STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Polymer & Composites

Correlation Between XRD Analysis and Mechanical Characterization Using Lens Manufactured Specimens Based on IoT Sensors

  1. Puttam Sreenivasa Rao
  2. A Srinath
  3. K L Narayana

Abstract

The advent of the Internet of Things (IoT) has enabled the seamless integration of sensors into the manufacturing process, facilitating the collection of real-time data for analysis and optimization. The correlation between X-ray diffraction (XRD) analysis and mechanical characterization is investigated using specimens manufactured through the Laser Engineered Net Shaping (LENS) technique. The study focuses on three different materials: brass, SS202, and SS304. XRD analysis is employed to determine the crystallographic structure, phase composition, and residual stress distribution within the LENS-manufactured specimens. Mechanical characterization, including tensile testing and hardness measurements, is performed to assess the mechanical properties and structural behavior of the samples. The objective of this research is to establish a correlation between the information obtained from XRD analysis and the mechanical performance of the LENS-manufactured specimens using LENS Sensor. By comparing the XRD results with the mechanical characterization data, insights into the influence of material properties on the structural behavior can be gained. The findings from this study contribute to a better understanding of the relationship between XRD analysis and mechanical characterization, providing valuable insights for optimizing the LENS manufacturing process and improving the overall performance of LENS-manufactured components. The findings underscore the critical role of IoT-integrated monitoring in enhancing the quality control and optimization of lens manufacturing processes, ultimately contributing to the advancement of precision engineering in optical technologies.

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