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Abstract <p>We developed a soft sensor to predict polyvinyl alcohol viscosity and designed process conditions to reach the target range. Using squared and cross terms and time-series data improved prediction accuracy. In the case study, optimal conditions brought off-target products into range.</p> Graphical abstract <p></p>

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Machine learning-based prediction of polyvinyl alcohol product viscosity and design of optimal process conditions

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月15日

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  • Ryota Nomura,
  • Yoshihito Yamauchi,
  • Hiroto Misawa,
  • Kosuke Nishigaya,
  • Satoshi Ooyama,
  • Hiromasa Kaneko

摘要

Abstract

We developed a soft sensor to predict polyvinyl alcohol viscosity and designed process conditions to reach the target range. Using squared and cross terms and time-series data improved prediction accuracy. In the case study, optimal conditions brought off-target products into range.

Graphical abstract