Toggle Main Menu Toggle Search

Open Access padlockePrints

A quality by design approach to process plant cleaning

Lookup NU author(s): Professor Elaine Martin, Professor Gary Montague

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Abstract

The cleaning of process plant has traditionally been an activity that has been carried out in open-loop mode, with confirmation of cleanliness achieved through off-line sample assessment. Such strategies have partly arisen as the depth of scientific understanding of the cleaning process has been limited. With deeper understanding through the tracking and prediction of cleaning progression, more sophisticated approaches can be adopted allowing the timely termination of cleaning operations. This paper discusses the component needs of the improved system. At its heart is the need to use appropriate measurement devices for the soil of interest to measure the current process condition and to derive predictive strategies to specify when to terminate cleaning. Results from a case study application on the cleaning of a toothpaste pilot plant demonstrate the concepts. The use of spectroscopic measurements is contrasted with more traditional measurements such as turbidity to track the cleaning profile. Improvement is not achieved simply through better measurement, algorithmic methods for measurement enhancement and forecasting to predict end point of cleaning are both necessary in order to achieve the termination of cleaning operations in a timely manner. The capability to perform both these tasks is considered using the experimental cleaning case study.


Publication metadata

Author(s): Martin EB, Montague GA, Robbins P

Publication type: Article

Publication status: Published

Journal: Chemical Engineering Research and Design

Year: 2013

Volume: 91

Issue: 6

Pages: 1095-1105

Print publication date: 01/06/2013

Online publication date: 29/01/2013

Acceptance date: 22/01/2013

ISSN (print): 0263-8762

ISSN (electronic): 1744-3563

Publisher: Elsevier

URL: http://dx.doi.org/10.1016/j.cherd.2013.01.010

DOI: 10.1016/j.cherd.2013.01.010


Altmetrics

Altmetrics provided by Altmetric


Share