Open AccessEvaluating The Performance of The Supply Chain Using Artificial Intelligence Techniques: A Case Study In The Dairy Industry
Author(s) -
Ali Rehman Musa,
Assist. Prof. Harith Yarub Maan
Publication year - 2022
Publication title -
international journal of transformation in business management
Language(s) - English
Resource type - Journals
eISSN - 2454-468X
pISSN - 2231-6868
DOI - 10.37648/ijtbm.v12i01.004
Subject(s) - supply chain , balanced scorecard , computer science , supply chain management , artificial neural network , fuzzy logic , factory (object oriented programming) , artificial intelligence , process management , risk analysis (engineering) , business , marketing , programming language
The issues of evaluating and improving supply chains are among the complex issues due to the diversity of factors affecting performance, as well as the gap between these factors and how they are applied. The current study aims to evaluate the performance of the Supply chains of the dairy factory, College of Agriculture, using artificial neural networks and fuzzy logic by relying on the balanced scorecard as a basic methodology for evaluation, which consists of five main aspects (financial - customer - internal processes - learning and growth - Suppliers). Each aspect has several sub-criteria and by obtaining the opinions of experts in evaluating these criteria for several days and then training the network to make a decision related to evaluating the supply chain and processing the outputs of the neural network with fuzzy logic to classify performance into four main categories, each of which represents the state of the supply chain and what distinguishes the model its ability to continuously evaluate the supply chain and employ artificial intelligence tools in managing the supply chain.