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All Journal Inventa: Journal of Science, Technology, and Innovation
Ikhtamul Fajri
Universitas Pancasakti Tegal
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Analisa Kekuatan Mesin Bending Hidrolik Tipe YSD-HSDY/HPPTK 200/3000 di Koperasi Tegal Manufaktur Indonesia Ikhtamul Fajri; M.Fajar Sidik
Journal of Science, Technology, and Innovation Vol 1 No 3 (2026): : April: Inventa: Journal of Science, Technology, and Innovation
Publisher : CV SCRIPTA INTELEKTUAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65310/pf38wd76

Abstract

This study presents an empirical analysis of the structural strength, operational performance, and reliability characteristics of a hydraulic bending machine type YSD-HSDY/HPPTK 200/3000 under real industrial conditions at Koperasi Tegal Manufaktur Indonesia. The research integrates field observation, direct measurement, and mechanical modeling to evaluate force distribution, deformation behavior, and system response during bending operations. Experimental data were collected through variations in material thickness, bending angles, and hydraulic pressure to examine their influence on machine capacity and output consistency. The results indicate that the machine demonstrates stable force generation within its operational threshold, although deviations emerge under increased loading intensity and frequency. Analytical findings reveal that stress concentration occurs at critical structural points, contributing to gradual performance degradation and reduced precision. Reliability assessment further shows that repeated operational cycles significantly affect hydraulic stability and component wear, leading to increased deviation in bending accuracy. The integration of empirical and analytical approaches provides a comprehensive understanding of machine behavior, offering a robust basis for performance optimization, predictive maintenance, and enhanced operational safety in industrial bending applications.
Co-Authors M.Fajar Sidik