| Title |
Intelligent Resource Use to Deliver Waste Valorisation and Process Resilience in Manufacturing Environments Moving towards sustainable process manufacturing |
| ID_Doc |
24814 |
| Authors |
Fisher, OJ; Watson, NJ; Escrig, JE; Gomes, RL |
| Title |
Intelligent Resource Use to Deliver Waste Valorisation and Process Resilience in Manufacturing Environments Moving towards sustainable process manufacturing |
| Year |
2020 |
| Published |
Johnson Matthey Technology Review, 64, 1 |
| DOI |
10.1595/205651320X15735483214878 |
| Abstract |
Circular economy (CE) thinking has emerged as a route to sustainable manufacture, with related cradle-to-cradle implications requiring implementation from the design stage. The challenge lies in moving manufacturing environments away from the traditional linear economy paradigm, where materials, energy and water have often been designed to move out of the system and into receivership of waste management bodies after use. Recent applications of industrial digital technologies (IDTs: for example internet of things, data-driven modelling, cyberphysical systems, cloud manufacturing, cognitive computing) to manufacturing may be instrumental in transforming manufacturing from linear to circular. However, although IDTs and CE have been the focus of intensive research, there is currently limited research exploring the relationship between IDTs and the CE and how the former may drive the implementation of CE. This article aims to close the knowledge gap by exploring how an IDT (data-driven modelling) may facilitate and advance CE principles within process manufacturing systems, specifically waste valorisation and process resilience. These applications are then demonstrated through two real-world manufacturing case studies: (a) minimising resource consumption of industrial deaning processes and (b) transforming wastewater treatment plants (WWTPs) into manufacturing centres. |
| Author Keywords |
|
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000541122300013 |
| WoS Category |
Chemistry, Physical |
| Research Area |
Chemistry |
| PDF |
https://doi.org/10.1595/205651320x15735483214878
|