Abstract
In the traditional production lines such as assembly lines, each worker is usually assigned to a particular fixed position, and the speed of performing the task decreases until the worker masters the assigned work. However, when an imbalance in the speeds of the workers exists, any given worker can delay the overall work on the production line, and the production rate of the particular line will also decrease. To avoid this problem, the “Self-Balancing Production Line” was introduced. In this type of production line, each worker is assigned work dynamically so they can keep the production line balanced while satisfying the specific conditions. A previous paper studying worker learning has been published. When a worker learns, the speed of the worker can be increased. In that paper, the authors analyzed the conditions with and without passing and claimed that if passing is allowed, self-balancing of a production line can be achieved. However, even if the initial sequence is slowest to fastest (this is the best sequence for self-balance in the previous paper) and if passing is allowed, much more time is required to balance some conditions of speed and degree of learning (we call this the learning rate). Therefore, a new policy for rearranging workers that changes the sequence before passing should be considered for rapid balance of the production line. In this paper, the policy for rearranging workers that changes the sequence being learned is proposed, and to verify the policy, numerical experiments are performed under various conditions of speed and learning rate.
Highlights
In a traditional assembly line, each worker is typically given a fixed assignment, and each worker iterates the assigned work continuously under the traditional assembly line balancing system
When a speed imbalance exists in this type of line, the slowest worker will delay the overall work, and the production rate of the production line will decrease
We propose the following four policies for selfbalancing a production line with learning
Summary
In a traditional assembly line, each worker is typically given a fixed assignment, and each worker iterates the assigned work continuously under the traditional assembly line balancing system. Because faster workers are assigned more work in processing a task and vice versa, balance can be maintained For this line with a constant working speed, the maximum production rate can be achieved if workers are sequenced from slowest to fastest [2]. Nembhard [11] considers individual learning and forgetting Under these conditions, he proposed a heuristic approach for assigning workers, and using ANOVA (ANalysis Of VAriance), he analyzed the effect of this approach. From previous papers, even if the initial sequence is arbitrary and passing is allowed, more much time is required to balance production for some conditions of speed and degree of learning (we call this the learning rate).
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