PENGEMBANGAN ALGORITMA ANT COLONY OPTIMIZATION UNTUK PERANCANGAN LINTAS PERAKITAN DENGAN ALTERNATIF URUTAN PERAKITAN DAN PROSES PERAKITANNYA MENGGUNAKAN KOLABORASI MANUSIA-ROBOT

• Main Author: Naurah Triwidyatari, Dinda
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/68398
• Institution: Institut Teknologi Bandung

Industry 4.0 shows a new revolution on industry and pushes industry to change for better. One of the innovations in industry is the existence of collaborative robot (cobot). PT JVC Electronics Indonesia is one of the companies which use cobot and could save up to USD 80.000. This development also drives a faster change on customer demand, leading to the creation of alternative task orders in an assembly line. Therefore, the industry needs to solve an alternative task (subgraphs) assembly line balancing problem using human-robot collaboration (ASALBP- HRC). One of the ways to solve ASALBP-HRC in a faster way is by using metaheuristic method. This research aims to develop an Ant Colony Optimization (ACO) algorithm to solve ASALBP- HRC to minimize takt time. This algorithm consists of two main procedures: a construction algorithm and an improvement algorithm. ACO algorithm uses several ants in each iteration to search for the solution. Each ant will leave pheromone trail used for other ants in successive iterations. This research also does parameter tuning using 1?4 fractional factorial design to get parameters significantly affecting the solution. Based on the computational result on nine data sets of different tasks, the ACO algorithm shows to get a feasible solution faster than analytical method with an average of time gap by 96,15% also average of objective value gap by 20,40%. Also, it shows that the number of iterations and the colony size are the parameters that affects the performance of ACO algorithm.