Development of inventory policy for spare parts subject to age replacement has previously been studied using (s, S) type ordering policies. When age replacement causes a large percentage of spare part demand to result from scheduled replacement rather than random failure, this policy fails to take advantage of the presumably known schedule of planned replacement times. This paper uses simulation analysis to characterise the conditions under which a dynamic ordering policy such as Wagner-Whitin produces significant cost reductions relative to (s, S), by virtue of taking the planned replacement times into account. A modification to the basic Wagner-Whitin method is introduced to address the issue of overly frequent, small order quantities when the demand pattern is dominated by random failures. Simulation results demonstrate the Wagner-Whitin algorithm significantly outperforms the (s, S) policy when a sufficient percentage of demand is due to scheduled replacement. The modified Wagner-Whitin policy outperforms the (s, S) policy under any mixture of planned replacement and random failure spare parts demand.
Two different cases of the probabilistic scheduling period inventory model for deteriorating items are discussed. The deterioration rate follows the Weibull distribution with two-parameter with varying and constrained expected deteriorating cost, when the demand during any scheduling period is a random variable and without shortage. The first case when the total cost components are considered to be crisp values, and the other case when the costs are considered as trapezoidal fuzzy numbers. Also, some special cases are deduced. To illustrate the proposed model in the crisp case and the fuzzy case, a numerical example was added.
This paper details the design and development of an RFID-based prototype inventory system. The system comes with a user-friendly graphical user interface and is built to track and monitor the movement of items, and maintain detailed (timestamped) audit logs on item removal, replenishment, and every user action. While authorised access to the store is achieved through RFID tags, this system uses an automatic servo motor-based locking mechanism to secure the items in the inventory store. The system is configured to identify and authenticate two user profiles - administrator and end user. The administrator (in charge of the inventory) typically has permissions to monitor and update the inventory, while the end user is only able to view the contents of the inventory through the web GUI, and place/replace items in the store. This system has been developed to be scalable to suit inventory applications across business entities, educational institutions such as colleges and schools and even homes. This RFID-based inventory system comprises mainly of an inventory store that has RFID tagged items/goods, and an RFID reader that tracks them.
Here, a two-echelon supply chain inventory problem consisting of a vendor and a buyer is considered for a deteriorating item. In the system, the buyer receives an opportunity of trade credit from t...
The moral hazard problem plagues the start-ups and even mature enterprises when they incorporate venture capital to pursue business upgrade or expansion. Especially in the value chain where the venture capitalist can synergise with the entrepreneur to contribute to the firm value. This paper proposes a game theoretic approach to solve the entrepreneur's optimisation problem in a venture capital financing scheme and generalises the formulation without a specific revenue function. Furthermore, this study generates managerial insights for venture capital market and relevant sustainable supply chain management. The key results also show that the complementarity effect can incentivise both the entrepreneur and the venture capitalist to exert more effort, thus achieving larger enterprise value when it is relatively significant, and the inefficiency caused by the allocation of equity share could be mitigated.
Inventory repositioning or pooling to efficiently align demand and supply is a strategic tool widely used in the car rental industry. This technique produces optimal results when demand is negatively correlated between locations within a pool. In practice, effective pricing decisions are expected to complement capacity adjustment, so activities of inventory repositioning can be minimised. Although matching demand increases profit, inventory repositioning unavoidably increases cost; thus, this investigation explores a different aspect of inventory repositioning, namely, effectiveness. The study utilises live pricing data from the US car rental industry, an industry where price is a major differentiator in the market, to detect whether any unwarranted inventory repositioning activity can be removed. Hypotheses are formulated to test whether discrete pricing between weekdays and weekends indeed exists within each pool. Consequently, if rivals do not follow this dogma of discrete pricing strategy, then there must be some invaluable insights. This exploration reveals numerous unforeseen factors such as the size of a rival, the volume of the demand, the destination character (leisure vs. business city) and a constant exorbitant daily rental rate, etc., make inventory repositioning ineffective. Ultimately, an effective repositioning model is proposed.
This paper examines the conditions necessary to specify a robust element of a supply chain using control theory and proposes a new robustness criterion clearly separating robustness from resilience. Algebraic analysis, using the Mikhailov criterion to determine robustness, yields simple criteria for an automatic pipeline with variable inventory and order-based production control system (APVIOBPCS) model. Models implemented with either exponential delays or finite delays are found to be completely robust. A new robustness measurement criterion is defined and applied to a case study of RAM manufacture. Results show that the continuous model of an APVIOBPCS system with an exponential delay has a wider allowable range of process delay time than other models and the range of permissible delay is sufficient to cope with a substantial increase in process delay time while retaining adequate performance and stability. Use of nonlinear inventory generally reduces the robustness range. The techniques used here can also determine the effects of other parameters on robustness.
In this paper, a production inventory model is considered for stock-dependent demand with the effect of deterioration. Generally, every industrialised organisation wants to produce perfect quality commodities. However, due to real-life problems (raw material, political problem, labour problem, machine breakdown, lock off, etc.) products produced by manufacturing process are not having perfect quality. Damage, deterioration, spoilage also affect the production process. In this model, production rate is considered to be larger than demand rate. Mathematical formulation is presented to locate best possible cycle time and entire inventory cost. Numerical examples and sensitivity analysis are provided to authenticate the model projected in this study. Graphical illustrations are provided to discuss the optimality of the model.
In this study an inventory model is proposed for deteriorating items considering two separate warehouses, as own warehouse (OW) of finite dimension and the rented warehouse (RW) for keeping the extra elements higher than the specified accommodation of the OW in practice. A lower deterioration rate is provided by the RW compared to OW due to its better preserving amenity. Also, the holding cost per unit in OW is lower compared to RW. In this paper an inventory model is considered for deteriorating items with inclusion of a two-warehouse management with linear demand rate and delay in payment. The objective of this work is to obtain the best fit replenishment strategies with minimisation of the total inventory cost. Numerical experiments are conducted with the developed mathematical model considering various parameters such as order, units and year. A sensitivity analysis is made to obtain optimal solutions with the change of parametric values with time.
This paper develops a production stock model for deteriorating products with shortages under the effect of inflation and late paying in which demand is a function of selling price and time. In this article, the model is considered with different deterioration distributions and various time dependent holding costs. This model aids in maximising the total inventory cost by finding the two production periods, the consumption period and the shortage period. Numerical example is presented to understand the developed model. Also, the effect of changes in different parameters on the optimal total cost is graphically presented.
Options can be used to hedge risks caused by different types of uncertainty in supply chain management. The first part of this study examines how to use surety-options to coordinate a retailer-leader supply chain. It develops an option model in which the retailer guarantees sales and the supplier guarantees quality. The retailer and the supplier negotiate the options price and security regulations. The supplier can transfer part of the market risk to the retailer but in return has to bear the quality risk. By the theoretical analysis and the numerical examples, this study demonstrates that surety-options can coordinate the supply chain and achieve Pareto-improvement by encouraging the retailer to increase marketing efforts and the supplier to improve the quality.
Micro, small and medium enterprises (MSMEs) in India are focused on improving their inventory management function as part of government's program to increase their contribution to the gross domestic product (GDP). A plethora of inventory models are available in literature; these models are either very complex, or need reliable inventory cost data, or are not applicable to all classes of items and are, therefore, rendered ineffective. In this paper we have developed and presented a simple, yet effective, model that combines the characteristics of selective inventory control (SIC) and an exchange curve (EC). Combination of these techniques not only allows determination of ordering policy for all items, but also involves managers in decision making, thus providing MSMEs with a solution that is robust and practical. We also describe application of this model to a sample of 30 items in an auto components manufacturing firm. The case study demonstrates ease of implementation of the proposed model as well as solution completeness.
Even though publications on discussed cash flow inventory problem are steadily growing, modelling the manager's characteristics and their effect on his/her decisions and planning outcome has not attracted in the text. In order to fill this gap and model authenticity more precisely. This research work develops a new economic order quantity (EOQ) model using discounted cash flow (DCF) approach under multiple suppliers' trade credits with stock-linked demand for failing commodities. This paper is a generalisation of an offered inventory model with trade credits in which both demand and deterioration are stable. Here the assumption of constant demand relaxed by incorporating the idea of learning in stock-dependent demand using DCF approach. The projected inventory control model using DCF approach and learning in multiple suppliers' trade credit has most excellent presentation in competence. Mathematical formulation is provided for three different situations for finding optimal cycle time and all future cash flows. On the basis of optimal solution some useful results are also discussed. Numerical examples are provided to demonstrate the models proposed in this study. Sensitivity analysis is also presented dissimilar parameters.
