A Triple-Phase Inspection for Quality Control in MMAM

A Triple-Phase Inspection for Quality Control in MMAM
  IJETT-book-cover           
  
© 2025 by IJETT Journal
Volume-73 Issue-5
Year of Publication : 2025
Author : K. Rebecca Jebaseeli Edna, V. Jemmy Joyce, G. Gomathi Jawahar, G. Sheeba Merlin
DOI : 10.14445/22315381/IJETT-V73I5P113

How to Cite?
K. Rebecca Jebaseeli Edna, V. Jemmy Joyce, G. Gomathi Jawahar, G. Sheeba Merlin, "A Triple-Phase Inspection for Quality Control in MMAM," International Journal of Engineering Trends and Technology, vol. 73, no. 5, pp.137-144, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I5P113

Abstract
Modern 3D printing methods like MMAM are fostering innovation in sectors that need highly customised, useful, and specialised parts. Statistical Quality Control (SQC) methods and standardised test specimens are used to monitor and validate the quality of 3D printing to ensure the quality, consistency, and repeatability of 3D printed components. Smartwatches with embedded sensors are made by incorporating tiny, specialised electronic components right into the body or structure of the watch. This makes it possible for the watch to monitor a range of physical activities and health metrics like heart rate, temperature, and motion. This method typically combines microelectronics, assembly techniques, and Multi-Material Additive Manufacturing (MMAM) to seamlessly incorporate sensors into the watch without compromising its appearance or functionality. This study suggests a three-phase inspection process for MMAM quality control. Process control and product control are used in mixed sampling plans to improve acceptance sampling’s accuracy and/or efficacy. The process control component is based on a standard approximation and depends on a measurable process variable with a known standard deviation. An attribute sampling technique based on the truncated Poisson distribution (tPd) is used in the product control phase. It is assumed that for this inspection, the amount of supplies used in the 1st and the 3rd phases of the inspection is equal. As a result, producers and consumers gain from this. To enable the sample plan selection process, tables that include the operational characteristics function and related metrics are developed and shown.

Keywords
Triple-phase inspection, Truncated Poisson distribution, Sampling size, AQL, LQL, Operational characteristic function, Quality control in MMAM.

References
[1] H.F. Dodge, “Chain Sampling Inspection Plan,” Journal of Quality Technology, vol. 9, no. 3, pp. 139-142, 1977.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Edward G. Schilling, and Dean V. Neubauer, “Acceptance Sampling in Quality Control,” 2nd ed., Chapman and Hall/CRC, New York, 2009.
[CrossRef] [Google Scholar] [Publisher Link]
[3] V. Soundarrajan, “Procedures and Tables for Construction and Selection of Chain Sampling Plans (Chsp-1), Part 2: Tables for Selection of Chain Sampling Plans, vol. 10, no. 3, pp. 99-103, 1978.
[CrossRef] [Google Scholar] [Publisher Link]
[4] K. Govindaraju, “Selection of ChSP-1 Chain Sampling Plans for Given Acceptable Quality Level and Limiting Quality Level,” Communication in Statistics Theory and Methods, vol. 19, no. 6, pp. 2179-2190, 1990.
[CrossRef] [Google Scholar] [Publisher Link]
[5] R. Radhakrishnan, and L. Mohana Priya, “Selection of Single Sampling Plan using Conditional Weighted Poisson Distribution,” International Journal of Statistics and Systems, vol. 3 no. 1, pp. 91-98, 2008.
[Google Scholar] [Publisher Link]
[6] R. Radhakrishnan, and R. Sampath kumar, “Construction of Mixed Sampling Plan Indexed through MAPD and IQL with Single Sampling Plan as Attribute Plan,” National Journal of Technology, vol. 2, no. 2, pp. 26-29, 2006.
[Google Scholar]
[7] Asokan Mulayath Variyath, and Saminathan Balamurali, Multi-Attribute Single Sampling Plans, Economic Quality Control, 2000. [Online]. Available: https://www.researchgate.net/publication/267661791_Multi_attribute_single_sampling_plans
[8] V. Kaviyarasu, and Asif T Thottathil, “Designing Special Type Doubling Sampling Plan for Zero-Inflated Poisson Distribution through Various Quality Levels,” International Journal of Statistics and Applied Mathematics, vol. 3, no. 4, pp. 44-53, 2018.
[Google Scholar] [Publisher Link]
[9] Ayesha Fazal, and Shakila Bashir, “Family of Poisson Distribution and its Application,” International Journal of Applied Mathematics & Statistical Sciences, vol. 6, no. 4, pp. 1-18, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[10] R. Sampath Kumar, R. Vijaya Kumar, and R. Radhakrishnan, “Selection of Mixed Sampling Plan with Double Sampling Plan as Attribute Plan Indexed through MAPD and AQL using IRPD,” Advances in Applied Science Research, vol. 3, no. 6, pp. 3430-3437, 2012.
[Google Scholar] [Publisher Link]
[11] Hoejin Kim, Yirong Lin, and Tzu-Liang Bill Tseng, “A Review on Quality Control in Additive Manufacturing,” Rapid Prototyping Journal, vol. 24, no. 3, pp. 645-669, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[12] S. Devaarul, “Mixed Acceptance Sampling System with Tightened Inspection in the Second Stage,” International Journal of Artificial Intelligence, vol. 2, no. s9, pp. 57-65, 2009.
[Google Scholar]
[13] Ahmed Raouf Fahmy, Thomas Becker, Mario Jekle, M. 3D Printing and Additive Manufacturing of cereal-Based Materials: Quality Analysis of Starch-Based Systems using a Camera-Based Morphological Approach,” Innovative Food Science & Emerging Technologies, vol. 63, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[14] R. Vijayaraghavan, and K.M. Sakthivel, “Chain Sampling Inspection Plans based on Bayesian Methodology,” Economic Quality Control, vol. 26, no. 2, pp. 173-187, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Muhammad Aslam, Muhammad Azam, and Chi-Hyuck Jun, “A Mixed Repetitive Sampling Plan based on Process Capability Index,” Applied Mathematical Modelling, vol. 37, no. 24, pp. 10027-10035, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[16] S. Devaarul, D. Senthil Kumar, “Design and Development of Three Stages Mixed Sampling Plans for V-A-V Quality Characteristics,” International Journal of Statistics and Systems, vol. 12, no. 4, pp. 763-772, 2017.
[Google Scholar] [Publisher Link]
[17] Bernhard Dorweiler et al., “Quality Control in 3D Printing: Accuracy Analysis of 3D-Printed Models of Patient-Specific Anatomy,” Materials, vol. 14, no. 4, pp. 1-13, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Hsin-Chieh Wu, and Tin-Chih Toly Chen, “Quality Control Issues in 3D-Printing Manufacturing: A Review,” Rapid Prototyping Journal, vol. 24, no. 3, pp. 607-614, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Grzegorz Budzik et al., “Methodology for the Quality Control Process of Additive Manufacturing Products Made of Polymer Materials, Materials, vol. 14, no. 9, pp. 1-19, 2021.
[CrossRef] [Google Scholar] [Publisher Link]