Static Structural Performance Evaluation of a Workshop Hoist Using ANSYS Mechanical

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Tilak Bohra, Dipak P Kharat, Santosh R. Shekokar, Yugesh A. Kharche, Nitin A Kharche, Sachin M. Bhole

Abstract

Material handling equipment is crucial in manufacturing industries, automobile workshops, maintenance facilities, warehouses, and assembly units.The advent of Computer Aided Engineering (CAE) tools has significantly enhanced mechanical design and analysis. Finite Element Analysis (FEA) allows engineers to predict structural behavior under various loads before manufacturing, reducing development costs, minimizing design errors, and improving reliability. In this study, a detailed modeling and structural analysis of a workshop hoist were performed using ANSYS Workbench 19.2.The three-dimensional hoist model, imported in IGES format, consists of 27 structural components made of structural steel. The hoist has approximate dimensions of 1887.7 mm in length, 1651 mm in height, and 940.21 mm in width, with a total mass of 214.72 kg. Material properties assigned included a Young’s modulus of 200 GPa, Poisson’s ratio of 0.3, yield strength of 250 MPa, and ultimate tensile strength of 460 MPa.


For structural analysis, fixed support boundary conditions were applied to the base frame, while a downward force of 4500 N was applied at the lifting point to simulate operational conditions. Static structural analysis determined total deformation, equivalent elastic strain, maximum principal strain, maximum shear strain, equivalent von-Mises stress, and maximum shear stress. The maximum deformation recorded was 16.278 mm, with maximum equivalent elastic strain and principal strain of 1.8636 × 10⁻³ mm/mm and 1.8528 × 10⁻³ mm/mm, respectively. The maximum shear strain was 2.5653 × 10⁻³ mm/mm.Stress analysis revealed a maximum von-Mises stress of 371.05 MPa and maximum shear stress of 197.33 MPa. The highest stress concentrations occurred near the boom linkage and load-carrying joint regions, where bending moments and load transfer forces are greatest, highlighting critical areas for design optimization.

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