PRESERVING EMPLOYEES' PERSONAL KNOWLEDGE DURING THE TRANSITION TO AUTOMATED PRODUCTION

This article is devoted to analysing ways of identifying and preserving the personal knowledge acquired by employees in the course of their work in the context of the introduction of highly automated production, as well as determining the most acceptable technologies for this process. The paper examines the practical implementation of existing approaches to the transfer of employees’ personal knowledge, based on the consistent formalization of employees’ personal knowledge and controlled organizational forgetting. As a result of the analysis, the author concludes that the transfer of individual employee knowledge for further use in automated systems should be based on the use of semantic models of corporate knowledge built using industry ontologies. The article describes the author’s proposed process for creating semantic knowledge models for the transfer of employee knowledge. The materials of the work are applicable for the development of practical ways and methods for identifying, further preserving, and effectively using the personal knowledge of employees during the transition to Industry 4.0 technologies.

Authors

Publication Details

Journal
Machine Learning and Applications An International Journal
Published
2025-09-29
DOI
https://doi.org/10.5121/mlaij.2025.12301
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00
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article

PRESERVING EMPLOYEES' PERSONAL KNOWLEDGE DURING THE TRANSITION TO AUTOMATED PRODUCTION

Ekaterina Mashina
Machine Learning and Applications An International Journal
Digital Transformation in Industry
article

PRESERVING EMPLOYEES' PERSONAL KNOWLEDGE DURING THE TRANSITION TO AUTOMATED PRODUCTION

Ekaterina Mashina
article en

Abstract

This article is devoted to analysing ways of identifying and preserving the personal knowledge acquired by employees in the course of their work in the context of the introduction of highly automated production, as well as determining the most acceptable technologies for this process. The paper examines the practical implementation of existing approaches to the transfer of employees’ personal knowledge, based on the consistent formalization of employees’ personal knowledge and controlled organizational forgetting. As a result of the analysis, the author concludes that the transfer of individual employee knowledge for further use in automated systems should be based on the use of semantic models of corporate knowledge built using industry ontologies. The article describes the author’s proposed process for creating semantic knowledge models for the transfer of employee knowledge. The materials of the work are applicable for the development of practical ways and methods for identifying, further preserving, and effectively using the personal knowledge of employees during the transition to Industry 4.0 technologies.

Machine Learning and Applications An International JournalVol. 12(3)
Openalex Percentile: Top 59%
Digital Transformation in Industry
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