A knowledge-based system for numerical design of experiments processes in mechanical engineering

作者：

Highlights：

• An architecture for numerical design of experiment configuration is proposed.

• A bayesian network with a “multi-net” strategy is proposed.

• Models are trained from historical data and expert knowledge.

• The performances of the proposed method are validated through a case study.

摘要

•An architecture for numerical design of experiment configuration is proposed.•A bayesian network with a “multi-net” strategy is proposed.•Models are trained from historical data and expert knowledge.•The performances of the proposed method are validated through a case study.

论文关键词：Knowledge based system,Numerical design of experiments,Bayesian network

论文评审过程：Received 1 May 2018, Revised 25 August 2018, Accepted 4 January 2019, Available online 7 January 2019, Version of Record 10 January 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.01.013