<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>In this paper, firstly, based on the application model of optimal scheduling of machining system for green manufacturing, two application models of the energy-saving scheduling model and energy-saving and noise-reducing scheduling model in a multi-model framework are combined, and the resource environment coefficient matrix of the two application models is established as well as the solution process is studied with the parallel machine problem. Then the system's architecture is constructed, and its basic operation flow, functional modules, etc., are designed and conceived. The application of the system is studied in conjunction with a gear machining workshop of a machine tool factory, and the machining system's energy and noise reduction performance is verified based on experiments. The results show that the energy consumption of the machining system is reduced by 0.514 kW-h by machining only the above six gear parts with a small difference in the maximum machining completion time and that the spindle speed has the most significant effect on the machine tool machining noise at a significance level <italic>α</italic> of 0.05. The analysis of this study verifies that the energy-saving and noise-reducing scheduling arrangement method can reduce the system machining energy consumption and noise, which is important for green manufacturing.</p>
</abstract>

In this paper, firstly, based on the application model of optimal scheduling of machining system for green manufacturing, two application models of the energy-saving scheduling model and energy-saving and noise-reducing scheduling model in a multi-model framework are combined, and the resource environment coefficient matrix of the two application models is established as well as the solution process is studied with the parallel machine problem. Then the system's architecture is constructed, and its basic operation flow, functional modules, etc., are designed and conceived. The application of the system is studied in conjunction with a gear machining workshop of a machine tool factory, and the machining system's energy and noise reduction performance is verified based on experiments. The results show that the energy consumption of the machining system is reduced by 0.514 kW-h by machining only the above six gear parts with a small difference in the maximum machining completion time and that the spindle speed has the most significant effect on the machine tool machining noise at a significance level α of 0.05. The analysis of this study verifies that the energy-saving and noise-reducing scheduling arrangement method can reduce the system machining energy consumption and noise, which is important for green manufacturing.

Energy-saving and noise-reducing integrated task allocation model for machining systems and its application

Applied Mathematics and Nonlinear Sciences

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

In this paper, firstly, based on the application model of optimal scheduling of machining system for green manufacturing, two application models of the...

Energy-saving and noise-reducing integrated task allocation model for machining systems and its application

Published Online: Sep 27, 2023

Page range: -

Received: Oct 16, 2022

Accepted: Apr 07, 2023

DOI: https://doi.org/10.2478/amns.2023.2.00383

Keywords
Machining system, Operation process, Energy saving and noise reduction, Scheduling model, Resource and the environmental coefficient matrix.

© 2023 Tao Chen, published by Sciendo

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

Energy-saving and noise-reducing integrated task allocation model for machining systems and its application

Published Online: Sep 27, 2023

Page range: -

Received: Oct 16, 2022

Accepted: Apr 07, 2023

DOI: https://doi.org/10.2478/amns.2023.2.00383

KeywordsMachining system, Operation process, Energy saving and noise reduction, Scheduling model, Resource and the environmental coefficient matrix.

© 2023 Tao Chen, published by Sciendo

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

Keywords
Machining system, Operation process, Energy saving and noise reduction, Scheduling model, Resource and the environmental coefficient matrix.