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High Performance Model for Handling Machine Breakdown in Identical Parallel Machines

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2020
Onwuachu Uzochukwu C., Ugwu C., Williams Edem

Onwuachu Uzochukwu C., Ugwu C. and Williams Edem. High Performance Model for Handling Machine Breakdown in Identical Parallel Machines. International Journal of Computer Applications 177(48):11-19, March 2020. BibTeX

	author = {Onwuachu Uzochukwu C. and Ugwu C. and Williams Edem},
	title = {High Performance Model for Handling Machine Breakdown in Identical Parallel Machines},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2020},
	volume = {177},
	number = {48},
	month = {Mar},
	year = {2020},
	issn = {0975-8887},
	pages = {11-19},
	numpages = {9},
	url = {},
	doi = {10.5120/ijca2020919965},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Machine breakdown is an issue that cannot be overlooked when considering the performance of any scheduling model. This issue has resulted in the inability to meet up with the job due date and also increases job completion time among identical parallel machines. Therefore, an efficient job scheduling model will take care of machine failure issues to obtain a good job schedule. This paper developed an efficient scheduling model that is robust, to handle the issues of machine failure and minimize the total completion time for job execution in identical parallel machines. The developed model adopted fuzzy logic technique in developing a job dispatcher for the identical parallel machines. The job dispatcher was used in determining the available machine and the failed machine before dispatching jobs to the individual parallel machines. The model was tested with fifteen identical parallel machines used for printing jobs in the printing press. The parameter used in analyzing this model includes the machine load balancing and machine utilization. The result from this model was compared with other existing model like first come first serve scheduling model and genetic scheduling model. The lowest machine utilization recorded from the experiment conducted using first come first serve scheduling model, genetic scheduling model and the developed scheduling model was 83.46856%, 89.57643% and 98.2949% respectively, which shows that the new model achieved better load balancing and efficient machine utilization among the identical parallel machines.


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Job scheduling model, machine breakdown, machine utilization, identical parallel machines and load balancing.