• ISSN: 2010-0248 (Print)
    • Abbreviated Title: Int. J. Innov.  Manag. Technol.
    • Frequency: Quarterly
    • DOI: 10.18178/IJIMT
    • Editor-in-Chief: Prof. Jin Wang
    • Managing Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: Google Scholar, CNKI, Ulrich's Periodicals Directory,  Crossref, Electronic Journals Library.
    • E-mail: ijimt@ejournal.net
HOME > Archive > 2013 > Volume 4 Number 6 (Dec. 2013) >
IJIMT 2013 Vol.4(6): 565-569 ISSN: 2010-0248
DOI: 10.7763/IJIMT.2013.V4.462

Predictive Approach on Flexible Job Shop Scheduling Problem Considering Controllable Processing Times

Astri Yulianty and Anas Ma’ruf

Abstract— As a result of rapid developments in production technologies in recent years, job shop scheduling problem becomes more complex with presence of routing alternatives. This problem is known as flexible job shop scheduling problem (FJSP). On the other hand, as cutting tool technology also developed, time process may vary by accelerating/decelerating cutting speed. Processing time could be increased or decreased by considering some specific variables. In practice, scheduling problem is usually subject to disturbances, such as machine breakdown. The most common method in coping with machine breakdown is by using predictive approach, which put in a certain amount of idle times within the schedule for machine repair. This paper deals with three main factors: FJSP, controllable processing time and machine breakdown. Mathematical models will be used to build an initial solution that determines job assignment and processing times of the jobs. Later, this initial solution will be used to reschedule jobs by considering expected downtime for each machine and downtime probability for each operation. A number of scenario will be described to show the merits of the proposed algorithm.

Index Terms— Flexible job shop, controllable processing times, machine breakdown, predictive scheduling.

Astri Yulianty is with Department of Industrial Engineering and Management Technology in Institut Teknologi Bandung, Indonesia (e-mail: astri.yulianty@gmail.com).
Anas Ma’ruf is with Department of Industrial Engineering in Institut Teknologi Bandung, Indonesia (e-mail: maruf@ti.itb.ac.id).

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Cite: Astri Yulianty and Anas Ma’ruf, " Predictive Approach on Flexible Job Shop Scheduling Problem Considering Controllable Processing Times," International Journal of Innovation, Management and Technology vol. 4, no. 6, pp. 565-569, 2013.

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