A reallocation-based heuristic to solve a machine loading problem with material handling constraint in a flexible manufacturing system

2006 ◽  
Vol 44 (3) ◽  
pp. 569-588 ◽  
Author(s):  
M. Goswami ◽  
M. K. Tiwari
Keyword(s):  
Flexible Manufacturing ◽  
Material Handling ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Machine Loading ◽  
Loading Problem

An Improved Particle Swarm Optimization Approach for Solving Machine Loading Problem in Flexible Manufacturing System

2015 ◽  
Vol 14 (03) ◽  
pp. 167-187 ◽  
Author(s):  
Ruchir Santuka ◽  
Siba Sankar Mahapatra ◽  
Prasant Ranjan Dhal ◽  
Antaryami Mishra
Keyword(s):  
Particle Swarm Optimization ◽  
Flexible Manufacturing ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Particle Swarm ◽  
Computational Effort ◽  
Swarm Optimization ◽  
Machine Loading ◽  
Loading Problem ◽  
Chaotic Numbers

Machine loading problem in flexible manufacturing system is considered as a vital pre-release decision. Loading problem is concerned with assignment of necessary operations of the selected jobs to various machines in an optimal manner to minimize system unbalance under technological constraints of limited tool slots and operation time. Such a problem is combinatorial in nature and found to be NP-hard; thus, finding the exact solutions is computationally intractable and becomes impractical as the problem size increases. To alleviate above limitations, a meta-heuristic approach based on particle swarm optimization (PSO) has been proposed in this paper to solve the machine loading problem. Mutation, a commonly used operator in genetic algorithm, has been introduced in PSO so that trapping of solutions at local minima or premature convergence can be avoided. Logistic mapping is used to generate chaotic numbers in this paper. Use of chaotic numbers makes the algorithm converge fast toward global optimum and hence reduce computational effort further. Twenty benchmark problems available in open literature have been solved using the proposed heuristic. Comparison between the results obtained by the proposed heuristic and the existing methods show that the results obtained are encouraging at significantly less computational effort.

The Study on Production Performances of Part Transporter in Flexible Manufacturing System by Using Simulation Method

2012 ◽  
Vol 576 ◽  
pp. 714-717
Author(s):  
Mohammad Iqbal ◽  
Muhammad Ridwan Andi Purnomo ◽  
Muhammad Ammar Bin Mohd Imra ◽  
Mohamed Konneh ◽  
A.N. Mustafizul Karim
Keyword(s):  
Waiting Time ◽  
Flexible Manufacturing ◽  
Material Handling ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Arrival Rate ◽  
Simulation Method ◽  
Simulation Software ◽  
Average Waiting Time ◽  
Processing Times

Material handling is one of major components in Flexible Manufacturing System (FMS). Any improvement of material handling capability is to affect the performance of the whole system. This paper discusses the simulation study on the effect of part arrival rate and dispatching rules to the average waiting time and production rate of the FMS. The facilities of the system were modeled into simulation environment by using Arena Simulation Software. The production parameters such as machine processing times, part transportation speed and type of products were put into the model to represent the behaviors of the real system. Two rules have been considered in the study, i. e. first come first served (FCFS), and shortest processing time (SPT). Average waiting time and productivity were taken into account as performance measures of the system. The result of the study showed that SPT rule gives shorter average waiting time and higher productivity. Based on this result, the SPT rules would be used to control part transporter in order to have a better performance of the FMS.

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