journal of the Korea Safety Management & Science
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• v.14 no.3
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• pp.167-174
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• 2012

In the manufacturing process the most widely used $\bar{X}$ chart has been applied to control the process mean. Also, Accelerated Life Test(ALT) is commonly used for efficient assurance of product life in development phases, which can be applied in production reliability acceptance test. When life data has lognormal distribution, through censored ALT design so that censored ALT data has asymptotic normal distribution, $ALT\bar{X}$ control chart integrating $\bar{X}$ chart and ALT procedure could be applied to control the mean of process in the manufacturing process. In the situation that process variation is controlled, $Z_p$ control chart is an effective method for the very small fraction nonconforming of quality characteristic. A simultaneous control scheme with $ALT\bar{X}$ control chart and $Z_p$ control chart is designed for the very small fraction nonconforming of product lifetime.