Review of Statistical Process Control (SPC) Methods in the Context of Ensuring Medical Device Reliability

Citation: Victor Armel Eyanga, "Review of Statistical Process Control (SPC) Methods in the Context of Ensuring Medical Device Reliability", Universal Library of Engineering Technology, Volume 03, Issue 01.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The article examines specific features of ensuring the integration of statistical process control (SPC) into the quality management systems of medical device manufacturers. The significance of the topic is determined by the simultaneous strengthening of regulatory pressure (FDA, ISO 13485) and the need for digital modernization of production loops within the logic of Industry 4.0, since it is precisely the combination of regulatory compliance and digital maturity that becomes a prerequisite for achieving an exceptionally high product reliability. The scientific novelty consists in substantiating a hybrid model in which dynamic risk management based on PFMEA is coupled with SPC instruments and predictive analytics components, forming an end-to-end architecture for monitoring and preventing deviations. Substantial emphasis is placed on an applied case of the Canadian company Umano Medical devoted to the industrialization of medical bed manufacturing, which makes it possible to specify requirements for data, metrology, and managerial decisions when scaling output. The purpose of the study is to analyze the effectiveness of implementing digital quality loops as a means of minimizing production defects and increasing process predictability. To achieve this purpose, Lean Six Sigma tools, methods of correlation analysis of production data, and provisions of systems engineering are applied, ensuring the alignment of technical, organizational, and information components. The analytical basis is formed from materials of publications from recent years. The outcome is the author’s concept of risk-oriented digital SPC, interpreted as an integrated system that unites variability management, risk prioritization, and deviation forecasting within a single digital cycle. The material is oriented toward the practical tasks of quality engineers, R&D specialists, and production managers in medical equipment manufacturing.

Keywords: Statistical Process Control, Medical Device Reliability, ISO 13485, PFMEA, Industry 4.0, Lean Six Sigma, Quality 4.0, FDA Complianc.

https://doi.org/10.70315/uloap.ulete.2026.0301005