PENGEMBANGAN ALGORITMA VARIABLE NEIGHBORHOOD SEARCH PADA LINTASAN PERAKITAN PRODUK CAMPURAN KOLABORASI MANUSIA DAN ROBOT

The electronics industry in Indonesia recently had positive growth in the first quarter of 2022. This growth is predicted to continue with the increased technology innovation in the products sold. The industry recently applied a collaborative robot (Cobot) for flexibility in responding to market con...

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Main Author: Helmy Zakaria, Muhammad
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/68358
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:68358
spelling id-itb.:683582022-09-14T09:42:21ZPENGEMBANGAN ALGORITMA VARIABLE NEIGHBORHOOD SEARCH PADA LINTASAN PERAKITAN PRODUK CAMPURAN KOLABORASI MANUSIA DAN ROBOT Helmy Zakaria, Muhammad Indonesia Final Project assembly line, collaboration of human and robot, mixed-model, metaheuristic algorithm, variable neighborhood search. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/68358 The electronics industry in Indonesia recently had positive growth in the first quarter of 2022. This growth is predicted to continue with the increased technology innovation in the products sold. The industry recently applied a collaborative robot (Cobot) for flexibility in responding to market conditions. In Indonesia, a company that has already applied cobot on assembly line is PT JVC Electronics Indonesia (JEIN) with operational cost reduced more than 80.000 USD and increased workers’ productivity and safety. As an electronic company, PT JEIN keeps improving to respond to market development by developing various products with same parent depending on consumer demand. This act needs a fast assembly line balancing planning for mixed-model type that utilizes the collaboration of humans and robots as an alternative resource. This research aims to develop a metaheuristic method Variable Neighborhood Search (VNS) for mixed-model assembly-line balancing problem using a robot, humans, and collaboration of both as alternatives of resources. This research developed the algorithm into six procedures: construction, shaking, local search, operator switching, station allocation, and move. This algorithm was experimented using the full factorial method with influential parameters are number of neighborhood and local search attempts (last one for big data group). Computation result from VNS algorithm reach an optimal solution for three data set and sub optimal solution for other five data with gap of 0,6 – 48%. The computation time for the VNS algorithm is faster than analytics method for all data. 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
description The electronics industry in Indonesia recently had positive growth in the first quarter of 2022. This growth is predicted to continue with the increased technology innovation in the products sold. The industry recently applied a collaborative robot (Cobot) for flexibility in responding to market conditions. In Indonesia, a company that has already applied cobot on assembly line is PT JVC Electronics Indonesia (JEIN) with operational cost reduced more than 80.000 USD and increased workers’ productivity and safety. As an electronic company, PT JEIN keeps improving to respond to market development by developing various products with same parent depending on consumer demand. This act needs a fast assembly line balancing planning for mixed-model type that utilizes the collaboration of humans and robots as an alternative resource. This research aims to develop a metaheuristic method Variable Neighborhood Search (VNS) for mixed-model assembly-line balancing problem using a robot, humans, and collaboration of both as alternatives of resources. This research developed the algorithm into six procedures: construction, shaking, local search, operator switching, station allocation, and move. This algorithm was experimented using the full factorial method with influential parameters are number of neighborhood and local search attempts (last one for big data group). Computation result from VNS algorithm reach an optimal solution for three data set and sub optimal solution for other five data with gap of 0,6 – 48%. The computation time for the VNS algorithm is faster than analytics method for all data.
format Final Project
author Helmy Zakaria, Muhammad
spellingShingle Helmy Zakaria, Muhammad
PENGEMBANGAN ALGORITMA VARIABLE NEIGHBORHOOD SEARCH PADA LINTASAN PERAKITAN PRODUK CAMPURAN KOLABORASI MANUSIA DAN ROBOT
author_facet Helmy Zakaria, Muhammad
author_sort Helmy Zakaria, Muhammad
title PENGEMBANGAN ALGORITMA VARIABLE NEIGHBORHOOD SEARCH PADA LINTASAN PERAKITAN PRODUK CAMPURAN KOLABORASI MANUSIA DAN ROBOT
title_short PENGEMBANGAN ALGORITMA VARIABLE NEIGHBORHOOD SEARCH PADA LINTASAN PERAKITAN PRODUK CAMPURAN KOLABORASI MANUSIA DAN ROBOT
title_full PENGEMBANGAN ALGORITMA VARIABLE NEIGHBORHOOD SEARCH PADA LINTASAN PERAKITAN PRODUK CAMPURAN KOLABORASI MANUSIA DAN ROBOT
title_fullStr PENGEMBANGAN ALGORITMA VARIABLE NEIGHBORHOOD SEARCH PADA LINTASAN PERAKITAN PRODUK CAMPURAN KOLABORASI MANUSIA DAN ROBOT
title_full_unstemmed PENGEMBANGAN ALGORITMA VARIABLE NEIGHBORHOOD SEARCH PADA LINTASAN PERAKITAN PRODUK CAMPURAN KOLABORASI MANUSIA DAN ROBOT
title_sort pengembangan algoritma variable neighborhood search pada lintasan perakitan produk campuran kolaborasi manusia dan robot
url https://digilib.itb.ac.id/gdl/view/68358
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