DEVELOPMENT OF GENETIC ALGORITHM FOR ASSEMBLY LINE BALANCING WITH HUMAN-ROBOT COLLABORATION

Collaborative robot (cobot) is a new innovative robot designed to work side by side with humans and considered human safety aspects. The implementation of cobots in the industry is increasing in Indonesia for various production applications. Research on the Assembly Line Balancing Problem Human-Robo...

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Main Author: Novita Sitorus, Jessica
Format: Final Project
Language:Indonesia
Subjects:
Online Access:https://digilib.itb.ac.id/gdl/view/79330
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:79330
spelling id-itb.:793302023-12-22T16:10:13ZDEVELOPMENT OF GENETIC ALGORITHM FOR ASSEMBLY LINE BALANCING WITH HUMAN-ROBOT COLLABORATION Novita Sitorus, Jessica Teknik (Rekayasa, enjinering dan kegiatan berkaitan) Indonesia Final Project genetic algorithm, assembly line balancing, human-robot collaboration INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/79330 Collaborative robot (cobot) is a new innovative robot designed to work side by side with humans and considered human safety aspects. The implementation of cobots in the industry is increasing in Indonesia for various production applications. Research on the Assembly Line Balancing Problem Human-Robot Collaboration (ALBP-HRC) has been conducted. The study proposed an analytical model. The weakness of the analytical model is the long computational time to find an optimal solution for data with a total of 35 and 45 tasks. Therefore, the analytical method is viable for small cases only. Thus, this research proposes a metaheuristic method to overcome previous research limitations. This research proposes the genetic algorithm as the metaheuristic method. In general, the algorithm contains two procedures: solution construction and solution improvement. Developments are in the area of generating feasible solutions, crossover, and mutation for ALBP-HRC cases. The proposed algorithm is translated to the Python programming language to execute the solutions. Based on the results, the proposed algorithm, in several cases, can match the optimal solution. Overall, the proposed algorithm achieved better solutions with an average solution gap of 13%. The computation time is faster, with an average time gap of 75%. The experimental designs also show that population and generation parameters significantly affect the performance of the genetic algorithm in finding solutions. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
topic Teknik (Rekayasa, enjinering dan kegiatan berkaitan)
spellingShingle Teknik (Rekayasa, enjinering dan kegiatan berkaitan)
Novita Sitorus, Jessica
DEVELOPMENT OF GENETIC ALGORITHM FOR ASSEMBLY LINE BALANCING WITH HUMAN-ROBOT COLLABORATION
description Collaborative robot (cobot) is a new innovative robot designed to work side by side with humans and considered human safety aspects. The implementation of cobots in the industry is increasing in Indonesia for various production applications. Research on the Assembly Line Balancing Problem Human-Robot Collaboration (ALBP-HRC) has been conducted. The study proposed an analytical model. The weakness of the analytical model is the long computational time to find an optimal solution for data with a total of 35 and 45 tasks. Therefore, the analytical method is viable for small cases only. Thus, this research proposes a metaheuristic method to overcome previous research limitations. This research proposes the genetic algorithm as the metaheuristic method. In general, the algorithm contains two procedures: solution construction and solution improvement. Developments are in the area of generating feasible solutions, crossover, and mutation for ALBP-HRC cases. The proposed algorithm is translated to the Python programming language to execute the solutions. Based on the results, the proposed algorithm, in several cases, can match the optimal solution. Overall, the proposed algorithm achieved better solutions with an average solution gap of 13%. The computation time is faster, with an average time gap of 75%. The experimental designs also show that population and generation parameters significantly affect the performance of the genetic algorithm in finding solutions.
format Final Project
author Novita Sitorus, Jessica
author_facet Novita Sitorus, Jessica
author_sort Novita Sitorus, Jessica
title DEVELOPMENT OF GENETIC ALGORITHM FOR ASSEMBLY LINE BALANCING WITH HUMAN-ROBOT COLLABORATION
title_short DEVELOPMENT OF GENETIC ALGORITHM FOR ASSEMBLY LINE BALANCING WITH HUMAN-ROBOT COLLABORATION
title_full DEVELOPMENT OF GENETIC ALGORITHM FOR ASSEMBLY LINE BALANCING WITH HUMAN-ROBOT COLLABORATION
title_fullStr DEVELOPMENT OF GENETIC ALGORITHM FOR ASSEMBLY LINE BALANCING WITH HUMAN-ROBOT COLLABORATION
title_full_unstemmed DEVELOPMENT OF GENETIC ALGORITHM FOR ASSEMBLY LINE BALANCING WITH HUMAN-ROBOT COLLABORATION
title_sort development of genetic algorithm for assembly line balancing with human-robot collaboration
url https://digilib.itb.ac.id/gdl/view/79330
_version_ 1822008849379360768