- Rising energy costs
- Little understanding of how and where energy is being used
- Carbon and sustainability goals
- Complicated tariffs
- Market competitiveness pressures
- Non intrusive connectivity
- Energy usage breakdown visualised in detail
- Analytics converting data into insights
- Expert advice to implement changes
- Understanding of how energy is being used leading to cost saving initiatives
- Ability to accurately calculate energy costs by product or batch
- Selecting optimal electricity tariffs for baseload and variable usage
- Allows analysis of peak load to minimise load based network charges
- Enable some electrical loads to be moved to lower priced half hour periods
- Ranking of loads to encourage operators and managers to focus on the biggest opportunities
- Ability to connect and digitise the whole factory to look at use cases over and above energy usage
- Supports carbon and sustainability goals
- Energy usage information behind the meter
- Non intrusive installation to help avoid downtime during implementation
- Real time visualisation of energy usage
- Breakdown of where and how energy is used in your facilities
- Out of the box analytics to convert raw data into actionable insights
- Simple upgrade to unleash further tools to create your own dashboards and analytics
Providing asset level real time electricity usage
- Manufacture high performance engine components
- Supplying the automotive market
- Using Smartia Energy Analytics to monitor electricity usage of their CNC machines
- Identified savings of 30% on machines in regular use and almost 80% savings on machines that have sporadic usage
Advance warnings 9 months before potential failures and £150k operational savings per turbine.
Predict 90% failures before they occur saving over £100k per composite part and reducing energy and material waste.
Automated defect detection reduced the man power required and therefore reduced the associated costs substantially. It also allowed staff to focus on other business critical tasks.
An automated product quality inspection system which has increased quality levels and saves £20m per plant annually.
£1M savings in a single quarter, and potentially achieving £6M savings within 18 months.
Computer vision based fault detection, automating the inspection process and increasing coverage by over 3 fold.
Detecting scrap in the single grain crystallisation casting process using regression modelling and advanced analytics.
Robotic fulfilment rig that demonstrates how robotics and machine learning can be used to help support staff.
Switched from the regular cutting tool replacement process at every 200 products to a monitored based system that extended the life of a cutting tool by up to 3 times.
Health Indicator application provides early alerts that equipment is degrading and likely to need maintenance.
Power usage effectiveness (PUE) is an important industry metric for measuring the energy efficiency of a data centre. Optimising this can provide huge cost savings of up to 20% in this case.
Condition-based tool replacement using data and machine learning to inform decisions. Leading to a reduction in cost and extending the life of the tools.
Smartia’s MAIO will enable AI at the edge, supporting privacy-preserving distributed learning. Use of AI for cyber security to detect attacks and improve the security of large scale IIoT systems.