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Article

Composition Optimization of Coating Machine Oven Manufacturing Services Based on Improved Sparrow Search Algorithm

1
Faculty of Printing, Packaging Engineering and Digital Media Technology, Xi’an University of Technology, Xi’an 710048, China
2
Shanghai Baosight Software Co., Ltd., Shanghai 201203, China
*
Author to whom correspondence should be addressed.
Coatings 2025, 15(6), 636; https://doi.org/10.3390/coatings15060636
Submission received: 27 April 2025 / Revised: 15 May 2025 / Accepted: 21 May 2025 / Published: 25 May 2025
(This article belongs to the Section Surface Characterization, Deposition and Modification)

Abstract

Aiming at the problem of the low collaborative efficiency of outsourced processing of coating machine oven parts under the network collaborative manufacturing mode, this paper proposes a composition optimization method for coating machine oven-manufacturing services based on an improved sparrow search algorithm. We establish a framework for the service composition optimization problem on the oven manufacturing service platform; complete an evaluation of the manufacturing service quality of service indicators (QoS) and energy consumption indicators; construct a dual-objective service composition optimization mathematical model considering the QoS and energy consumption indicators; and embed the Tent chaotic mapping, elite reverse learning, and Lévy flight improvement differential evolution strategies into the sparrow search algorithm. We named this algorithm the LCSSA_DE algorithm, using it to solve the mathematical model of the manufacturing service combination problem of coating machine ovens, and obtain the optimal manufacturing service combination recommendation scheme. The experimental results demonstrate that this algorithm can effectively improve the convergence speed compared with the suboptimal multi-objective artificial vulture optimization algorithm (MOAVOA), with the average convergence time improved by 7.26%, avoiding falling into the local optimum during the search, while 69%–77% of the test points are more in line with the preference criteria of the Pareto frontier, and can be adapted to the optimization of the coating machine oven manufacturing service composition optimization problem at different scales.
Keywords: coating machine ovens; network collaborative manufacturing; crowdsourcing; composition optimization; improved sparrow search algorithm coating machine ovens; network collaborative manufacturing; crowdsourcing; composition optimization; improved sparrow search algorithm

Share and Cite

MDPI and ACS Style

Gao, Z.; Liu, S.; Zhu, L.; Li, C.; Cao, Y.; Shi, G. Composition Optimization of Coating Machine Oven Manufacturing Services Based on Improved Sparrow Search Algorithm. Coatings 2025, 15, 636. https://doi.org/10.3390/coatings15060636

AMA Style

Gao Z, Liu S, Zhu L, Li C, Cao Y, Shi G. Composition Optimization of Coating Machine Oven Manufacturing Services Based on Improved Sparrow Search Algorithm. Coatings. 2025; 15(6):636. https://doi.org/10.3390/coatings15060636

Chicago/Turabian Style

Gao, Zhenjie, Shanhui Liu, Langze Zhu, Chaoyang Li, Yangzhen Cao, and Gan Shi. 2025. "Composition Optimization of Coating Machine Oven Manufacturing Services Based on Improved Sparrow Search Algorithm" Coatings 15, no. 6: 636. https://doi.org/10.3390/coatings15060636

APA Style

Gao, Z., Liu, S., Zhu, L., Li, C., Cao, Y., & Shi, G. (2025). Composition Optimization of Coating Machine Oven Manufacturing Services Based on Improved Sparrow Search Algorithm. Coatings, 15(6), 636. https://doi.org/10.3390/coatings15060636

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