• Title/Summary/Keyword: Production-process Management

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AI Smart Factory Model for Integrated Management of Packaging Container Production Process

  • Kim, Chigon;Park, Deawoo
    • International Journal of Internet, Broadcasting and Communication
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    • v.13 no.3
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    • pp.148-154
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    • 2021
  • We propose the AI Smart Factory Model for integrated management of production processes in this paper .It is an integrated platform system for the production of food packaging containers, consisting of a platform system for the main producer, one or more production partner platform systems, and one or more raw material partner platform systems while each subsystem of the three systems consists of an integrated storage server platform that can be expanded infinitely with flexible systems that can extend client PCs and main servers according to size and integrated management of overall raw materials and production-related information. The hardware collects production site information in real time by using various equipment such as PLCs, on-site PCs, barcode printers, and wireless APs at the production site. MES and e-SCM data are stored in the cloud database server to ensure security and high availability of data, and accumulated as big data. It was built based on the project focused on dissemination and diffusion of the smart factory construction, advancement, and easy maintenance system promoted by the Ministry of SMEs and Startups to enhance the competitiveness of small and medium-sized enterprises (SMEs) manufacturing sites while we plan to propose this model in the paper to state funding projects for SMEs.

The Failure Mode and Effects Analysis Implementation for Laser Marking Process Improvement: A Case Study

  • Deng, Wei-Jaw;Chiu, Chung-Ching;Tsai, Chih-Hung
    • International Journal of Quality Innovation
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    • v.8 no.1
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    • pp.137-153
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    • 2007
  • Failure mode and effects analysis (FMEA) is a preventive technique in reliability management field. The successful implementation of FMEA technique can avoid or reduce the probability of system failure and achieve good product quality. The FMEA technique had applied in vest scopes which include aerospace, automatic, electronic, mechanic and service industry. The marking process is one of the back ends testing process that is the final process in semiconductor process. The marking process failure can cause bad final product quality and return although is not a primary process. So, how to improve the quality of marking process is one of important production job for semiconductor testing factory. This research firstly implements FMEA technique in laser marking process improvement on semiconductor testing factory and finds out which subsystem has priority failure risk. Secondly, a CCD position solution for priority failure risk subsystem is provided and evaluated. According analysis result, FMEA and CCD position implementation solution for laser marking process improvement can increase yield rate and reduce production cost. Implementation method of this research can provide semiconductor testing factory for reference in laser marking process improvement.

A Study on the Risk Identification Methods for Initial and Mass Production Stage of Military Products Using FMEA (FMEA를 활용한 군수품 초도 생산 및 양산 단계의 위험 식별 방안 연구)

  • Lee, Chang Hee;Yang, Kyung Woo;Park, Du Il;Lee, Il Lang;Kwon, Jun Sig;Choe, Il Hong;Kim, Sang Boo
    • Journal of Korean Society for Quality Management
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    • v.42 no.3
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    • pp.311-324
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    • 2014
  • Purpose: It can deduce improvement plan that recognizes any risk factors in initial production and mass production by using FMEA and through this process, the appropriate criteria for defence items can be established. Methods: It proposes two methodology - Apply DT/OT data achieved from the beginning mass production stage based on FMECA data of the design stage, to risk management, and risk management plan that reflected line and field faliure data in case of is offered. Results: It proposes the risk management plan through Bayesian method and the risk identification that considered MTTF estimated value in case of initial production process. In case of mass production process, both risk identification by using fault occurrence frequency scores and Byaesian method, In case of the Initial production and mass production, it proposes use both two methods. Conclusion: A more realistic risk identification method can be applied, and by this method the quality improvement effect is expected.

A Standard Business Process of Resource Planning Systems for Footwear Production (신발생산 자원관리 시스템의 표준 비즈니스 프로세스)

  • 류영근;조남호
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 2002.06a
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    • pp.56-56
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    • 2002
  • The embodiment of working process fitting in characteristics of business each other in ERP system is indispensable factor. But, general ERP system is not so much profitable for the way of production management of footwear of domestic midge and small company that is dependant on most of the way of OEM production. Therefore, the development of ERP system fitted for present situation of the footwear manufacturing companies is necessary. For this, first, the business process for footwear production, for development of this system, have to be standardize and second, the model of Integrated system process based on standard business process have to be design for programming. In this paper, we proposed a method to build up standard business process and execute BPP in the point of the foundation for introduction and development of the resource planning systems only used by production of footwear and suited to the way of production management of the domestic companies manufacturing footwear. With this, we presented a process model of resource planning systems for footwear production. This study is focused on construction of integrated process model for production resource planning of ERP subsystems and the integrated process model consist of 13 modules.

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A Study on the Dispatching Rules of One-process Job Using Computer Simulation (시뮬레이션을 이용한 단공정작업의 스케줄링에 관한 연구)

  • 이기영;김영민
    • Journal of the Korea Safety Management & Science
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    • v.2 no.2
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    • pp.85-94
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    • 2000
  • This paper deals with the selection of a proper dispatching rule for an one-process Job scheduling that follows a particular distribution of an order production. That is, it makes a distribution on an order per unit period and applies to simulation model that uses it. This study consists of two purposes either seeks adequately production scheduling using priority rule or seeks extension of the facilities that increase current production efficiency through computer simulation in scheduling.

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A Study on Application Method of GT (GT기법의 적용항법에 대한 연구)

  • 이현용;이승우;강경식
    • Journal of the Korea Safety Management & Science
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    • v.2 no.2
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    • pp.139-153
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    • 2000
  • To develope a domestic machinery industry, international competition through reducing cost by increasing productivity is as important as evolving technology and increasing quality. In this study, we have studied in application of GT technology. GT is a skill that acquires high productivity using part's resemblance for multi part and small size production like mass production. We have classified group, such as design, layout and the others, to be applied systematically. The design group includes retrieval for drawings and study for GT design. The layout group includes GT layout, analysis of production process and study for composition method. And others include scheduling, standardization and standard process.

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Web-based Distributed Lean Construction Information System;Development of System Prototype (웹 기반 분산형 린건설 정보시스템 개발;시스템 프로토타입 개발)

  • Park, Moon-Seo;Yoon, You-Sang
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • 2007.11a
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    • pp.182-189
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    • 2007
  • To reform and improve the productivity of construction industry, 1) it should be encouraged to improve the construction production process and 2) it is required to enhance reliability of construction information based on the systematic thinking process. To promote the information reliability created during construction production process, Lean Construction Research Center(LRC2) is developing a supporting system to improve design/material supply/schedule management, functioning to efficiently manage the information created at construction production processes and developing a web based construction information system that provides result management/decision making support/knowledge based information services.

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A Methodology for Analysis and Simplification of Multi-level Dynamic Production Lot Sizing Problems (다단계 생산로트크기 결정문제의 분석과 단순화 방법)

  • 김갑환;박순오
    • Journal of the Korean Operations Research and Management Science Society
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    • v.24 no.4
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    • pp.13-26
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    • 1999
  • When we try to design a production planning system for a manufacturing company, it is a time consuming task to analyze various planning activities and identify inter-relationship among a lot of decisions made for the production planning. Most of the research efforts have been concentrated to well-organized independent decision-making problems that may usually be identified only after analyzing the characteristics of the decision-making process as a whole. In this paper, a methodology is suggested to characterize the whole process of the production planning for a manufacturing company and reduce the complexity of decision-making problems. The methodology is based on an experience of developing a production planning software for an automobile component manufacturer in korea. First, it is explained how to identify and represent the dependency among various decision-making variables. And a methodology is proposed to analyze the identified dependency among decision variables and identify decision-making process. Lastly, a practical example is provided to illustrate the analysis procedure in this paper.

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MAINTENANCE SETUP AND SETUP PERFORMANCE IMPROVEMENT IN AN UNRELIABLE PRODUCTION SYSTEM

  • Lee, Chang-Hwan
    • Management Science and Financial Engineering
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    • v.3 no.1
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    • pp.57-74
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    • 1997
  • An EOQ-like inventory model for a manufacturing process is studied. The system is assumed to deteriorate during the production process. The results are either the production of a number of defective items, or the breakdown of the production machine. The optimal production lot size is derived. The model is extended to the case in which the probabilities of making defective items and machine breakdowns are a function of both the quantity (amount) and quality (performance) of the consumed setup cost (including the preventive maintenance cost). We further assume that the setup performance can be improved by investing in the performance improvement program. Hence, the same or a better setup outcome can be achieved with a lower setup cost. We then investigate the optimal setup cost and investment policy simultaneously, thereby achieving a better process quality and setup cost reduction concurrently.

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Process Reliability Improvement and Setup Cost Reduction in Imperfect Production System

  • Lee, Chang-Hwan
    • Journal of the Korean Operations Research and Management Science Society
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    • v.22 no.4
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    • pp.93-113
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    • 1997
  • In studying an EOQ-like inventory model for a manufacturing process, a number of findings were made. The system can "go out of control" resulting in a relatively minor problem state or "break-down". When the production system is in the minor problem statei produces a number of defective items. It is assumed that each defective piece requires rework cost and related operations. Once the machine breakdown takes place, the production system produces severely defective items that are completely unusable. Each completely unusuable item is immediately discarded and incurs handling cost, scrapped raw material cost and related operations. Two investment options in improving the production process are introduced : (1) reducing the probability of machine breakdown, breakdowns, and (2) simultaneously reducing the probability of machine breakdowns and setup costs. By assuming specific forms of investment cost function, the optimal investment policies are obtained explicitly. Finally, to better understand the model in this paper, the sensitivity of these solutions to changes in parameter values and numerical examples are provided.amples are provided.

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