AN OPTIMIZATION OF ASSEMBLY SEQUENCE USING GENETIC ALGORITHM TO MINIMIZE NUMBER OF REORIENTATION AND EQUIPMENT CHANGES
PT ACP is a kitchenware manufacturing company. Before implementing these solutions, the company planned to standardize and optimize its existing processes to standardize assembly sequences. Currently, PT ACP is planning to standardize some of its products and implement an assembly line. Assembly seq...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/60894 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | PT ACP is a kitchenware manufacturing company. Before implementing these solutions, the company planned to standardize and optimize its existing processes to standardize assembly sequences. Currently, PT ACP is planning to standardize some of its products and implement an assembly line. Assembly sequences planning initiative is prioritized for the company’s flagship product, named Deep Fryer (30 components).
The assembly sequence planning problem is an NP-Hard combinatoric problem usually solved by using the Genetic Algorithm by reducing the number of reorientations and equipment changes. In this research, the Genetic Algorithm is used by exploring the feasible solution space. The operators generate a set of feasible initial solutions, process feasible solutions, and result in an optimal solution. Genetic Algorithm parameters in the assembly sequence planning problem do not have a specific method of determination. The Taguchi Method is used to determine the parameters of the Genetic Algorithm.
The assembly sequence for Deep Fryer reduced the reorientations and equipment changes time by 14.4% (5.74 minutes from 6.74 minutes) and reducing the total assembly time by 3.3% (29 minutes from 30 minutes).
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