Evaluating UX Design Factors Affecting Efficiency of Composite Material Design and Analysis Platforms

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Year : 2026 | Volume : 14 | 04 | Page :
    By

    Gaurav Pramodrao Taywade,

  • Mahendra D. Ingole,

  • Rajkumar Jha,

  1. Research Scholar, School of Management Studies, G. H. Raisoni University, Amravati, Maharashtra, India
  2. Dean and Associate Professor, School of Management Studies, G. H. Raisoni University, Amravati, Maharashtra, India
  3. Associate Professor, School of Management Studies, G. H. Raisoni University, Amravati, Maharashtra, India

Abstract

Within engineering software platforms that involve the design, simulation and characterization of composite materials, user experience (UX) design has become a key determinant for efficient use. This research aims to quantify how user experience design parameters relate to productivity in composite engineering workflows by analyzing the relationship between usability, learnability, accessibility, complexity of the UI, navigation efficiency and users engineering results satisfaction. Computational techniques in python were used in the analysis of a dataset of 400 observations that can be used for design and analysis of composite materials. Both explanatory and predictive relationships were investigated using descriptive statistics, reliability analysis, Pearson correlation analysis, multiple linear regression, mediation, machine-learning prediction models, and analysis of variance. The results suggest that the factors of usability and user satisfaction positively affect the productivity of composite engineering platforms, and that interface complexity negatively affects the productivity to a high degree. The relationship between learnability and productivity was found to have a statistically significant positive contribution, while accessibility represented a relatively minor direct contribution to productivity. This mediation analysis showed that the link between usability and engineering productivity is partially mediated by user satisfaction, demonstrating both direct and indirect benefits of good interface design. Among the various predictive models tested, the Random Forest model yielded the greatest coefficient of determination (R2 = 0.949), showing outstanding predictive power. The results highlight the significance of user-centered interface design in composite material modeling and characterization systems and reveal that UX based metrics may be used as a good proxy for engineering productivity. It offers practical advice to anyone who develops composite engineering software, works with composite materials, and is designing software or hardware to perform effectively in design processes and make sound decisions, with a focus on improving user experience.

Keywords: User experience, software development efficiency, usability, developer satisfaction, machine learning, productivity analysis.

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How to cite this article:
Gaurav Pramodrao Taywade, Mahendra D. Ingole, Rajkumar Jha. Evaluating UX Design Factors Affecting Efficiency of Composite Material Design and Analysis Platforms. Journal of Polymer & Composites. 2026; 14(04):-.
How to cite this URL:
Gaurav Pramodrao Taywade, Mahendra D. Ingole, Rajkumar Jha. Evaluating UX Design Factors Affecting Efficiency of Composite Material Design and Analysis Platforms. Journal of Polymer & Composites. 2026; 14(04):-. Available from: https://journals.stmjournals.com/jopc/article=2026/view=249309


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Ahead of Print Subscription Original Research
Volume 14
04
Received 10/06/2026
Accepted 22/06/2026
Published 07/07/2026
Publication Time 27 Days
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