Model and algorithm for the first-level maintenance operation optimization of EMU trains

2021 ◽  
pp. 1-15
Author(s):  
Peng Zhao ◽  
Baoming Han ◽  
Dewei Li ◽  
Yawei Li
Keyword(s):  
Arrival Time ◽  
Job Shop ◽  
Utilization Efficiency ◽  
Operation Optimization ◽  
Operation Sequence ◽  
Modified Genetic Algorithm ◽  
Operation Process ◽  
Train Length ◽  
Scheduling Plan ◽  
Multiple Units

As a key operation for the daily maintenance of electric multiple units (EMU), the first-level maintenance operation directly affects the utilization efficiency of the EMU. The fixed operation sequence of EMU trains, the limitation of the track capacity and inconsistent arrival time of EMU trains give rise to such problems as extended waiting time, idle tracks and waste of maintenance capacity. To solve these problems and optimize the assignment of EMU-to-track, we propose a flexible job-shop sequence scheduling (Flexible-JSS) mode for the first-level maintenance of EMU trains, and a flexible sequence and tracks sharing (FSTS) model for the first-level maintenance at electric multiple units depot (EMUD) has also been proposed in this paper. The FSTS model is designed to shorten the latest completion time after taking into account the constraints such as the train length, track capacity, the operation sequence of all EMU trains, the operation process of a single EMU train, and the train-set scheduling plan. A modified genetic algorithm is used to solve the model. The feasibility and effectiveness of the model and algorithm are verified by a real case, and the comparison with the other two fixed job-shop sequence scheduling (Fixed-JSS) modes proves that the Flexible-JSS mode can improve the efficiency and ability of the first-level maintenance at EMUD impressively.

Selected Testing for Rapid Prototyping Technology Operation

2013 ◽  
Vol 308 ◽  
pp. 25-31 ◽  
Author(s):  
Ludmila Novakova-Marcincinova ◽  
Jozef Novak-Marcincin
Keyword(s):  
Rapid Prototyping ◽  
Material Testing ◽  
Basic Knowledge ◽  
Fused Deposition Modelling ◽  
Software System ◽  
Operation Optimization ◽  
Fused Deposition ◽  
Operation Process ◽  
Selection Of ◽  
Part Production

This paper deals with basic knowledge and problems in area of Rapid Prototyping (RP) technology operation focused on used material testing and operation optimization from economical aspects of view. It belongs to progressive methods of model creation based on geometry obtained from CAD environment with application possibilities in different industrial spheres. Chapters are focused on optimization of Rapid Prototyping preparation and operation process. There also is algorithm that leads to selection of suitable RP operation settings. Utilization of algorithm is presented on case of part production with use of UPrint device and Catalyst software, system created for utilization of Fused Deposition Modelling (FDM) technology.

The Effect of Crossover and Mutation Operators on Genetic Algorithm for Job Shop Scheduling Problem

2012 ◽  
Vol 542-543 ◽  
pp. 1251-1259
Author(s):  
Long Xu ◽  
Wen Bin Hu
Keyword(s):  
Genetic Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Benchmark Problems ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Mutation Operators ◽  
Scheduling Plan ◽  
Crossover And Mutation

Job Shop Scheduling Problem (JSSP) is a famous NP-hard problem in scheduling field. The concentration of JSSP is to find a feasible scheduling plan to figure out the earliest completion time under machine and processing sequence constraints. At present, genetic algorithm has been widely adopted in varies of operation research problems including JSSP, and good performance have been achieved. However, few work have stress the selection of varies operators when implemented for JSSP. Using benchmark problems, this paper compares the effect of crossover and mutation operators on genetic algorithm for JSSP.

Multi-Objective Optimization Algorithm for Job Shop Scheduling Problem in Discrete Manufacturing Enterprise

2015 ◽  
Vol 741 ◽  
pp. 860-864
Author(s):  
Li Lan Liu ◽  
Xue Wei Liu ◽  
Sen Wang ◽  
Wei Zhou ◽  
Gai Ping Zhao
Keyword(s):  
Production Scheduling ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Pso Algorithm ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Manufacturing Enterprise ◽  
Shop Scheduling ◽  
Discrete Manufacturing ◽  
Scheduling Plan

Job Shop scheduling should satisfy the constraints of time, order and resource. To solve this NP-Hard problem, multi-optimization for job shop scheduling problem (JSSP) in discrete manufacturing plant is researched. Objective of JSSP in discrete manufacturing enterprise was analyzed, and production scheduling optimization model was constructed with the optimization goal of minimizing the bottleneck machines’ make-span and the total products’ tardiness; Then, Particle Swarm Optimization (PSO) algorithm was used to solve this model by the process-based encoding mode; To solve the premature convergence problem of PSO, advantages of Simulated Annealing (SA) algorithm, such as better global optimization performance, was integrated into PSO algorithm and a Hybrid PSO-SA Algorithm (HPSA) was proposed and the flowchart was presented; Then, this hybrid algorithm was applied in actual production scheduling of a discrete manufacturing enterprise. Finally, comparative analysis of HPSA/SA/PSO optimal methods and actual scheduling plan was carried out, which verify the result that the HPSA is effective and superiority.

Efficiency of using electric power for traction of ED4M electric multiple units

2020 ◽  
pp. 85-89
Author(s):  
Alexander Alexeevich Baklanov ◽  
◽  
Stanislav Gennadyevich Istomin ◽  
Keyword(s):  
Power Consumption ◽  
Detailed Analysis ◽  
Electric Power ◽  
Weather Conditions ◽  
Current Time ◽  
Running Time ◽  
Motor Current ◽  
Multiple Unit ◽  
Train Length ◽  
Multiple Units

The paper presents results of 6-car and 8-car ED4M electric multiple unit rides and assessments of various factors influence on power consumption. In particular, the paper considers modes of starting and braking on example of speed-time curves and traction motor current-time curves at different starting accelerations. A detailed analysis showed at unaltered running time due to higher starting acceleration and lower starting braking speed the power consumption decreases and at lower starting acceleration and higher starting braking speed it increases. Besides, the paper considers an influence of such factors as density of population, train length, weather conditions and divergence of characteristics of motor-wheel units of motor cars.

scholarly journals Reactive Scheduling Based on Adaptive Manipulator Operations in a Job Shop Configuration with Two Machines

2021 ◽  
Vol 15 (5) ◽  
pp. 661-668
Author(s):  
Ryo Yonemoto ◽  
◽  
Haruhiko Suwa
Keyword(s):  
Machine Tools ◽  
Manufacturing Systems ◽  
Material Handling ◽  
Manufacturing System ◽  
Job Shop ◽  
Machining Processes ◽  
Operation Sequence ◽  
Machine Failure ◽  
Operation Schedule ◽  
Two Machines

Manufacturing systems are affected by uncertainties, such as machine failure or tool breakage, which result in system downtime and productivity deterioration. In machining processes, system downtime must be reduces. This study aims to establish an automated scheduling technique that flexibly responds to unforeseen events, such as machine failure, based on adaptive operations of the handling manipulator instead of an operation schedule for the machine tools. We propose an “adaptive manipulation” procedure for establishing a reactive revision policy. The reactive revision policy modifies a portion of the manipulator operation sequence, followed by the machine operation sequence. We conduct a physical scheduling simulation on a material-handling manipulator system imitating a job-shop manufacturing system. Through simulations involving machine breakdown scenarios, the applicability of the reactive revision policy based on adaptive manipulation is demonstrated.

scholarly journals Adaptive Modeling and Operation Optimization for the Cold End System of Thermal Power Units based on Mechanism and Statistical Analysis

2020 ◽  
Vol 319 ◽  
pp. 01003
Author(s):  
Wei Jin ◽  
Shaojun Ren ◽  
Yunshan Dong ◽  
Fengqi Si ◽  
Ce Wang ◽  
...  
Keyword(s):  
Cooling Tower ◽  
Thermal Power ◽  
Coupled Model ◽  
Operating Mode ◽  
Mechanism Analysis ◽  
Operating Characteristics ◽  
Operation Optimization ◽  
Actual Operating ◽  
Operation Process ◽  
Experimental Trials

The operation optimization for the cold end system is an efficient means to improve the economy of steam turbine units. To compensate for the inadequacy of the traditional mechanism analysis utilized in obtaining actual operating characteristics of the cold end system, the prediction model of the exhaust pressure was established on the basis of mechanism analysis combined with data from the operation process. An online adaptive updating strategy was introduced to guarantee the modeling accuracy. A discrete model of the cooling tower outlet water temperature (CTOWT) was constructed based on the operation data partitioned into different groups according to the pump operating mode change (POMC). Combining the above two models, the coupled model of the cold end system was therefore obtained. A model-based operation optimization system was then implemented for the cold end system in a coal-fired power plant. Experimental trials authenticate that the optimization suggestions provided by the system can effectively enhance the benefit of power generation.

Study on Job Shop Scheduling Optimization with Multi-Objective

2011 ◽  
Vol 217-218 ◽  
pp. 326-329
Author(s):  
Tao Ze ◽  
Di Liang ◽  
Zhou Qun
Keyword(s):  
Mathematical Model ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Maximum Load ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Multi Objective ◽  
Scheduling Plan ◽  
The Mathematical Model

A new multi-objective scheduling method based on the GA is proposed to the job-shop scheduling problem (JSP) constrained by machines, workers. Function objectives of the proposed method are to minimize the completion time, the maximum load of machines and the total expense of machines and workers. Firstly, the mathematical model is constructed. Then, on the basis of the mathematical model, the genetic algorithm (GA) based on Pareto is applied, and an optimal or suboptimal scheduling plan can be obtained. The optimal solutions are not unique due to the multi-objective of JSP. Finally, a scheduling example is employed to illustrate that the proposed method could solve multi-objective job shop scheduling problem effectively.

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