Flexible Machine Allocation and Buffer Optimization in a Serial Production Line  

Oleh:

Sari, Yosephine Vina ; Jang, Young Jae ; Hwang, Illhoe

Jenis: Article from Proceeding
Dalam koleksi: The 14th Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS), 3-6 December 2013 Cebu, Philippines, page 1-10.
Topik: Production Lines; Machine Allocation; Buffer Optimization; Genetic Algorithm; Particle Swarm Optimization
Fulltext: 1250.pdf (599.65KB)

Isi artikel

In this paper, we propose an optimization model to achieve the maximum production rate by allocating the machine sequence as well as the buffer sizes in the line. Generally, the buffer has been used for production rate maximization in a serial production line. The research of Buffer Optimization has been carried on for years to determine buffer size within the production line. Inspired by the actual manufacturing process of LCD Panel Glass Manufacturing, we introduce Flexible Machine Allocation as a new optimization approach for better production rates on a serial production line. It was observed that the involved flexible machines need to be sequenced within processes for different product engineering requirement. The optimization model works by changing the sequence of the flexible machines (i.e. Machine Allocation); it is combined with the Buffer Optimization problem for each selected Machine’s sequence to obtain the progressive optimum result from both methods at the same time. The model assumes that a serial production line consists of flexible-but-unreliable machines and identical processing time with finite buffers between machines. The optimization problem is challenged in that the machine sequence problem has possible sequence domain. Therefore, we propose two different algorithms: genetic algorithm and particle swarm optimization. The proposed algorithm utilizes the Markovian-based-Decomposition-Method to evaluate the production rate of each Buffer Optimization iteration; and Heuristic approach for each Buffer Optimization. Numerical examples are presented and possible applications in the real manufacturing system are discussed

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