TY - JOUR

T1 - A probabilistic approach to the Stochastic Job-Shop Scheduling problem

AU - Shoval, Shraga

AU - Efatmaneshnik, Mahmoud

N1 - Publisher Copyright:
© 2018 Elsevier B.V. All rights reserved.

PY - 2018

Y1 - 2018

N2 - Uncertainty exists in almost any manufacturing process, and its effect may be detrimental to the manufacturing outcomes. In the Stochastic Job Shop Scheduling Problem (SJSSP), some of the process parameters are random variables, in particular the processing time. This paper considers another facet of the SJSSP, which is the probability for success (or failure) of a manufacturing job and its effect on other jobs. The paper presents a mathematical model for determining the expected manufacturing cost, and proposes heuristics for reducing that cost. The fundamental model is based on a single resource (e.g. a single machine) and a set of manufacturing jobs, each characterized by a cost and a probabilistic distribution for success. A failure causes either a re-work of the failed job, or restarting the entire process from the first job. Since the problem is NH Hard, a set of heuristics for scheduling the jobs is proposed, and simulation results validate these heuristics.

AB - Uncertainty exists in almost any manufacturing process, and its effect may be detrimental to the manufacturing outcomes. In the Stochastic Job Shop Scheduling Problem (SJSSP), some of the process parameters are random variables, in particular the processing time. This paper considers another facet of the SJSSP, which is the probability for success (or failure) of a manufacturing job and its effect on other jobs. The paper presents a mathematical model for determining the expected manufacturing cost, and proposes heuristics for reducing that cost. The fundamental model is based on a single resource (e.g. a single machine) and a set of manufacturing jobs, each characterized by a cost and a probabilistic distribution for success. A failure causes either a re-work of the failed job, or restarting the entire process from the first job. Since the problem is NH Hard, a set of heuristics for scheduling the jobs is proposed, and simulation results validate these heuristics.

KW - Stochastic job shop scheduling

KW - manufacturing tolerance

KW - optimizing manufacturing cost

KW - probablishtic process model

UR - http://www.scopus.com/inward/record.url?scp=85049167922&partnerID=8YFLogxK

U2 - 10.1016/j.promfg.2018.02.154

DO - 10.1016/j.promfg.2018.02.154

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AN - SCOPUS:85049167922

SN - 2351-9789

VL - 21

SP - 533

EP - 540

JO - Procedia Manufacturing

JF - Procedia Manufacturing

T2 - 15th Global Conference on Sustainable Manufacturing, GCSM 2017

Y2 - 25 September 2017 through 27 September 2017

ER -