Abstract

APPLICATION OF SCHEDULING PREVENTIVE MAINTENANCE PROCESSES USING THE GENETIC ALGORITHM OF THE SEWING LINE / CASE STUDY IN LABORATORY 7 OF THE GENERAL COMPANY FOR TEXTILE AND LEATHER INDUSTRIES

Suha Jamal Mawlood AL- Barazanchi, Professor Dr. Yousef Hacheam Sultan Al-Taie

Volume: 9 Issue: 3 2019

Abstract:

The study aims to achieve several objectives, including follow-up scientific developments and transformations in modern concepts of scheduling operations for the purpose of identifying the ways of switching to the entrances of artificial intelligence, clarifying the mechanism of scheduling operations to benefit from the advantages of systems and to achieve the maximum savings in time and cost of machines. Higher efficiency, using the genetic algorithm, which allows to determine the optimal preventive maintenance time and reduce the total maintenance costs, which in turn enable the workers on these machines to control the holidays in which, and from the dilemma of thought And the field problem, one can ask the question of how to achieve the scheduling of maintenance operations using the genetic algorithm?In the light of this, the importance of the study and its objectives were determined. The analytical descriptive approach was adopted in the theoretical framework. In the practical framework, the quantitative approach was adopted. The quantitative indicators of the sewing line were used and the results were compared between the preventive maintenance scheduling method and the genetic algorithm method. Data using indicators. The results showed that the use of the genetic algorithm helped to reduce the effort, time and cost. It is possible to reach the optimal solution with very few steps when using the genetic algorithm as a random search algorithm. The most prominent recommendations were the adoption of laboratory management on the genetic algorithm in estimating the optimal preventive maintenance period The method leads to reducing costs and increasing the efficiency of machines by determining the optimal preventive maintenance time for these machines, and the completion of the study of some of the proposals, the most prominent of which is to conduct more research on the scheduling of processes of technology systems aggregates and integration with Genetic algorithm and in different industrial and service sectors.

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