US 11,940,782 B2
Product performance prediction modeling to predict final product performance in case of device exception
Jing Wang, Chengdu (CN); Hu Chen, Chengdu (CN); and Zhi Yong Peng, Chengdu (CN)
Assigned to SIEMENS AKTIENGESELLSCHAFT, Munich (DE)
Appl. No. 17/261,614
Filed by Siemens Aktiengesellschaft, Munich (DE)
PCT Filed Jul. 26, 2018, PCT No. PCT/CN2018/097256
§ 371(c)(1), (2) Date Jan. 20, 2021,
PCT Pub. No. WO2020/019256, PCT Pub. Date Jan. 30, 2020.
Prior Publication US 2021/0263508 A1, Aug. 26, 2021
Int. Cl. G05B 19/418 (2006.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01)
CPC G05B 19/41875 (2013.01) [G06N 5/04 (2013.01); G06N 20/00 (2019.01); G05B 2219/32194 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A product performance prediction modeling method, comprising:
acquiring first sample data, the first sample data including first device outlier data generated in a process of manufacturing a product by a device;
acquiring product information and a production line configuration simulation parameter of a production line relating to location of the device, the product information being product information of the product manufactured by the production line;
selecting a product performance simulation model to perform a simulation test on a performance of the product to obtain product performance simulation data, wherein the product performance simulation model is selected according to the first device outlier data, the production line configuration simulation parameter and the product information; and
inputting the first device outlier data, the production line configuration simulation parameter, the product information and the product performance simulation data into a machine learning model to perform machine learning training to obtain a product performance prediction model.