Optimization Of Forklift Fork Design For Enhanced Performance And Safety In Material Handling Operations Using Finite Element Analysis

Abstract

The Material Handling Industry Relies Heavily On The Performance And Safety Of Forklifts, With Fork Design Playing A Critical Role In Ensuring Efficiency And Reliability. Forklift Forks, Which Are The Primary Load-Bearing Components, Are Responsible For Supporting And Lifting Heavy Loads, Making Their Structural Integrity And Design Optimization Critical For Safe And Effective Material Handling. This Research Investigates The Optimization Of Forklift Fork Design To Enhance Its Performance And Safety By Leveraging Finite Element Analysis (Fea) Through Ansys Software. A Key Focus Of The Study Is The Optimization Of Solid Mass, Stress Distribution, And The Factor Of Safety. Lightweight Designs Are Prioritized To Improve Energy Efficiency Without Compromising Structural Strength. The Optimization Process Employed The Response Surface Method (Rsm) Using Ansys Design Explore, Where 25 Design Experiments Were Conducted And Analysis Through Minitab Statistical Software. This Iterative Process Aimed To Reduce Solid Mass For Material Efficiency, Minimize Von Mises Stress To Enhance Durability, And Improve The Factor Of Safety To Ensure Adherence To Safety Standards Like The Occupational Safety And Health Administration (Osha). The Study Identified Three Candidate Designs, With Candidate Point 1 Selected For Further Optimization Due To Its Superior Performance Metrics. The Optimization Process Utilized Input Parameters Such As The Fork's Height, Length, Depth, And Overall Geometry, Employing Fine And Converged Mesh Systems To Ensure Precision. Key Findings Demonstrate A Reduction In Solid Mass From 53.232 Kg To 52.772 Kg A Difference Of 0.46 Kg, A Significant Decrease In Average Equivalent (Von Mises) Stress From 3.2306 ?? 10??? Pa To 2.2998 ?? 10??? Pa, An Improvement Of 28.8% And An Improvement In The Safety Factor From 1.8082 To 2.7998 Representing A Substantial 54.8% Enhancement In The Fork's Resilience. These Results Highlight A Marked Enhancement In The Fork's Performance And Structural Safety While Optimizing Material Use. This Study Contributes To Material Handling Equipment Design By Presenting A Robust Framework For Performance Optimization Using Finite Element Analysis And Advanced Design Exploration Techniques. The Findings Emphasize The Practicality And Relevance Of Integrating Computational Optimization Tools In Industrial Design Processes To Achieve Higher Efficiency, Safety, And Sustainability In Material Handling Systems