• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.74-80
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• 2021

This study investigated the process quality level of a K5 gas mask, which recently acquired its operational capability, through statistical process analysis for the mass production stages and their lots. The tensile adhesion strength was the only operating requirement in the manufacturing process of the K5 gas mask. For this purpose, the results of tensile adhesion strength between the lens and facial rubber during the initial and second mass production stages were analyzed using conventional statistical and statistical process analysis methods. The conventional statistical results indicated that the second mass production stage was better than the initial mass production stage. In cases of a control chart and process capability of tensile adhesion strength, the process quality level was also improved by following the mass production stages. The improvement was caused by process stabilization and work skill elevation. These results and methods are expected to be conducted and utilized in the third mass production stage. Moreover, quality improvement of K5 gas mask mass production can be achieved using the Lean 6 sigma procedure, MDAIC (Define, Measure, Analyze, Improve, Control).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.79-86
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• 2017

This research focused on deciding optimal manufacturing WIP (Work-In-Process) limit for a small production system. Reducing WIP leads to stable capacity, better manufacturing flow and decrease inventory. WIP is the one of the important issue, since it can affect manufacturing area, like productivity and line efficiency and bottlenecks in manufacturing process. Several approaches implemented in this research. First, two strategies applied to decide WIP limit. One is roulette wheel selection and the other one is elite strategy. Second, for each strategy, JIT (Just In Time), CONWIP (Constant WIP), Gated Max WIP System and CWIPL (Critical WIP Loops) system applied to find a best material flow mechanism. Therefore, pull control system is preferred to control production line efficiently. In the production line, the WIP limit has been decided based on mathematical models or expert's decision. However, due to the complexity of the process or increase of the variables, it is difficult to obtain optimal WIP limit. To obtain an optimal WIP limit, GA applied in each material control system. When evaluating the performance of the result, fitness function is used by reflecting WIP parameter. Elite strategy showed better performance than roulette wheel selection when evaluating fitness value. Elite strategy reach to the optimal WIP limit faster than roulette wheel selection and generation time is short. For this reason, this study proposes a fast and reliable method for determining the WIP level by applying genetic algorithm to pull system based production process. This research showed that this method could be applied to a more complex production system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.3
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• pp.117-124
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• 2008

Ultra-high voltage transformer industry has characteristic of small quantity batch production system by other order processing unlike general mass production systems. In this industry, observance of time deadline is very important in market competitive power security and company continued existence. The transformer winding is a process that rolls a coil is coated with an electric insulation material in order to generate the required voltage using the voltage fluctuation. The winding process is very important production process in the extra-high voltage transformer manufacturing industry because winding process is core process that occupy weight about half of whole process and is process that decide current ratio of transformer. This paper proposes a statistical calculation and control method of planned leadtime on the basis of real data and informations for the A company in transformer winding process. Moreover, we develop unit process scheduling system.

• Journal of environmental and Sanitary engineering
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• v.15 no.3
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• pp.24-30
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• 2000

In this study, to determine the optimum fermentation process for the feed production of food wastes and estimate the practical value of fermented feed using kudzu creeper and sawdust as bulking agent. This study considered initial C/N ratio control as the fermentation process variables. The result are summarized as follows. Minimum water contents of byproducts in the fermentation feed production showed 39%(kudzu), 37%(sawdust) at the C/N ratio 25 and 45%(kudzu, sawdust) at the C/N ratio 35. Temperature variations in the fermentation feed production at the C/N ratio 25 indicated $68^{\circ}C$(kudzu), $70^{\circ}C$(sawdust). Optimum condition of fermentation process of water content, C/N ratio and permeability (porous structure of the mixture). For optimum fermentation gravitationally dewatered garbage, the proper mixing ratios of kudzu(moisture contents : 17.3%) and sawdust(moisture contents : 13.2%) were 41% and 39%, respectively. Major biological reaction in the aerobic fermentation feed production occurred during 12~24hrs.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.448-457
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• 1998

A neural network based control algorithm with fuzzy compensation is proposed for the automated adjustment in the production of electronic end-products. The process of adjustment is to tune the variable devices in order to examine the specified performances of the products ready prior to packing. Camcorder is considered as a target product. The required test and adjustment system is developed. The adjustment system consists of a NNC(neural network controller), a sub-NNC, and an auxiliary algorithm utilizing the fuzzy logic. The neural network is trained by means of errors between the outputs of the real system and the network, as well as on the errors between the changing rate of the outputs. Control algorithm is derived to speed up the learning dynamics and to avoid the local minima at higher energy level, and is able to converge to the global minimum at lower energy level. Many unexpected problems in the application of the real system are resolved by the auxiliary algorithms. As the adjustments of multiple items are related to each other, but the significant effect of performance by any specific item is not observed. The experimental result shows that the proposed method performs very effectively and are advantageous in simple architecture, extracting easily the training data without expertise, adapting to the unstable system that the input-output properties of each products are slightly different, with a wide application to other similar adjustment processes.

• IE interfaces
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• v.14 no.1
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• pp.9-19
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• 2001

Production planning and control system plays an important role in manufacturing companies because it determines all production capacity planning, material procurement planning, and production scheduling which are needed in the process of producing products. Many researches on production planning and control system have been conducted for many manufacturing companies for recent decade. But, a considerable research achievement has mainly been obtained on the forecast-driven production for a make-to-stock and an assemble-to-order. The reason is that there are some hardships such as difficulties of standardizing product information, the frequent changes of design and material, and the unexpected dynamic events that influence the production of customer's order in a make-to-order or an engineering-to-order environments. By these characteristics and their complexities, some studies for production planning and control system in a make-to-order environment are presented recently. In this paper, we present the framework of the hietachical production planning and control for a make-to-order environment with dynamic events. In order to illustrate the usefulness of the proposed framework for a hietachical production planning and control, the information system for a make-to-order production was implemented with the object of the company of producing electricity transformer.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.3
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• pp.10-17
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• 2016

Control Chart is a graph which dots the characteristic values of a process. It is the tool of statistical technique to keep a process in controlled condition. It is also used for investigating the state of a process. Therefore many companies have used Control Chart as the tool of statistical process control (SPC). Products from a production process represent accidental dispersion values around a certain reference value. Fluctuations cause of quality dispersion is classified as a chance cause and a assignable cause. Chance cause refers unmanageable practical cause such as operator proficiency differences, differences in work environment, etc. Assignable cause refers manageable cause which is possible to take actions to remove such as operator inattention, error of production equipment, etc. Traditionally ${\bar{x}}-R$ control chart or ${\bar{x}}-s$ control chart is used to find and remove the error cause. Traditional control chart is to determine whether the measured data are in control or not, and lets us to take action. On the other hand, RNELCC (Reflected Normal Expected Loss Control Chart) is a control chart which, even in controlled state, indicates the information of economic loss if a product is in inconsistent state with process target value. However, contaminated process can cause control line sensitive and cause problems with the detection capabilities of chart. Many studies on robust estimation using trimmed parameters have been conducted. We suggest robust RNELCC which used the idea of trimmed parameters with RNEL control chart. And we demonstrate effectiveness of new control chart by comparing with ARL value among traditional control chart, RNELCC and robust RNELCC.

• Journal of Korean Society for Quality Management
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• v.5 no.2
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• pp.3-20
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• 1977

The purpose of this Study is to develope the Role of Statistics in Industrial mass production. The process of mass production will be divided into three steps, that is, Standardization, production and inspection. The Statistics is applied to Specificat-ions, Quality Control and Sampling inspection in these three steps. The applications have developed to Statistical methods based on probability theory. And then, The improved plan is exhibited the point of problems of introducting of spreading of quality control throughout field survey.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.4
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• pp.8-15
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• 2004

Gilding process make thin membrane with other metals to surface of metal and metalloid. It control the hydrogen ion and oxalic acid density with rinsing work since the process used to acid and alkali. Therefore, in this study, several control method applied the gilding process. It desired to the optimal controller and their results can be save on water resource by useful feed of rinsing. And there is quite a possibility of uniform production due to fixed control of acid and alkali. Also it can be contributed the competition power because of lower production unit cost. Especially, this control method to be developed can be applied to any process without mathematical model. And it can be changed their algorithm more easily, if control object is changed.

• IE interfaces
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• v.11 no.2
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• pp.1-11
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• 1998

In this paper, a case study is introduced on the development on a production planning system for the efficient control of work-in-process material flows. A special attention has been given to the prevention of the shortage of the automobile-components at the auto-assembly lines and the dynamic adaptation of the production plan to the continuously changing environment. The expertise of the production planner is analyzed and transformed into the logic of the software developed.