RESEARCH OF INFORMATION MAINTENANCE TECHNOLOGY OF MACHINE OPERATOR TRAINING QUALITY ASSESSMENT AS THE ELEMENT OF THE SYSTEM

Alexander Laktionov

Abstract


The information maintenance technology of machine operator training quality assessment with numerical programmed control (the machine operator), which ensures the operation of the “Operator – Machine Tool – Part Manufacturing Program” (OMMP) system, has been studied. The methods used to obtain primary empirical self-assessments, expert assessment and standardized estimates of the industry standard for calculating:

1) The index of professional competence of the machine operator, where self-assessments and expert assessments are combined;

2) The index of quality assessment of machine operator training, where the series of expert assessments and standardized assessments of the industry standard are combined, separately, for each of the four levels of complexity of the part-processing control program.

The proposed mathematical methods of index estimates simplify the process of comparative analysis and establish a relationship between the growth index of the professional machine operator competence formation and the effectiveness of the information maintenance technology index for assessing the quality of its training by state certification methods.

It has been experimentally proved that raising the level of qualification through the means of state certification has a significant effect on the growth of the level of professional competence and the quality of machine operator training. The effectiveness of information technology to support the quality assessment of machine operator training is provided by subjective factors (formed qualities of the operator’s personality) in conjunction with the external (objective) factors causing them to form.


Keywords


professional competence; quality of machine operator training; open system; self-assessments; expert assessments; standardized assessments

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DOI: http://dx.doi.org/10.21303/2461-4262.2018.00790

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ISSN 2461-4262 (Online), ISSN 2461-4254 (Print)