Digital Manufacturing

Digital Manufacturing

The fourth industrial revolution is a prime example of a complex global challenge and opportunity, leading to an unprecedented level of transformation.

However this is more than just deploying individual technologies and solutions to improve the efficiency and resilience of individual businesses. Instead, Industry 4.0 leads to a new level of integration across engineering processes, businesses and value chains. The AME digital demonstrator has seen an investment of:

  • Circa £1m in new digital manufacturing hardware and software
  • £400k in a state of the art Festo Digital Factory Lab with a fully connected production line and a digital twin model
  • £300k in software and hardware to conduct research into connected and enhanced workers, these include over 10 software packages, 10 4k depth sensor cameras, 3 cobots, 4 ABB interactive robots, 2 AI computers with high GPU capacity
  • £200k in industrial software, hardware and configuration costs to emulate an entire manufacturing supply chain

The digital demonstrator will be the first high-fidelity digital manufacturing supply chain emulation in the UK which will also leverage £5m of existing equipment in AME. This will enable Industry 4.0 principles to be demonstrated in terms of vertical integration, horizontal integration and end-to-end engineering. The OEM cell is being kitted out with Festo Didactic learning factory equipment using Siemens systems, and content from the Siemens Connected Curriculum will be drawn on and reconfigured into customised learning modules.  These developments will enable our research groups to open up to a wider range of companies throughout the supply chain, offer training at all levels, and host visits and demonstrations for the public.

The five areas of future research taking place in the digital demonstrator include:

Strategic and tactical decision-making levels across individual businesses (E2EE & VI), and across manufacturing value chains (HI), lack both academic and practical consideration. This will advance academic research examining Industry 4.0 at the levels of IT/OT infrastructure, cyber security for connected factories, engineering systems, data-driven technologies and communication systems used to enhance manufacturing productivity.

The demonstrator will be the foundation for research exploring the ongoing transformations in Industry 4.0 and its impacts on businesses’ strategies, organisational principles, and management, and on the societal sphere. In this context, a coherent, cross-disciplinary view on Industry 4.0 and utilising the underlying systemic principles of self-organisation, self-adaptation, and self-learning is crucial to develop new and sustainable business models, and therefore extend the research scope from an operative level of Industry 4.0 utilisation towards tactical and strategic decision making.

Another emerging research area with intersections of Industry 4.0 and strategic decisions is re-designing of the supply chains following the COVID-19 pandemic impacts. Numerous Industry 4.0 technologies such as digital-model-based definitions, advanced robotics and hybrid manufacturing can support localisation of supply chains, which, in turn, can be expected to increase resilience and reduce risks stemming from the existing global network designs.

Procurement, logistics and production decision-making areas use Industry 4.0 technologies fragmentarily. Specifically, production planning and control is influenced by the technical Industry 4.0 infrastructure such as CPS, IoT, additive manufacturing, mobile and collaborative robots, human-machine interaction (HMI) and machine-to-machine (M2M) communication. The digital demonstrator equipment will support research focused on the development and the integration of systems layers in practice to address the limited knowledge on the influences of the human factors at operational, process and system levels.

A strong focus on descriptive analytics, predictive and prescriptive models is urgent. Currently, several analysis and models are available for predicting the impact of change in the operational performance of processes. However, there is a major gap related to understanding and the predictability of the human factors (and societal impact) involved in operations change and within CPS optimisation strategies, e.g., workforce readiness (technical, digital, soft skills). This calls for urgent attention and highlights the need for cross-disciplinary research. Collaborations between engineering, data, computer, social and behavioural sciences is urgently needed to develop cross-disciplinary analysis of the impacts of change by emerging technologies – e.g., embedded mixed reality – to develop human-centred systems. Such systems will unlock a new level of decision-making capabilities in industry, allowing for optimal planning, real-time adaptable decision-making and robust learning systems.

The AME Expansion

A significant expansion of the AME is now underway with financial support from Coventry and Warwickshire Local Enterprise Partnership in order to engage and support the wider UK Manufacturing Value Chain. This involves investment in a new building with an additional 1800 m2 and also investment in new equipment and facilities including new laser manufacturing, data driven metrology, functional materials laboratories and digital manufacturing. The latter particularly will benefit from the creation of a high-fidelity digital manufacturing demonstrator which will consist of a series of physical stations with fully configured digital systems to represent real, individual manufacturing businesses of varying complexity at each point in the value chain – end customer, original equipment manufacturer (OEM), Tier 1 and Tier 2.

The AME expansion investment in infrastructure and capabilities will enable the AME’s progression to its next phase by creating a platform for industrial engagement focused on applied cross-disciplinary research. This is designed to not only advance knowledge in relevant areas of research, but also to address industrial challenges and de-risk investment to encourage technological development and adoption across the manufacturing value chain.

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