SCI-FI: SCalable, Intelligent condition monitoring for Foundation Industries

Proper maintenance in domestic Foundation Industries is crucial for everything that matters: productivity, product quality, reliable deliveries and safe working environments. However, in responding to the demands of global competitions, and more recently the effects of COVID-19, management teams have been forced to make difficult decisions to reduce costs.

This has resulted in significant cuts to maintenance budgets, which are often seen purely as costs rather than investments. This has resulted in staff reductions, cancellation of third-party maintenance contracts and under-maintained machines with the inevitable consequences for productivity and energy and resource efficiency.

There is a pressing need for automated condition monitoring systems that help maintenance teams sustain their effectiveness with fewer resources. Such systems should scale the expertise of the maintenance team, allowing them to manage more machines with fewer people. They should help them optimise machine performance, avoid unplanned downtime and understand the root causes of failures.

The SCI-FI project is about adapting a cost-effective approach to automated condition monitoring (CM) and prognostics (PdM), that has been proven in the automotive sector, developed specifically for the needs of metal (Tata) and paper (Smurfit-Kappa) manufacturing. It involves taking techniques, algorithms and user interfaces that were developed for the kinds of discrete, standalone machines common in automotive and adapting them for the coupled machines and processes that predominate in Foundation Industries.

This system would help manufacturers in domestic Foundation Industries become more competitive by reducing both CAPEX and OPEX expenditure through more efficient and more effective maintenance strategies.