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Product Service System Configuration Based on a PCA-QPSO-SVM Model

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  • Zhaoyi Cui

    (Business School, University of Shanghai for Science and Technology, Shanghai 200093, China)

  • Xiuli Geng

    (Business School, University of Shanghai for Science and Technology, Shanghai 200093, China)

Abstract

To achieve sustainable development and improve market competitiveness, many manufacturers are transforming from traditional product manufacturing to service manufacturing. In this trend, the product service system (PSS) has become the mainstream of supply to satisfy customers with individualized products and service combinations. The diversified customer requirements can be realized by the PSS configuration based on modular design. PSS configuration can be deemed as a multi-classification problem. Customer requirements are input, and specific PSS is output. This paper proposes an improved support vector machine (SVM) model optimized by principal component analysis (PCA) and the quantum particle swarm optimization (QPSO) algorithm, which is defined as a PCA-QPSO-SVM model. The model is used to solve the PSS configuration problem. The PCA method is used to reduce the dimension of the customer requirements, and the QPSO is used to optimize the internal parameters of the SVM to improve the prediction accuracy of the SVM classifier. In the case study, a dataset for central air conditioning PSS configuration is used to construct and test the PCA-QPSO-SVM model, and the optimal PSS configuration can be predicted well for specific customer requirements.

Suggested Citation

  • Zhaoyi Cui & Xiuli Geng, 2021. "Product Service System Configuration Based on a PCA-QPSO-SVM Model," Sustainability, MDPI, vol. 13(16), pages 1-22, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:9450-:d:619911
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    References listed on IDEAS

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    1. Lv, Ya-jun & Wang, Jun-wei & Wang, Julian & Xiong, Cheng & Zou, Liang & Li, Ly & Li, Da-wang, 2020. "Steel corrosion prediction based on support vector machines," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    2. Nicolas Haber & Mario Fargnoli, 2021. "Sustainable Product-Service Systems Customization: A Case Study Research in the Medical Equipment Sector," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
    3. Johannes Matschewsky & Marianna Lena Kambanou & Tomohiko Sakao, 2018. "Designing and providing integrated product-service systems – challenges, opportunities and solutions resulting from prescriptive approaches in two industrial companies," International Journal of Production Research, Taylor & Francis Journals, vol. 56(6), pages 2150-2168, March.
    4. Mario Fargnoli & Nicolas Haber & Tomohiko Sakao, 2019. "PSS modularisation: a customer-driven integrated approach," International Journal of Production Research, Taylor & Francis Journals, vol. 57(13), pages 4061-4077, July.
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    Cited by:

    1. Mario Fargnoli & Nicolas Haber & Massimo Tronci, 2022. "Case Study Research to Foster the Optimization of Supply Chain Management through the PSS Approach," Sustainability, MDPI, vol. 14(4), pages 1-19, February.

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