Balancing mixed-model assembly line to reduce work overload in a multi-level production system

Generating the optimal production schedule for an assembly line, which will balance the workload at all the production stages, is a difficult task considering a variety of practical constraints. Varying customer demand is an important factor to be considered when designing an assembly line. In order to respond to varying customer demand, many companies are attempting to make their production system more flexible/agile or adaptable to change. Due to the volatile nature of market, companies cannot afford to manufacture same type of product for long period of time and neither can maintain high inventory level; to tackle this problem we propose a new approach of balancing mixed-model assembly line in a multi-level production system. The emphasis is on incorporating the effect of set-up times of lower production levels on the final assembly schedule. This will facilitate stabilized workload among and across the stations and effectively balance the production schedule at all production stages. As a result, the proposed model assures that workloads are balanced and setup times are reduced to such an extent that WIP and overall inventories are kept to a low level

Mixed-model assembly line sequencing using beam search

In today's manufacturing environments, companies have to produce a large variety of products in small quantities on a single assembly line. In this paper, we use a beam search (BS) approach to solve the model-sequencing problem of mixed-model assembly lines (MMALs). Specifically, we develop six BS algorithms for part-usage variation and load-leveling performance measures. The results of computational experiments indicate that the proposed BS methods are competitive with the well-known heuristics in the literature. A comprehensive bibliography is also provided