• Title, Summary, Keyword: improvement of manufacturing process

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Manufacturing strategy and change programs of Korean firms (한국제조기업의 생산전략과 생산혁신활동)

  • 이승규;김진섭
    • Korean Management Science Review
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    • v.13 no.1
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    • pp.135-156
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    • 1996
  • The purpose of this paper is to study the links between manufacturing strategy and change programs of manufacturing firms in Korea. The nature of our analysis is more descriptive than normative or confirmative. First, we investigate the linkage between manufacturing strategy, manufacturing capability, change programs and performance measurement systems. Secondly, we intend to explore an empirical typology of manufacturing strategy and change programs. The initial findings of the study are as follows: Linkage between manufacturing strategy and change programs of manufacturing firms was not apparent. Flexibility as a strategic priority is positively related to the innovative change programs. There are two distinctive strategies of manufacturing firms in Korea, namely, quality strategy and balanced strategy. We identified three types of change programs, which are incremental change, administrative innovation, and process innovation. Incremental change group has represented low factor score in the change program dimensions. The firms in administrative innovation group mainly depend on information systems and business reengineering. Korean manufacturing firms seem to pursue process improvement by trying simultaneously incremental change in the process, managerial process improvement, and a little bit of innovative change. Performance variable utilization of the firms are not significantly different along with manufacturing strategies and change programs. We found, however, learning and improvement performance dimension is significantly related to flexibility variables. Process innovation group marked high score in usage of learning and improvement indices. The findings of this study seem to have various implications on realigning the manufacturing strategy, change programs, and performance systems in Korean firms.

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A Study on the Design of Experiment Planning for Quality Improvement in Flow Shop Manufacturing System (흐름생산시스템에서 품질향상을 위한 실험 계획 설계 -이산화망간-리튬 전지의 품질 향상을 중심으로)

  • 박해천;홍남표
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.24 no.63
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    • pp.101-110
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    • 2001
  • This study is concern with the design of experiment planning for quality improvement in flow shop manufacturing system. In this study, the procedure of two stage experiment planning are proposed and applied to the manufacturing process of Li/$MnO_2$ batteries. The result of in this paper is that, compared with the current process conditions, 52% of the insulation inspection process, 81.6% of the first premier discharge process, 98.5% of the second premier discharge process, 84.7% of O.C.V./C.C.V. process, and 86.2% of voltage inspection process are decreased. After a given period of time, the life of the batteries extends to 75 hours, which means the 15% improvement in capacity. In case that the proposed methods are applied to the process Improvements of the flow shop manufacturing system, the much effected in experimental cost- saving and quality improvement.

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A Study on Quality Improvement Method for Manufacturing Process Plan (제조공정계획의 품질개선기법에 관한 연구)

  • Kim, In-Ho
    • Korean Journal of Computational Design and Engineering
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    • v.13 no.3
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    • pp.235-242
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    • 2008
  • This paper proposes a method for improving the process plan quality by use of dimensional tolerances. Dimensioning and tolerancing plays a key role in manufacturing process plan because the final part must ensure conformance with the dimensions and tolerances in its drawing. As a first step for the improvement of process plan quality, two resultant tolerances in design and process plan should be compared each other, and so a tolerance chart is used for acquisition and comparison of the two tolerances. In addition to two kinds of design and manufacturing tolerances, operational sequences or paths for the resultant dimension and tolerance are additionally recognized for measuring the quality of process plan quantitatively. Rooted tree is applied to find the related paths for the manufacturing resultant tolerances. A quality coefficient is defined by the components of two tolerances and their relations, the paths related to manufacturing resultant tolerances and the difficulty of an operation. In order to improve the quality of manufacturing process plan, the paths that two kinds of tolerances are the same or different in the rooted tree are recognized respectively and a method for tolerance rearrangement is developed. A procedure for improving the quality is suggested by combining the coefficient and the tolerance rearrangement method. A case study is applied to illustrate the efficiency of improvement method.

A Study on Productivity Improvement through Safety Management and Manufacturing Process Reengineering : Case Study in Polyurethane Manufacturer (안전관리 및 생산 공정 개선을 통한 생산성 향상에 관한 연구 : 폴리우레탄 제조업체 사례)

  • Kim, Hyun Soo;Lee, Hyeong-Ryong;Kwon, Ick-Hyun
    • Journal of the Korea Safety Management and Science
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    • v.15 no.4
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    • pp.185-196
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    • 2013
  • Polyurethane is an elastomer polymer, which is flexible, tough and resistant. This material is widely used various fields such as automobile, aeroplane, textiles, construction industries. Currently there exists more than 1,000 manufacturing companies in Korea that are closely related to Polyurethane. In spite of a number of Polyurethane manufacturing companies, there are little attention in academia as well as industries to study the safety and manufacturing process improvement on Polyurethane. In this paper, we consider a case study for the Polyurethane manufacturer to improve productivity by using safety management and manufacturing process reengineering. After careful analysis, we derive three enhancements to increasing the safety and productivity for the target company. Especially, we achieve about 16% productivity improvement in roller manufacturing process by replacing manual stirring job with automated mixing machine.

A Case Study for Quality Improvement Process for the PCB Manufacturing (PCB 제조에 있어서의 품질개선 사례 연구)

  • 진홍기;백인권;손기목;서정원
    • Journal of the Korean Society for Quality Management
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    • v.26 no.2
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    • pp.106-117
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    • 1998
  • The following study has been undertaken to build QIP (Quality Improvement Process) of an inner-layer process in a PCB (Printed Circuit Board) manufacturing plant. The objective of the study is stabilization and optimization of the process through quality improvement. To do that, defective factors in process are gathered by the cause and effect analysis and classified by PFD (Process Flow Diagram), key factors are found out by PFMECA (Process Failure Mode and Effect Criticalty Analisis), DOE(Design of Experiments) is a, pp.ied to those key factors to optimize the process, SPC (Statistical Process Control) chart is used to maintain the optimal conditions of the process and to improve quality continuously, and a quality management system is developed to improve quality mind and quality system for the PCB jmanufacturing plant. Overall, QIP is established to improve quality for the PCB manufacturing plant in the study.

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Dynamic Yield Improvement Model Using Neural Networks (신경망을 이용한 동적 수율 개선 모형)

  • Jung, Hyun-Chul;Kang, Chang-Wook;Kang, Hae-Woon
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.32 no.2
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    • pp.132-139
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    • 2009
  • Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring technology, many industries operate the production lines that are developed into automation system. In these production lines, the product structures are very complexity and variety. So, there are many multi-variate processes that need to be monitored with many quality characteristics and associated process variables at the same time. These situations have made it possible to obtain super-large manufacturing process data sets. However, there are many difficulties with finding the cause of process variation or useful information in the high capacity database. In order to solve this problem, neural networks technique is a favorite technique that predicts the yield of process for process control. This paper uses a neural networks technique for improvement and maintenance of yield in manufacturing process. The purpose of this paper is to model the prediction of a sub process that has much effect to improve yields in total manufacturing process and the prediction of adjustment values of this sub process. These informations feedback into the process and the process is adjusted. Also, we show that the proposed model is useful to the manufacturing process through the case study.

Heuristic Algorithm for Selecting Mutually Dependent Qualify Improvement Alternatives of Multi-Stage Manufacturing Process (다단계제조공정의 품질개선을 위한 종속대안선택 근사해법)

  • 조남호
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.11 no.18
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    • pp.7-15
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    • 1988
  • This study is concerned with selecting mutually dependent quality improvement alternatives with resource constraints. These qualify improvement alternatives art different fro the tradition at alternatives which are independent from each other. In other words, selection of any improvement alternative requires other related specific improvement. Also the overall product quality in a multi stage manufacturing process is characterized by a complex multiplication method rather than a simple addition method which dose not allow to solve a linear knapsack problem despite its popularity in the traditional study. This study suggests a non-linear integer programming model for selecting mutually dependent quality improvement alternatives in multi-stage manufacturing process. In order to apply the model to selecting alternatives. This study also suggests a heuristic mode1 based on a dynamic programming model which is more practical than the non-linear integer programming model. The logic of the heuristic model enables 1) to estimate improvement effectiveness values on all improvement alternatives specifically defined for this study. 2) to arrange the effectiveness values in a descending order, and 3) to select the best one among the alternatives based on their forward and backward linkage relationships. This process repeats to selects other best alternatives within the resource constraints. This process is presented in a Computer programming in Appendix A. Alsc a numerical example of model application is presented in Chapter 4.

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W-function for the Improvement of the Network in Manufacturing Process (제조공정 Network의 개선을 위한 W-함수)

  • 이상도;박기주
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.12 no.20
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    • pp.71-76
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    • 1989
  • In this paper, GERT network in modeled to improve the network of manufacturing process with feedback loop. A lot of Information on the GERT network can be derived from the equivalent W-function and MGF(moment generating function) using Mason's rule. These equations are used in calculating the variations of the performance measure and in improving the system performance. System improvement in manufacturing process is achieved by increasing the equivalent probabilities of each branches and by decreasing the expected equivalent time.

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Improvement of Manufacturing Drawings for Manufacturing Quality Assurance of Modular Housing Unit (모듈러 주거시설의 단위유닛 제작품질 확보를 위한 공장제작도서 개선 연구)

  • Hwang, Hyun-Jun;Jung, Chan-woo
    • Journal of the Korean housing association
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    • v.27 no.6
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    • pp.137-144
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    • 2016
  • In modular architecture, manufacturing drawing which includes whole information for modular unit production is essential since works for modular unit have to be performed in manufacturing factory not construction field. Although the manufacturing drawing is important as known it is insufficient to utilize the manufacturing drawing in modular architecture project and this makes modular unit low-quality with re-work and work time delay. To prevent low-quality modular unit caused by insufficient manufacturing drawing, in this research firstly manufacturing drawing's current situation and error cases in manufacturing phase of past modular housing project were analyzed, and correlation between reduction of errors occurance frequency and improving manufacturing drawing was verified. Secondly manufacturing drawing improvement factors were deducted in interior, furniture, mechanical work phase which errors' occurance rate is high and the way of deducting manufacturing drawing lists and contents were suggested with light-weight work as an example in case of new type of errors occurance. A series of research process can contribute to good-quality modular unit by errors reduction. As a result of research, about half of errors occurance can be reduced with suggested manufacturing drawing improvement factors. And the manufacturing drawing process can contribute to modular production which have uniform quality.

Development of Prediction Model using PCA for the Failure Rate at the Client's Manufacturing Process (주성분 분석을 이용한 고객 공정의 불량률 예측 모형 개발)

  • Jang, Youn-Hee;Son, Ji-Uk;Lee, Dong-Hyuk;Oh, Chang-Suk;Lee, Duek-Jung;Jang, Joongsoon
    • Journal of Applied Reliability
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    • v.16 no.2
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    • pp.98-103
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    • 2016
  • Purpose: The purpose of this paper is to get a meaningful information for improving manufacturing quality of the products before they are produced in client's manufacturing process. Methods: A variety of data mining techniques have been being used for wide range of industries from process data in manufacturing factories for quality improvement. One application of those is to get meaningful information from process data in manufacturing factories for quality improvement. In this paper, the failure rate at client's manufacturing process is predicted by using the parameters of the characteristics of the product based on PCA (Principle Component Analysis) and regression analysis. Results: Through a case study, we proposed the predicting methodology and regression model. The proposed model is verified through comparing the failure rates of actual data and the estimated value. Conclusion: This study can provide the guidance for predicting the failure rate on the manufacturing process. And the manufacturers can prevent the defects by confirming the factor which affects the failure rate.