Application of index estimates for improving accuracy during selection of machine operators
Journal Title: Восточно-Европейский журнал передовых технологий - Year 2019, Vol 3, Issue 1
Abstract
<p>The methods proposed in this paper for calculating index ratings when selecting machine operators provide greater accuracy than the selection based on expert estimates and integrated indicators for groups of expert estimates.</p><p>Index estimates are calculated based on the algorithm that combines self-assessments and expert estimates into the Quality index of professional competence of a machine operator (<em>І<sub>РС</sub></em>) while expert estimates and standardized assessments are combined into the Quality index of a machine operator training (<em>I<sub>QT</sub></em>). The proposed methods for computing the index estimates comprehensively characterize an element in the functioning of the social subsystem in the system «Machine operator ‒ Machine with numerical control ‒ Part manufacturing program», OMMP.</p><p>Index estimates characterize the degree of coherence/imbalance among self-assessments and expert estimates, as well as expert estimates and standardized assessments, as well as systemic interrelations between a machine operator and elements of the social, technical, and information subsystems within an open system.</p><p>Advantages of index-based selection of machine operators over that based on expert estimates were assessed by comparing the two series of rankings in a list of names. The series of rankings were obtained using such methods as linear convolution and multiplicative convolution. It has been proven that the selection of machine operators using linear convolution is considerably more accurate if carried out based on the index estimates, when compared with expert estimates. It is appropriate to use a binary search method to select machine operators in accordance with a customer’s requirements.</p>
Authors and Affiliations
Alexander Laktionov
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