دانلود مقاله ISI انگلیسی شماره 110222
ترجمه فارسی عنوان مقاله

آخرین زمان خرید و تعمیرات تصمیم گیری برای قطعات سریع حرکت می کند

عنوان انگلیسی
Last Time Buy and repair decisions for fast moving parts
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
110222 2018 38 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : International Journal of Production Economics, Volume 197, March 2018, Pages 158-173

ترجمه کلمات کلیدی
فهرست، قطعات یدکی، خرید آخرین زمان، تعمیر، تقاضای مداوم،
کلمات کلیدی انگلیسی
Inventory; Spare parts; Last Time Buy; Repair; Continuous demand;
پیش نمایش مقاله
پیش نمایش مقاله  آخرین زمان خرید و تعمیرات تصمیم گیری برای قطعات سریع حرکت می کند

چکیده انگلیسی

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 part's 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.