Purpose
This paper aims to explore methods of defining ejecting zones (EZs) used in automatic picking systems (APSs), particularly in A-frame APSs. An A-frame APS automatically ejects products onto a ...conveyor, which then brings the products to their destination. EZs are moving zones on a conveyor, and each EZ corresponds to one picking order. Products are ejected as a zone passes channels in which the products are stored.
Design/methodology/approach
First, three EZ types are defined, and their operations are explained. Second, picking orders are analyzed and categorized by considering the structure and the picking mechanism of an A-frame APS. In addition, picking-order instances reflecting actual data are randomly generated according to each category. Finally, the performance of the EZs is evaluated using the picking-order instances and computer simulations.
Findings
The results from the computer simulations suggest the EZ types suitable for use with various picking order types considering order fulfilment speed and energy usage.
Research limitations/implications
In this paper, the authors only adopt a triangular distribution which is considered most practical distribution in the industry.
Practical implications
It is believed that these results can provide managers and operators with useful guides to facilitate the effective operation of an A-frame APS. The provided ideas have been implemented at the pharmaceutical warehouse of the largest logistics company in Korea.
Social implications
The result shows that the proposed idea could save energy consumption and the APS have potential to save labor involvement in picking.
Originality/value
It is essential to define the EZs when operating an A-frame APS efficiently, but there is almost no research in this area. This paper focuses on defining EZs, as well as methods to utilize these zones.
The design of component assembly lines in Printed Circuit Board (PCB) manufacturing environments is a challenging problem faced by many firms in the electronics industry. The main design approaches ...to such component assembly lines are the Mini-Line, Flexible Flow Line, and Hybrid Line designs. In this paper, we discuss the operational trade-offs associated with these design alternatives and present a mathematical programming framework that captures relevant system design issues. Each of the design alternatives can be viewed as a special case of the stated mathematical programming model. We develop effective algorithms to solve these mathematical programs. We have used the framework in a specific PCB manufacturing environment to advise managers on the best configuration of their lines. The models were used as sensitivity analysis tools. The results of our computational experiments, combined with qualitative comparisons of different design approaches developed by a crossfunctional team (engineers, manufacturing and product managers), have led to the development of a set of managerial guidelines for the selection of the design plan for component assembly lines in the studied environment.
We consider the problem of resequencing a prearranged set of jobs on a moving assembly line with the objective of minimizing changeover costs. A changeover cost is incurred whenever two consecutive ...jobs do not share the same feature. Features are assigned from a set of job-specific feasible features. Resequencing is limited by the availability of offline buffers. The problem is motivated by a vehicle resequencing and painting problem at a major U.S. automotive manufacturer. We develop a model for solving the joint resequencing and feature assignment problem and an efficient solution procedure for simultaneously determining optimal feature assignments and vehicle sequences. We show that our solution approach is amenable to implementation in environments where a solution must be obtained within tight time constraints. We also show that the effect of offline buffers is of the diminishing kind with most of the benefits achieved with very few buffers. This means that limited resequencing flexibility is generally sufficient. Furthermore, we show that the value of resequencing is sensitive to the feature density matrix, with resequencing having a significant impact on cost only when density is in the middle range.
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