EWMA-PRIM: Process optimization based on time-series process operational data using the exponentially weighted moving average and patient rule induction method

作者：

Highlights：

• Process operational big data is analyzed for optimizing a non-stationary process.

• The proposed EWMA-PRIM outperforms ordinary PRIM for the non-stationary process.

• The proposed method obtains optimal intervals where current performance is better.

摘要

•Process operational big data is analyzed for optimizing a non-stationary process.•The proposed EWMA-PRIM outperforms ordinary PRIM for the non-stationary process.•The proposed method obtains optimal intervals where current performance is better.

论文关键词：Time-series,Big data,Manufacturing process optimization,Data mining,Patient rule induction method,Exponentially weighted moving average

论文评审过程：Received 14 April 2021, Revised 2 January 2022, Accepted 22 January 2022, Available online 30 January 2022, Version of Record 5 February 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116606