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Last Time Buy and repair decisions for fast moving parts

机译:上次购买和维修快速移动零件的决定

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Spare part availability is essential for advanced capital goods with a long service period. Sourcing becomes challenging once the production of spare parts ceases, while the remaining service period is still long. In this paper, we focus on fast moving parts with repair of failed parts as an alternative supply option. We proceed from the methodology of Behfard et al. (2015) for slow movers, which assumes discrete demand distributions and therefore leads to excessive computation times for fast movers. We find that the use of continuous demand distributions requires significant modifications, both for the approximation of the performance indicators and for the optimization of the repair policy. We develop accurate heuristics to find the near-optimal Last Time Buy (LTB) quantity and the repair policy that we apply for two control policies: pull return - push repair, and push return pull repair. We show that pull return - push repair is better to follow if return lead times are short and return costs are low. For long return lead times, we find that when the return cost exceeds 35%-40% of the pares value, push return- pull repair becomes more cost efficient. We also show that for relatively high demand of spare parts over the planning period (300 for a 10 years planning period) the continuous model is a good approximation for the discrete model of Behfard et al. (2015). In addition, the computation time of our method is much lower then.
机译:备件可用性对于具有较长服务期限的高级资本货物至关重要。一旦零件的生产停止,采购就会变得充满挑战,而剩余的服务期限仍然很长。在本文中,我们将重点放在快速移动的零件上,将出现故障的零件作为替代供应选项进行维修。我们从Behfard等人的方法论出发。 (2015年)对于慢速移动者,它假设离散的需求分布,因此导致快速移动者的计算时间过长。我们发现使用连续需求分配需要进行重大修改,无论是为了接近绩效指标还是为了优化维修策略。我们开发精确的试探法,以找到接近最佳的上次购买(LTB)数量以及我们申请两个控制策略的维修策略:拉回修-推修和推回修修。我们证明,如果退货提前期短且退货成本低,则更好地遵循拉式退货-推式修理。对于较长的退货交货时间,我们发现当退货成本超过同价的35%-40%时,推回提货维修的成本效益更高。我们还表明,对于计划期内相对较高的备件需求(在10年的计划期内> 300),连续模型对于Behfard等人的离散模型是很好的近似。 (2015)。此外,我们的方法的计算时间要短得多。

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