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A digital twin–driven method for online quality control in process industry

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Abstract

To ensure the stability of product quality and production continuity, quality control is drawing increasing attention from the process industry. However, current methods cannot meet requirements with regard to time series data, high coupling parameters, delayed data acquisition, and ambiguous operation control. A digital twin–driven (DTD) method is proposed for real-time monitoring, evaluation, and optimization of process parameters that are strongly related to product quality. Based on a process simulation model, production status information and quality related data are obtained. Combined with an improved genetic algorithm (GA), a time sequential prediction model of bidirectional gated recurrent unit (bi-GRU) with attention mechanism (AM) is built to flexibly allocate parameter weights, accurately predict product quality, timely evaluate technical process, and rapidly generate optimized control plans. A typical case study and relevant field tests from the process industry are presented to prove the effectiveness of the method. Results indicate that the proposed method clearly outperforms its competitors.

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Availability of data and material

The datasets and technical materials generated and analyzed during the current study are not publicly available due to corporate security and we cannot disclose it.

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Funding

This research is supported by the National Natural Science Foundation of China (No. 51975521).

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Authors and Affiliations

  1. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Zhejiang 310027, Hangzhou, People’s Republic of China

    Xiaoyang Zhu & Yangjian Ji

  2. Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, Zhejiang University, Zhejiang 310027, Hangzhou, People’s Republic of China

    Xiaoyang Zhu & Yangjian Ji

  3. Department of Industrial and System Engineering, Zhejiang University, Zhejiang 310027, Hangzhou, People’s Republic of China

    Xiaoyang Zhu & Yangjian Ji

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  1. Xiaoyang Zhu
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Zhu, X., Ji, Y. A digital twin–driven method for online quality control in process industry. Int J Adv Manuf Technol 119, 3045–3064 (2022). https://doi.org/10.1007/s00170-021-08369-5

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