<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper proposes an innovative management optimization method for the challenges facing the management of industrial enterprises in the context of the current rapid development of the industrial economy. The article combines human factors engineering and lean production theory to optimize the management efficiency and effectiveness of industrial enterprises. Considering the complexity of industrial environments, a personnel identification system and a tracking system are constructed in the study to achieve more effective staff management. To comprehensively assess the management effectiveness, the article combines the fuzzy synthesis method to build an evaluation model for the management effectiveness of industrial enterprises. The empirical study shows that the optimization method significantly improves the productivity: the working hours are reduced from 210 hours to 150 hours, the torso rotational and bending forces are reduced by about 54% and 45%, respectively, and the troops on each joint are reduced by about 59% on average. The overall optimization of the model has an affiliation value of 0.53, indicating that the management effect is evaluated as good. The data fully proved the effectiveness of the management optimization method for industrial enterprises proposed in this paper in increasing productivity and improving working conditions.</p>
</abstract>

This paper proposes an innovative management optimization method for the challenges facing the management of industrial enterprises in the context of the current rapid development of the industrial economy. The article combines human factors engineering and lean production theory to optimize the management efficiency and effectiveness of industrial enterprises. Considering the complexity of industrial environments, a personnel identification system and a tracking system are constructed in the study to achieve more effective staff management. To comprehensively assess the management effectiveness, the article combines the fuzzy synthesis method to build an evaluation model for the management effectiveness of industrial enterprises. The empirical study shows that the optimization method significantly improves the productivity: the working hours are reduced from 210 hours to 150 hours, the torso rotational and bending forces are reduced by about 54% and 45%, respectively, and the troops on each joint are reduced by about 59% on average. The overall optimization of the model has an affiliation value of 0.53, indicating that the management effect is evaluated as good. The data fully proved the effectiveness of the management optimization method for industrial enterprises proposed in this paper in increasing productivity and improving working conditions.

An applied study of industrial enterprise engineering and management based on human factors engineering

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper proposes an innovative management optimization method for the challenges facing the management of industrial enterprises in the context of the...

An applied study of industrial enterprise engineering and management based on human factors engineering

Pubblicato online: 26 feb 2024

Pagine: -

Ricevuto: 12 gen 2024

Accettato: 21 gen 2024

DOI: https://doi.org/10.2478/amns-2024-0536

Parole chiave
Human factors engineering, Lean production, Personnel identification system, Fuzzy synthesis, Industrial enterprise management

© 2023 Lixia Niu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

An applied study of industrial enterprise engineering and management based on human factors engineering

Pubblicato online: 26 feb 2024

Pagine: -

Ricevuto: 12 gen 2024

Accettato: 21 gen 2024

DOI: https://doi.org/10.2478/amns-2024-0536

Parole chiaveHuman factors engineering, Lean production, Personnel identification system, Fuzzy synthesis, Industrial enterprise management

© 2023 Lixia Niu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Human factors engineering, Lean production, Personnel identification system, Fuzzy synthesis, Industrial enterprise management