AbstrakAdanya pola demand dan lead time yang bervariasi mengakibatkan pentingnya pengelolaan suku cadang secara tepat. Penentuan kuantitas dan reorder point yang tepat sangat berpengaruh terhadap besarnya biaya persediaan suku cadang.Model biaya persediaan dikembangkan dengan mempertimbangkan ketidakpastian demand. Pada penelitian ini, demand dipengaruhi adanya kerusakan pada peralatan. Model awal biaya persediaan didekati dengan distribusi gamma. Hasil pengembangan model dengan distribusi gamma menunjukkan bahwa reorder point persediaan suku cadang dipengaruhi nilai safety stock persediaan. Nilai safety stock bergantung pada ekspektasi permintaan selama lead time, sebesar parameter dan .Penelitian ini juga menunjukkan bahwa model persediaan berdistribusi gamma dapat digunakan untuk mencari kuantitas optimal melalui biaya ekspektasi kekurangan persediaan. Kata kunci: Kuantitas Optimal, Reorder Point, Distribusi Gamma PendahuluanDemand suku cadang berbeda dengan demand material pada umumnya, biasanya dipengaruhi adanya kerusakan peralatan. Waktu yang dibutuhkan untuk pengadaan suku cadang mulai dari pemesanan hingga kedatangan disebut lead time. Waktu yang dibutuhkan dalam penyediaan suku cadang bisa sangat cepat atau sebaliknya mengalami kelambatan. Persediaan suku cadang menjadi masalah yang kompleks, terutama karena adanya pola permintaan yang intermittent atau lumpy [1], [8]. Pada permintaan intermittent adalah permintaan bersifat acak dengan beberapa periode tanpa permintaan. Sedangkan permintaan lumpy dalam beberapa periode tidak terdapat permintaan dan bersifat acak dalam jangka waktu yang panjang.

No abstract

Clothes are products that follow short-life fashion and market demand. Products with a short lifetime occur due to technological developments and/or changes in market tastes. The clothing industry is one of the industries that has a short and obsolete sales period in stages. The excess number of products that accumulate in the warehouse due to obsolescence can cause the company to get a profit that is not optimal. One strategy to increase demand for the product is to apply discounts. There are two types of discounts used, namely a single discount and multiple discounts. The demand function of inventory model is considered analogous to the logistic growth model. The results show profit is maximized to get optimal order quantity and optimal discount price.

Inventory strategies are very necessary for supporting the production process. The strategy in the form of a model is proposed for redundant allocation of critical parts of a server system for minimizing additional costs. This model considers the occurrence of failure using downtime limits as the downtime on the server should be minimal. The rapid replacement of spare parts can be achieved through an onsite inventory or a redundant configuration. Furthermore, fast delivery would be an alternative when there is no inventory or redundancy. We considered four scenarios including a combination of stock, installation of redundant components, and fast deliveries. The model was solved using the Lagrangian relaxation method. No downtime in scenarios using redundancy resulted in a stable total cost over the last period, even though the penalty increased. The redundant module only had an additional cost in the initial period, so if the penalty value increased, there was a switching of scenario selection in the third or fourth scenario.

We study a multi echelon spare parts inventory system which consider some important factors, among others; maintenance of the equipment, pricing, lifetime and distance to the central warehouse. But it turns out a position local warehouse to another warehouse interesting to note as well. Effect of space is called spatial dependence in deciding the allocation of spare parts inventories in multi-echelon systems. Availability of critical spare parts to the essential equipment needed for the equipment can perform its function at a specific time period. Some of the factors that greatly affect the supply of critical spare parts can be prioritized. This 784 Valeriana Lukitosari et al. paper's accommodate spatial dependence in the decision to stock spare parts with spatial regression models. The result is information regarding the important factors in deciding the inventory of spare parts in a multi-echelon system.