Author : Salem F. Lakrash
Publisher :
ISBN 13 :
Total Pages : 332 pages
Book Rating : 4.:/5 (125 download)
Book Synopsis A combined simulation heuristic approach to optimize a single-product straight assembly line by : Salem F. Lakrash
Download or read book A combined simulation heuristic approach to optimize a single-product straight assembly line written by Salem F. Lakrash and published by . This book was released on 2021 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, a single straight assembly line only for one type of product is addressed based on a real production environment. This research aims to optimize the performance of the assembly line in such a way as to minimize the number of workstations by developing a combined simulation heuristic methodology for line balancing of a single-product straight assembly line. Three months of data were collected, which is relevant to cycle time, repair station time and downtime (MTBF and MTTR), reject percentage (percentage success after the first repair, percentage success after the second repair, percentage unrepairable resulting in complete scrap out) and actual hourly throughput. Simulation models were built to mimic the existing production scenario to investigate and evaluate the assembly line's dynamic behavior under various conditions and to predict the future behavior of the system. Moreover, the Design of Experiments (DOE) was conducted to identify the problematic areas, and a regression model was built for the data set. Rockwell ARENA software, MINITAB 17 software, and MATLAB software were utilized simultaneously to proceed with the simulation processes and design of experiments. Besides, Analysis of Variance (ANOVA) was used to specify the main effects of changes on the throughput performance measures, along with linear regression to examine the relationships among output measures. In this research, a Genetic Algorithm (GA) model was developed to solve a single straight assembly line balancing problem. The proposed GA uses a hybrid method to generate the initial population and applies modified crossover and mutation operators. The proposed way of producing the initial population can increase the diversity of the population. A new method of selection was utilized to balance selective pressure and a repair strategy was used to overcome gene duplication. The fitness function was developed and consists of three terms. The first term addresses and evaluates the feasibility of the solutions; the second term of the fitness function monitors the progressive loading, and the third term fulfills the front-loading concept. The developed GA can find the optimum or near optimum solution for SALBP.