Open AccessModels and algorithm for managing of the human capital development in a digital transformation of the machine-building enterprise
Author(s) -
Yulia Bondarenko,
Т. В. Азарнова,
И. Л. Каширина,
A L Uhin,
Anton N. Sunteev
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/862/4/042020
Subject(s) - competence (human resources) , schedule , computer science , digital transformation , process (computing) , context (archaeology) , human capital , transformation (genetics) , set (abstract data type) , knowledge management , industrial engineering , algorithm , operations research , engineering , management , paleontology , world wide web , economics , biology , programming language , economic growth , operating system , biochemistry , chemistry , gene
The article is devoted to the development of models and an algorithm for managing the process of continuous training of personnel as the most important direction in the development of human capital of an engineering enterprise. The proposed approach is based on a competency-based approach to learning. The paper proposes an algorithm for managing staff training. The basis of the algorithm is made up of mathematical models: a two-criteria model for the formation of an effective test package and a model for the formation of an optimal staff training schedule. The model for the formation of an effective test package makes it possible to select the minimum set from the set of tests, which makes it possible to obtain a quantitative assessment of the employee’s competency level. The model for creating the optimal schedule for staff training allows each employee to choose a program and a time period for training that ensure that the company achieves the maximum value of the total competence of employees. The model takes into account the production capabilities and needs of the enterprise in qualified personnel in the context of digital transformation.