A comparison of multi-criteria methods for spare parts classification

Spare parts classification is a fundamental step in spare parts inventory management. Through classification, the parts are grouped using a set of relevant criteria. Methodologies and methods for multicriteria decision making are used to support the classification of spare parts. In this paper, a comparative study between the use of the multi-criteria classification based on rules and the multi-criteria classification using the Analytic Hierarchy Process is presented, showing the advantages and disadvantages of each method. The study confirmed that the multi-criteria method based on rules is more easily applied in organizations. The multi-criteria method using Analytic Hierarchy Process required more calculations, turning the implementation of the method more complicated, especially for non-Analytic Hierarchy Process specialists

Application of Artificial Neural Networks to Multiple Criteria Inventory Classification

Inventory classification is a very important part of inventory control which represents the technique of operational research discipline. A systematicapproach to the inventory control and classification may have a significant influence on company competitiveness. The paper describes the results obtained by investigating the application of neural networks in multiple criteria inventory classification. Various structures of a back-propagation neural network have been analysed and the optimal one with the minimum Root Mean Square error selected. The predicted results are compared to those obtained by the multiple criteria classification using the analytical hierarchy process

ABC Analysis in an Internet Shop: A New Set of Criteria

This article presents a model of ABC analysis tailored for internet shops. The standard set of criteria is expanded to cover e-commerce specific characteristics, such as the number of product views, search engine rankings and product links via a recommendation system..The proposed new methodology is applied to real data from an internet bookstore in Poland. A comparison with the results of a standard, not internet-oriented ABC analysis shows the advantage of using the new set of criteria.ABC analysis, internet shop, inventory control

Determination Inventory Level for Aircraft Spare Parts Using Continuous Review Model

In this paper, we determine ordering quantity and reorder point for aircraft consumable spare parts. We use continuous review model to propose a spare part inventory policy that can be used in a aircraft maintenance company in Indonesia. We employ ABC classification system to categorize the spare parts based on their dollar contribution. We focus our research on managing the inventory level for spare parts on class A and B which commonly known as important classes. The result from the research indicates that the continuous review policy gives a significant amount of saving compared to an existing policy used by the company

Fuzzy Continuous Review Inventory Model using ABC Multi-Criteria Classification Approach: A Single Case Study

Abstract. Inventory is considered as the most expensive, yet important,to any companies. It representsapproximately 50% of the total investment. Inventory cost has become one of the majorcontributorsto inefficiency, therefore it should be managed effectively. This study aims to propose an alternative inventory model,  by using ABC multi-criteria classification approach to minimize total cost. By combining FANP (Fuzzy Analytical Network Process) and TOPSIS (Technique of Order Preferences by Similarity to the Ideal Solution), the ABC multi-criteria classification approach identified 12 items of 69 inventory items as “outstanding important class†that contributed to 80% total inventory cost. This finding  is then used as the basis to determine the proposed continuous review inventory model.This study found that by using fuzzy trapezoidal cost, the inventory  turnover ratio can be increased, and inventory cost can be decreased by 78% for each item in “class A†inventory.Keywords:ABC multi-criteria classification, FANP-TOPSIS, continuous review inventory model lead-time demand distribution, trapezoidal fuzzy numberÂ

Use of Artificial Intelligence (AI) in Managing Inventory of Medicine in Pharmaceutical Industry

 Inventory is one of the vital components of current assets. Excess holdings of inventory may increase cost as well as wastage. As such, effective and efficient management of inventory is an integral part of supply chain. Especially, in the field of management of pharmaceutical products and medicine it bears more importance. Improper use of pharmaceutical products or shortage of medicine would not only cause financial loss but also may affect the patients adversely. Rather than using the traditional techniques of managing inventory use of Artificial Intelligence (AI) can make the process more effective and efficient. AI is the application of computer program that demonstrates action like a human being, learns from experience, gets new input and processes big data by reasoning. It can acquire large amount of data and create rules for turning the data into actionable information. This study has been conducted based mainly on secondary sources of data. It is a qualitative study that gives a conceptual idea regarding how the functions of AI can support managing inventory of medicine in pharmaceutical industry

Inventory Analysis Using the ABC-Ved Matrix - Applied Research in Al-Zawraa State Company

Purpose: The aim of this study is to examine or analyze the inventory by integrating the analyzes of ABC and VED and take advantage of their advantages together by forming an ABC-VED matrix to classify the inventory according to the cost criteria and the functional importance of the inventory items.   Theoretical framework: The ABC-VED matrix consists of ABC analysis, VED analysis, and then the ABC-VED matrix.   Design / Methodology / Approach: The researcher relied on the case study approach in this research, due to the multiplicity of features and benefits of this approach by using more than one research method at the same time to obtain the maximum benefit related to the case under study, In addition to the fact that this approach helps in a comprehensive and in-depth analysis of the researched problem by obtaining a large amount of information for all events related to the researched case, Where the researcher seeks through this research to analyze the inventory according to the ABC-VED matrix to classify the inventory into three categories according to the criteria of cost and the functional importance of the inventory.   Finding: The results show that the use of the ABC-VED matrix helped Al-Zawra State Company to control, organize and manage its inventory of raw materials and spare parts in more efficient ways, by classifying it into three categories according to the criteria of cost and critical importance, by focusing on the first category and giving it great attention and care because of its high cost, and its great importance.   Research, practical & social implications: The study is expected to help control inventory because of its classification into three categories according to the criteria of cost and the functional importance of raw materials and spare parts for the company in the field of research or other companies wishing to control their inventory.   Originality / Value: The value of the study focuses on the analysis of inventory in Al-Zawraa State Company, and this research responds to addressing the problems of inventory in the company in the field of research by classifying it into three master categories for the purpose of controlling and managing it better