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

<p>In today’s society, which attaches great importance to humanization, human factors engineering has become a hot topic of research in industrial engineering to improve enterprises and factory sites. This paper aims to optimize the efficiency of industrial engineering by adopting industrial engineering (IE) methods, combing the methodological study of the production process and applying job measurement methods to improve engineering efficiency. The study results show that after the improvement of two-handed operation, the left and right-handed operation time is reduced to 25.78 seconds, which is 31.8% lower compared to the pre-improvement period. The overall process was optimized to minimize the bottleneck beat time from 1.379 seconds/piece to 1.333 seconds/piece, and the maximum production capacity increased from 51,308 pieces/day to 52,204 pieces/day. In addition, labor requirements in the industrial workflow were reduced by 20%, from 610 to 486 people. As for the improvement of the operating environment, the noise levels were kept below 73.9 dB(A), especially for the dust collector, which was significantly reduced from 86.4 dB(A) to 72.9 dB(A). This optimization of industrial engineering and its operating environment by applying human factors engineering principles ensures the production quality. It achieves the maximum output with minimum resource input, laying a solid foundation for the continuous optimization of industrial engineering.</p>
</abstract>

In today’s society, which attaches great importance to humanization, human factors engineering has become a hot topic of research in industrial engineering to improve enterprises and factory sites. This paper aims to optimize the efficiency of industrial engineering by adopting industrial engineering (IE) methods, combing the methodological study of the production process and applying job measurement methods to improve engineering efficiency. The study results show that after the improvement of two-handed operation, the left and right-handed operation time is reduced to 25.78 seconds, which is 31.8% lower compared to the pre-improvement period. The overall process was optimized to minimize the bottleneck beat time from 1.379 seconds/piece to 1.333 seconds/piece, and the maximum production capacity increased from 51,308 pieces/day to 52,204 pieces/day. In addition, labor requirements in the industrial workflow were reduced by 20%, from 610 to 486 people. As for the improvement of the operating environment, the noise levels were kept below 73.9 dB(A), especially for the dust collector, which was significantly reduced from 86.4 dB(A) to 72.9 dB(A). This optimization of industrial engineering and its operating environment by applying human factors engineering principles ensures the production quality. It achieves the maximum output with minimum resource input, laying a solid foundation for the continuous optimization of industrial engineering.

Analysis and optimization of industrial engineering and management operating environment based on human factors engineering

Applied Mathematics and Nonlinear Sciences

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

In today’s society, which attaches great importance to humanization, human factors engineering has become a hot topic of research in industrial engineering to...

Analysis and optimization of industrial engineering and management operating environment 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-2024-0530

Parole chiave
Human factors engineering, Industrial engineering, IE, job measurement, Industrial operating environment

© 2024 Renzhou Ji, published by Sciendo

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

Analysis and optimization of industrial engineering and management operating environment 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-2024-0530

Parole chiaveHuman factors engineering, Industrial engineering, IE, job measurement, Industrial operating environment

© 2024 Renzhou Ji, published by Sciendo

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

Parole chiave
Human factors engineering, Industrial engineering, IE, job measurement, Industrial operating environment