Design and Analysis of Industrial Material Handling Systems using FEA and Dynamic Simulation Techniques: FEA AND SIMULATION-BASED DESIGN OF MATERIAL HANDLING SYSTEMS

Sukhadip Mhankali Chougule; Govindarajan Murali; Anant Sidhappa Kurhade

doi:10.56042/jsir.v84i6.17512

Authors

Sukhadip Mhankali Chougule Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Guntur (Dt) 522 502, Andhra Pradesh, India and Department of Mechanical Engineering, PCET’s Pimpri Chinchwad College of Engineering and Research, Ravet, Pune 412 101, Maharashtra, India
Govindarajan Murali Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Guntur (Dt) 522 502, Andhra Pradesh, India
Anant Sidhappa Kurhade Department of Mechanical Engineering, Dr. D. Y. Patil Institute of Technology, Sant Tukaram Nagar, Pimpri, Pune 411 018, Maharashtra, India and School of Technology and Research, Dr. D. Y. Patil Dnyan Prasad University, Pimpri, Pune 411 018, Maharashtra, India

DOI:

https://doi.org/10.56042/jsir.v84i6.17512

Keywords:

Adaptive control, Algoryx momentum, Automation, Orientation, Vibratory bowl feeder

Abstract

This study focuses on the design, simulation, and experimental validation of advanced material handling systems, specifically a vibratory bowl feeder and a paddle mixer, aimed at enhancing automation efficiency in modern industrial environments. The scope encompasses improving part orientation and mixing reliability in sectors such as automotive, pharmaceutical, and food processing industries. A vibratory bowl feeder was custom-designed for nuts and bolts, addressing common challenges such as inconsistent feed rates, jamming, and adaptability. The methodology involved 3D CAD modeling in SolidWorks, finite element analysis (FEA) for structural integrity verification, and dynamic simulation using Algoryx Momentum to predict system behavior under varied operating conditions. A spring-mass model was developed to compute natural frequencies and vibration characteristics. Simulation results were validated through experimentation across a frequency range of 47–79.75 Hz, measuring feed rate and part delivery time. Key findings indicate that the vibratory feeder achieved up to 200 parts per minute and over 95% orientation accuracy. FEA confirmed structural safety with stresses below 312 MPa and a verified natural frequency of 78.4 Hz. Simulation outcomes closely matched experimental results in the 50–60 Hz range but deviated at lower frequencies, highlighting real-world inefficiencies not captured in the model. The study concludes that integrating simulation with physical validation ensures robust design, reduced development costs, and enhanced system efficiency. Future work includes incorporating AI-based control and smart sensors to improve adaptability, accuracy, and energy efficiency. This work establishes a strong foundation for the development of intelligent, high-performance material handling systems.