• Title/Summary/Keyword: Rework probability

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Scheduling Algorithm for Nonidentical Parallel Machines Problem with Rework (Rework가 존재하는 이종병렬기계에서의 일정계획 수립)

  • Kang, Yong Ha;Kim, Sung Shick;Park, Jong Hyuck;Shin, Hyun Joon
    • Journal of Korean Institute of Industrial Engineers
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    • v.33 no.3
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    • pp.329-338
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    • 2007
  • This paper presents a dispatching algorithm for nonidentical parallel machines problem considering rework, sequence dependent setup times and release times. For each pair of a machine and a job type, rework probability of each job on a machine can be known through historical data acquisition. The heuristic scheduling scheme named by EDDR (Earliest Due Date with Rework probability) algorithm is proposed in this paper making use of the rework probability. The proposed dispatching algorithm is measured by two objective function value: 1) total tardiness and 2) the number of reworked jobs, respectively. The extensive computational results show that the proposed algorithm gives very efficient schedules superior to the existing dispatching algorithms.

Problem space based search algorithm for manufacturing process with rework probabilities affecting product quality and tardiness (Rework 확률이 제품의 품질과 납기준수에 영향을 주는 공정을 위한 문제공간기반 탐색 알고리즘)

  • Kang, Yong-Ha;Lee, Young-Sup;Shin, Hyun-Joon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.7
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    • pp.1702-1710
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    • 2009
  • In this paper, we propose a problem space based search(PSBS) algorithm to solve parallel machine scheduling problem considering rework probabilities. For each pair of a machine and a job type, rework probability of each job on a machine can be known through historical data acquisition. Neighborhoods are generated by perturbing four problem data vectors (processing times, due dates, setup times, and rework probabilities) and evaluated through the efficient dispatching heuristic (EDDR). The proposed algorithm is measured by maximum lateness and the number of reworked jobs. We show that the PSBS algorithm is considerably improved from the result obtained by EDDR.

An Adaptive Scheduling Algorithm for Manufacturing Process with Non-stationary Rework Probabilities (비안정적인 Rework 확률이 존재하는 제조공정을 위한 적응형 스케줄링 알고리즘)

  • Shin, Hyun-Joon;Ru, Jae-Pil
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.11
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    • pp.4174-4181
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    • 2010
  • This paper presents an adaptive scheduling algorithm for manufacturing processes with non-stationary rework probabilities. The adaptive scheduling scheme named by hybrid Q-learning algorithm is proposed in this paper making use of the non-stationary rework probability and coupling with artificial neural networks. The proposed algorithm is measured by mean tardiness and the extensive computational results show that the presented algorithm gives very efficient schedules superior to the existing dispatching algorithms.

An Analysis on the M/G/1 Bernoulli Feedback System with Threshold in Main Queue (Main Queue에 Threshold가 있는 M/G/1 Bernoulli Feedback 시스템 분석)

  • Lim, Si-Yeong;Hur, Sun
    • Journal of Korean Institute of Industrial Engineers
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    • v.27 no.1
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    • pp.11-17
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    • 2001
  • We consider the M/G/1 with Bernoulli feedback, where the served customers wait in the feedback queue for rework with probability p. It is important to decide the moment of dispatching in feedback systems because of the dispatching cost for rework. Up to date, researches have analyzed for the instantaneous-dispatching model or the case that dispatching epoch is determined by the state of feedback queue. In this paper we deal with a dispatching model whose dispatching epoch depends on main queue. We adopt supplementary variable method for our model and a numerical example is given for clarity.

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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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Analysis of the Relations between Design Errors Detected during BIM-based Design Validation and their Impacts Using Logistic Regression (로지스틱 회귀분석을 이용한 BIM 설계 검토에 의하여 발견된 설계 오류와 그 영향도간의 관계 분석)

  • Won, Jong-Sung;Kim, Jae-Yeo
    • Journal of the Korea Institute of Building Construction
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    • v.17 no.6
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    • pp.535-544
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    • 2017
  • This paper analyzes the relations between design errors, prevented by building information modeling (BIM)-based design validation, and their impacts in order to identify critical consideration factors for implementing BIM-based design validation in architecture, engineering, and construction (AEC) projects. More than 800 design errors detected by BIM-based design validation in two BIM-based projects in South Korea are categorized according to their causes (illogical error, discrepancy, and missing item) and work types (structure, architecture, and mechanical, electrical, and plumbing (MEP)). The probabilistic relations among the independent variables, including the causes and work types of design errors, and the dependent variables, including the project delays, cost overruns, low quality, and rework generation that can be caused by these errors, are analyzed using logistic regression. The characteristics of each design error are analyzed by means of face-to-face interviews with practitioners. According to the results, the impacts of design error causes in predicting the probability values of project delays, cost overruns, low quality, and rework generation were statistically meaningful.