Responsive Additive Manufacturing to Overcome Natural and Attack-based disruption (RAMONA)
Dr Phil Davies is working with colleagues in the University of Warwick and University of Surrey, with funding over £1 million by the EPSRC, to create tools and techniques for resilient additive manufacturing. This research will address how to develop effective techniques to detect disruption, how to effectively and accurately analyse this disruption, and how to respond to disruption through reconfigured manufacture.
Funder: EPSRC
Principle Investigator: Dr Greg Gibbons (WMG)
Co-Investigators: Prof. Carsten Maple (WMG), Dr Gregory Epiphaniou (WMG), Prof. Mark Williams (WMG), Prof. Glenn Parry (Surrey), and Dr Phil Davies (Reading)
Value: ~£1 million
Disruption resilient manufacturing is becoming increasingly important, with the current COVID-19 pandemic bringing this to the fore. Whilst COVID-19 was a natural disaster, the increasing digitisation of supply chains and manufacturing processes means further widespread challenges with respect to malicious activity and cyber attacks that can cause significant disruption. Whilst the news suggests many of these take place on digital platforms or within financial or health institutions, there is growing evidence that cyber-physical systems, such as manufacturing, are becoming more regularly targeted and therefore subject to disruption. For instance, a recent Cisco (2017) report found that 28% of manufacturers across 13 countries suffered cyber-attacks that resulted in revenue loss, with this set to increase as digitisation of the manufacturing industry increases. Therefore, it is crucial to identify methods of both securing against and re-configuring if needed the point of production within the supply network should a string within the supply network become compromised.
This research focuses specifically on additive manufacturing supply chains as part of a responsive manufacturing system, to address the significant security challenges within manufacturing supply chains to ensure greater levels of supply chain resilience for both UK and global manufacturing. In particular, this would address the call from Additive Manufacturing UKs (2017) UK National Strategy Report for AM, where they highlighted a critical challenge is to address security related challenges in AM production, with the importance of this increasing if production is to be distributed and responsive to emergent changes within the system, such as an adversary infiltrating elements of the supply chain.
To support such rapid reconfiguration of the manufacturing system across the supply network, our vision is to create a practicable methodology for manufacturing systems that can detect a threat and reconfigure themselves rapidly in the presence of an adversary. The work packages developed as part of this research further address the critical challenges outlined above and underpin our vision through the development of 'double lock' system, of physical hash on the product and digital hash on component files secured against a distributed ledger technology, that can be scaled across and tailored to different SC configurations, allowing manufacturing to be responsive to disruption and enable greater resilience and agility in UK manufacturing SCs. This proposal also considers both the current state of the art in academic research, and the fundamental needs and applied research from industry. This research is transformative as it meets the twin hurdle of academic rigour and industrial relevance.
To create tools and techniques for resilient additive manufacturing this research will address the following challenges:
- How to develop effective techniques to detect disruption
- How to effectively and accurately analyse the disruption
- How to respond to disruption through reconfigured manufacture
Time frame: September 2021 until mid 2024
Authors |
---|
This site uses cookies to improve your user experience. By using this site you agree to these cookies being set. You can read more about what cookies we use here. If you do not wish to accept cookies from this site please either disable cookies or refrain from using the site.