Particle Swarm Optimization for Cellular Manufacturing Problem

Project Title

Particle Swarm Optimization for Cellular Manufacturing Problem

Project Area of Specialization Mechanical EngineeringProject Summary

Particle swarm optimization (PSO) is an emerging Artificial Intelligence technique. Inspired from social behavior of Birds and school of fishes. It was introduced by Kennedy and Eberhart in 1995. Cell formation is the backbone of any cellular manufacturing system, this system covers the advantages of both flow line system and job shop system. The cellular Manufacturing system provides efficient flow and high production rate with respect to others. So obtaining the best cell manufacturing system arrangement we are implementing PSO an Artificial Intelligence technique.

Project Objectives

•Implementation of Particle Swarm Optimization.

•To identify part families and corresponding machine groups.

•Minimize the inter-cellular movement.

•Obtaining the maximum efficacy.

Project Implementation Method

By using MATLAB, Particle Swarm Optimization Algorithm is applied to cellular Manufacturing System.

Benefits of the Project

• Increases the productivity of any manufacturing industry.
• Reduction of Lead time.
• Effective and well managed job handling.
• Optimized arrangement of machines.

Technical Details of Final Deliverable

• Optimized arrangement of Machines in manufacturing industries.
• Jobs that require a similar processing are identified and processed within a cell according to the requirement of the operation.

Final Deliverable of the Project Software SystemCore Industry ManufacturingOther Industries Others Core Technology Artificial Intelligence(AI)Other Technologies OthersSustainable Development Goals Decent Work and Economic Growth, Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	10000
Report Printing	Miscellaneous	5	2000	10000