Exploring the Use of Design of Experiments in Industrial Processes Operating Under Closed-Loop Control: Experimentation in closed-loop systems

Francesca Capaci, Murat Kulahci, Erik Vanhatalo

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Abstract

Industrial manufacturing processes often operate under closed-loop control, where automation aims to keep important process variables at their set-points. In process industries such as pulp, paper, chemical and steel plants, it is often hard to find production processes operating in open loop. Instead, closed-loop control systems will actively attempt to minimize the impact of process disturbances. However, we argue that an implicit assumption in most experimental investigations is that the studied system is open loop, allowing the experimental factors to freely affect the important system responses. This scenario is typically not found in process industries. The purpose of this article is therefore to explore issues of experimental design and analysis in processes operating under closed-loop control and to illustrate how Design of Experiments can help in improving and optimizing such processes. The Tennessee Eastman challenge process simulator is used as a test-bed to highlight two experimental scenarios. The first scenario explores the impact of experimental factors that may be considered as disturbances in the closed-loop system. The second scenario exemplifies a screening design using the set-points of controllers as experimental factors. We provide examples of how to analyze the two scenarios. 
Original languageEnglish
JournalQuality and Reliability Engineering International
Volume33
Issue number7
Pages (from-to)1601-1614
Number of pages14
ISSN0748-8017
DOIs
Publication statusPublished - 2017

Bibliographical note

This is an open access article under the terms of the Creative Common Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Keywords

  • Design of Experiments
  • Engineering control
  • Feedback adjustment
  • Simulation
  • Tennessee Eastman process

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