Abstract: Repairable items inventory system is a management tool used to incorporate all information concerning inventory levels and movements for repaired and new items. This paper presents development of an effective simulation model for managing the inventory of repairable items for a production system where production lines send their faulty items to a repair shop considering the stochastic failure behavior and repair times. The developed model imitates the process of handling the on-hand inventory of repaired items and the replenishment of the inventory of new items using Economic Order Quantity and Reorder Point ordering policy in a flexible and risk-free environment. We demonstrate the appropriateness and effectiveness of the proposed simulation model using an illustrative case problem. The developed simulation model can be used as a reliable tool for estimating a healthy on-hand inventory of new and repaired items, backordered items, and downtime due to unavailability of repaired items, and validating and examining Economic Order Quantity and Reorder Point ordering policy, which would further be compared with other ordering strategies as future work.
Abstract: This paper is concerned with the single-item
continuous review inventory system in which demand is stochastic
and discrete. The budget consumed for purchasing the ordered items
is not restricted but it incurs extra cost when exceeding specific
value. The unit purchasing price depends on the quantity ordered
under the all-units discounts cost structure. In many actual systems,
the budget as a resource which is occupied by the purchased items is
limited and the system is able to confront the resource shortage by
charging more costs. Thus, considering the resource shortage costs as
a part of system costs, especially when the amount of resource
occupied by the purchased item is influenced by quantity discounts,
is well motivated by practical concerns. In this paper, an optimization
problem is formulated for finding the optimal (r, Q) policy, when the
system is influenced by the budget limitation and a discount pricing
simultaneously. Properties of the cost function are investigated and
then an algorithm based on a one-dimensional search procedure is
proposed for finding an optimal (r, Q) policy which minimizes the
expected system costs.
Abstract: This study considers the problem of calculating safety stocks in disaster situations inventory systems that face demand uncertainties. Safety stocks are essential to make the supply chain, which is controlled by forecasts of customer needs, in response to demand uncertainties and to reach predefined goal service levels. To solve the problem of uncertainties due to the disaster situations affecting the industry sector, the concept of Emergency Safety Stock (ESS) was proposed. While there exists a huge body of literature on determining safety stock levels, this literature does not address the problem arising due to the disaster and dealing with the situations. In this paper, the problem of improving the Order Quantity Model to deal with uncertainty of demand due to disasters is managed by incorporating a new idea called ESS which is based on the probability of disaster occurrence and uses probability matrix calculated from the historical data.
Abstract: This paper explains the development of Multifunctional Barcode Inventory Management System (MBIMS) to manage inventory and stock ordering. Today, most of the retailing market is still manually record their stocks and its effectiveness is quite low. By providing MBIMS, it will bring effectiveness to retailing market in inventory management. MBIMS will not only save time in recording input, output and refilling the inventory stock, but also in calculating remaining stock and provide auto-ordering function. This system is developed through System Development Life Cycle (SDLC) and the flow and structure of the system is fully built based on requirements of a retailing market. Furthermore, this system has been developed from methodical research and study where each part of the system is vigilantly designed. Thus, MBIMS will offer a good solution to the retailing market in achieving effectiveness and efficiency in inventory management.
Abstract: We consider a single-echelon, single-item inventory
system where both demand and lead-time are stochastic. Continuous
review policy is used to control the inventory system. The objective
is to calculate the reorder point level under stochastic parameters. A
case study is presented in Neonatal Intensive Care Unit.
Abstract: This paper deals with a periodic-review substitutable
inventory system for a finite and an infinite number of periods. Here
an upward substitution structure, a substitution of a more costly item
by a less costly one, is assumed, with two products. At the beginning
of each period, a stochastic demand comes for the first item only,
which is quality-wise better and hence costlier. Whenever an arriving
demand finds zero inventory of this product, a fraction of unsatisfied
customers goes for its substitutable second item. An optimal ordering
policy has been derived for each period. The results are illustrated
with numerical examples. A sensitivity analysis has been done to
examine how sensitive the optimal solution and the maximum profit
are to the values of the discount factor, when there is a large number
of periods.
Abstract: In recent years, environment regulation forcing
manufactures to consider recovery activity of end-of- life products
and/or return products for refurbishing, recycling,
remanufacturing/repair and disposal in supply chain management. In
this paper, a mathematical model is formulated for single product
production-inventory system considering remanufacturing/reuse of
return products and rate of return products follows a demand like
function, dependent on purchasing price and acceptance quality level.
It is useful in decision making to determine whether to go for
remanufacturing or disposal of returned products along with newly
produced products to satisfy a stationary demand. In addition, a
modified genetic algorithm approach is proposed, inspired by particle
swarm optimization method. Numerical analysis of the case study is
carried out to validate the model.