Research on Preventative Maintenance of Key Equipment in Discrete Manufacturing Enterprise MES

2011 ◽  
Vol 314-316 ◽  
pp. 2158-2161
Author(s):  
Hai Qing Li
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Failure Probability ◽  
Preventive Maintenance ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Time Estimation ◽  
Utilization Rate ◽  
Shop Scheduling ◽  
Discrete Manufacturing

This paper presents preventive maintenance based condition of key equipments in MES and management of job shop scheduling. A comprehensive mathematical model between multi-key-equipments preventive maintenance and job shop scheduling is offered. Assuming key equipment’s failure probability obeys the Weibull distribution and unifying the time estimation and preventive maintenance of the key equipments’ failure and decision–making of job shop scheduling, the goal of achieving multi-key-equipments’ max utilization rate is developed.

Study on Scheduling Optimization for Flexible Job Shop

2010 ◽  
Vol 26-28 ◽  
pp. 821-825 ◽  
Author(s):  
Xiao Xia Liu ◽  
Chun Bo Liu ◽  
Ze Tao
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Hybrid Genetic Algorithm ◽  
Utilization Rate ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Multi Objective ◽  
Pareto Ranking

A hybrid genetic algorithm based on Pareto was proposed and applied to flexible job shop scheduling problem (FJSP) with multi-objective, and the multi-objective FJSP optimization model was built, where the make-span and the machine utilization rate were concerned. The algorithm embeds Pareto ranking strategy into Pareto competition method. The operation-based encoding and an active scheduling decoding method are employed. In order to promote solution diversity, the niche technology and many kinds of crossover operations are used. Pareto filter saves the optimum individual occurring in the course of evolution, which avoids losing the optimum solutions. Three simulation experiments are carried out to illustrate that the proposed method could solve multi-objective job shop scheduling problem effectively.

scholarly journals An approach to the optimal timber transport scheduling

2020 ◽  
Vol 164 ◽  
pp. 03019 ◽  
Author(s):  
Anton Shabaev ◽  
Anton Sokolov ◽  
Alexander Urban ◽  
Dmitry Pyatin
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Hybrid Algorithm ◽  
Decomposition Method ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Real Data ◽  
Shop Scheduling ◽  
Wood Harvesting ◽  
Timber Transport

An approach to the optimal timber transport scheduling is described in the paper. A description of this problem is given, a multi-criteria mathematical model is created. It is noted that the problem belongs to the class of General vehicle routing problems (GVRP) associated with the job-shop scheduling. A hybrid algorithm for solving this problem based on the decomposition method using the simplex method and the genetic algorithm is developed. Testing of the proposed approach using real data from wood harvesting enterprises showed its effectiveness. The algorithm was implemented in “Opti-Wood” decision support system for wood harvesting planning and management, developed by Opti-Soft company (Russia).

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