Bogle, IDL;
(2017)
A Perspective on Smart Process Manufacturing Research Challenges for Process Systems Engineers.
Engineering
, 3
(2)
pp. 161-165.
10.1016/J.ENG.2017.02.003.
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Abstract
The challenges posed by smart manufacturing for the process industries and for process systems engineering (PSE) researchers are discussed in this article. Much progress has been made in achieving plant- and site-wide optimization, but benchmarking would give greater confidence. Technical challenges confronting process systems engineers in developing enabling tools and techniques are discussed regarding flexibility and uncertainty, responsiveness and agility, robustness and security, the prediction of mixture properties and function, and new modeling and mathematics paradigms. Exploiting intelligence from big data to drive agility will require tackling new challenges, such as how to ensure the consistency and confidentiality of data through long and complex supply chains. Modeling challenges also exist, and involve ensuring that all key aspects are properly modeled, particularly where health, safety, and environmental concerns require accurate predictions of small but critical amounts at specific locations. Environmental concerns will require us to keep a closer track on all molecular species so that they are optimally used to create sustainable solutions. Disruptive business models may result, particularly from new personalized products, but that is difficult to predict.
| Type: | Article |
|---|---|
| Title: | A Perspective on Smart Process Manufacturing Research Challenges for Process Systems Engineers |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/J.ENG.2017.02.003 |
| Publisher version: | http://doi.org/10.1016/J.ENG.2017.02.003 |
| Language: | English |
| Additional information: | © 2017 THE AUTHORS. Published by Elsevier LTD on behalf of the Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
| Keywords: | Science & Technology, Technology, Engineering, Multidisciplinary, Engineering, Smart manufacturing, Process systems engineering, Uncertainty, Flexibility, Optimization, Model-based control, PROCESS DESIGN, GLOBAL OPTIMIZATION, UNCERTAINTY, MODEL, FRAMEWORK, PROGRAMS, SUPPORT, IMPACT |
| UCL classification: | UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1560478 |
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