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Bayesian Network Approach to Customer Requirements to Customized Product Model

Author

Listed:
  • Qin Yang
  • Zhirui Li
  • Haisen Jiao
  • Zufang Zhang
  • Weijie Chang
  • Daozhu Wei

Abstract

Customizing products based on customer needs is an irreversible trend, and many companies strive to provide customized products to customers in less time. Customer requirements are a key factor in the company's ability to provide customized products. In order to better meet customer needs, solve the problem of incomplete and inaccurate expression, and improve the correlation between customized product performance and customer demand, a customized product method based on Bayesian network is proposed. First, the company built a custom product model based on Bayesian networks. According to the model, the customer selects some nodes and their related information. Then, we can accurately predict the final product model through the link tree algorithm, test the customer demand node to determine the focus of the customer's needs, and optimize the model. Finally, an example of a multifunctional nursing bed is used to illustrate the effectiveness of the method.

Suggested Citation

  • Qin Yang & Zhirui Li & Haisen Jiao & Zufang Zhang & Weijie Chang & Daozhu Wei, 2019. "Bayesian Network Approach to Customer Requirements to Customized Product Model," Discrete Dynamics in Nature and Society, Hindawi, vol. 2019, pages 1-16, July.
    • Handle: RePEc:hin:jnddns:9687236
    DOI: 10.1155/2019/9687236
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    Cited by:

    1. Dominika Siwiec & Andrzej Pacana, 2021. "A Pro-Environmental Method of Sample Size Determination to Predict the Quality Level of Products Considering Current Customers’ Expectations," Sustainability, MDPI, vol. 13(10), pages 1-22, May.
    2. André Souza Oliveira & Bruno Caetano dos Santos Silva & Cristiano Vasconcellos Ferreira & Renelson Ribeiro Sampaio & Bruna Aparecida Souza Machado & Rodrigo Santiago Coelho, 2021. "Adding Technology Sustainability Evaluation to Product Development: A Proposed Methodology and an Assessment Model," Sustainability, MDPI, vol. 13(4), pages 1-22, February.

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