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  • 标题:Development of qualimetric approaches to the processes of quality management system at enterprises according to international standards of the ISO 9000 series
  • 本地全文:下载
  • 作者:Roman Trisch ; Elena Gorbenko ; Natalia Dotsenko
  • 期刊名称:Eastern-European Journal of Enterprise Technologies
  • 印刷版ISSN:1729-3774
  • 电子版ISSN:1729-4061
  • 出版年度:2016
  • 卷号:4
  • 期号:3
  • 页码:18-24
  • DOI:10.15587/1729-4061.2016.75503
  • 语种:English
  • 出版社:PC Technology Center
  • 摘要:For the assessment of the processes of the system of quality management (QMS) at enterprises, it is necessary to bring all estimations of the indicators of quality of the processes to one, desirably a dimensionless, scale of measurements. As the function of desirability for the conversion of various dimensional indicators of quality into a dimensionless value, applying a desirability function is proposed.A peculiarity and a difference from the existing functions of desirability is the fact that it takes into account maximally permissible and minimally permissible values of the indicator of quality of a process, and also its best (optimal) value. In addition to this, the parameter of form and steepness of function is present, which will make it possible to use them for the assessment of the processes of different significance with different requirements for quality.It is proposed to assess QMS through the values of the set of interconnected processes, i.e., to combine the assessments of different processes into one set of data and to estimate this set as a whole. This procedure will make it possible to increase the amount of information about the estimations of quality of the system as a set of processes, which will allow assessing the system as a whole with higher objectivity and reliability. The solution to this problem is proposed by statistical methods, using parametric and nonparametric statistics, since they do not require the knowledge of the law of distribution of a random value.
  • 关键词:quality management system;quality indicator;assessment criterion;nonparametric statistics;graphic model
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