Abstract

Starting from the PDCA cycle (Plan - Do - Check - Act), imposed by the ISO 9000 quality standards, a loop is proposed to automatically adjust the work equipment to the statistical distribution of the quality feature of the last N products randomly selected. The loop promptly warns the leadership in case of distortion of the statistical distribution, caused by equipment, raw materials, human operators or the environment. It also constantly informs about the percentage of noncompliant products. The main original element, at the heart of the article's concerns, is the quality tracking loop presented in section 4. The starting point is the quality management scheme, according to ISO9000, while sections 2-3 expose the theoretical basis of the subject, without which it would have not been possible to deepen the role of the modules from the loop proposed in Figure 6.

Highlights

  • IntroductionThe current standard, concerning quality management systems, maintains the requirements of the old standards, but groups them logically on the technological flow

  • The loop promptly warns the leadership in case of distortion of the statistical distribution, caused by equipment, raw materials, human operators or the environment

  • The cycle Plan- DoCheck- Act is a typical automation loop, in which the Check- Act operations are a feedback that interferes with planning, in order to improve the quality of the product

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Summary

Introduction

The current standard, concerning quality management systems, maintains the requirements of the old standards, but groups them logically on the technological flow. The cycle Plan- DoCheck- Act is a typical automation loop, in which the Check- Act operations are a feedback that interferes with planning, in order to improve the quality of the product. Since the standard [1] has a general nature, covering all activities in production and services, this paper aims to identify solutions for the "Improvement" module, so that through "Verification" and "Actuation", some operations from the quality management system of a production line can be automated

Statistical distributions
Normal Gauss distribution
Automation of quality management
Conclusions
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