Research
A Model for Managing and Controlling the Inventory of Stores Items based on ABC Analysis
Today, the effective inventory management plays an important role in the success of the organizations in the new business environment. It is not clearly possible for the organizations that store hundreds of inventory items to economically design an inventory management policy for each inventory item separately. To have an efficient control of a huge amount of inventory items, traditional approach is to classify the inventory into different groups. Different inventory control policies can then applied to different groups. The well-known ABC classification is simple to understand and easy to use. Moreover, various inventory items may play quite different roles in the business of the organization. Hence, the managers need to classify these items in order to control each inventory category properly based on its importance rating. In this thesis we consider a model of college hostel mess stores items (grocery and vegetables) for inventory management through ABC analysis. This research is composed of the following sections: In the first section, the criteria affecting the evaluation of the inventory control system of the studied mess stores and the priority of each one of them will be identified, in the second section, the priority of each criterion such as cost of item, annual demand for an each item hence find annual consumption cost in each inventory category (A, B, C) is Calculated based on conventional model, in the third section, presents an alternative way of classifying the different productive items of accompanies and this ABC model compares with the classic Pareto classification, which ranks productive items according to their importance in terms of frequency and costs whereas rankings obtained using the classical method are based on information about costs and demand over a period in the past "A-items" that result from this new classification.
FMEA based Quantification analysis of Outbound Supplier Risk and its Resilience
Supply chain is the linkage of series of organizations with facilities, functions, and logistic activities that are involved in producing and also delivering a product or service. In the past, when firms manufactured in-house, they sourced locally and sold directly to customer. During that period, supply chain risk was less diffused and easier to manage. In recent years global supply chain was hit by increasing globalization, because all organizations had to face vulnerable by different types of risk in their inbound and outbound supply chain network. The various supply chain (SC) vulnerabilities are reputation, unreliability, overstocking, price increases, corruption, natural disasters and financial failure. The implications of supply chain possessing vulnerability costlier and lead to significant customer delivery delays, etc. Though, different types of supply chain vulnerability management methodologies have been proposed for managing supply risk. To the above concern, reinforce outbound supply chain risk management by proposing an integrated methodology to classify, manage and assess outbound supply risks were made. The contributions of the work owing to namely (1) outbound supply risk factors are identified through both supply chain risk literature review and industrial interview; (2) Hierarchical risk factor classification structure is created; (3) reduction of outbound supplier risk by using six sigma methodologies was validated. This project is an attempt to quantify the outbound supplier risk with a suitable case study.
