Answers are grounded in this paper and cite their sources.
Creep testing is essential for characterizing the time-dependent deformation of engineering materials, but conventional testing systems can be costly and complex, limiting their use in teaching laboratories and small-scale research facilities. This study presents the design, fabrication, and experimental validation of a low-cost spring-loaded tensile creep testing apparatus developed for educational applications and preliminary material investigations. The apparatus was designed in SolidWorks and fabricated using locally available components, with a calibrated spring mechanism providing sustained tensile loading while minimizing system complexity and energy consumption. Its performance was evaluated through 120 h tensile creep tests on nylon, unplasticized polyvinyl chloride (UPVC), lead, and medium-density polyethylene (MDPE) under ambient conditions of 29–33 °C and 60–65% relative humidity, following the general recommendations of ASTM E139-11 and ISO 204. The measured creep strains after 120 h were 10.92%, 6.08%, 10.00%, and 4.00% for nylon, UPVC, lead, and MDPE, respectively, compared with theoretical values of 11%, 5%, 9.16%, and 3.006%. The corresponding relative errors were 0.7%, 21.6%, 9.2%, and 33.1%. The observed deformation responses exhibited characteristic creep behaviour, demonstrating the apparatus’s ability to capture time-dependent deformation across materials with different mechanical characteristics. The discrepancies between experimental and theoretical results, particularly for UPVC and MDPE, highlight the influence of material variability, nonlinearity, environmental conditions, and the absence of replicate measurements. Although the developed apparatus reliably captures basic creep behavior and distinguishes material trends, ambient thermal variations and baseline sensor drift limit its measurement precision. Consequently, while the platform is well-suited for hands-on instruction and initial material screening, rigorous sensor calibration, environmental shielding, and statistical replication remain mandatory before the generated data can support safety-critical engineering applications.
No takes yet. Share an insight, caveat, or question.
Rai et al. (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: