Accepted for IESL 113th Annual Sessions 2019
Fuzzy Rule-Based Finite Capacity Planning Implementation of MRP for Discrete Manufacturing Environments
Corresponding Author : Buddhika Kurera (firstname.lastname@example.org)
Abstract – Discrete Manufacturing is a term commonly used to identify manufacturing processes which produce items that can be counted, tracked as units. One of the common challenges in manufacturing industry is the production planning. As a result, many methods have been invented over the years to solve the planning problem optimizing the schedules. In such methods Material Requirement Planning plays a major role as it calculates the demand and supply beforehand. However, the fact of ignorance of capacity constraints in classical MRP to simplify the problem, leads to undesirable outputs when it comes to real-life scenarios as assumptions fails. The main issue in finite capacity planning approach is the complexity of the problem. As the number of variables and constraints grow, the complexity of the MRP calculation increases exponentially. In this research the main focus is to implement an effective mechanism to manage the problem. For the purpose, a fuzzy rule-based approach has been studied. Fuzzy logic is not a strange concept in scheduling. In fact, when data is not certain, usage of fuzzy logic would be an excellent choice. However, in this research fuzzy logic has been used to improve the efficiency, hence reducing the complexity of the problem. A model has been proposed to achieve the objective. Simulations based on numerical analysis have been carried out to fine tune the model based on benchmark problems afterwards.
Keywords: Discrete Manufacturing, Material Requirement Planning, MRP, Fuzzy rule-base, Fuzzy