Energy Analytics
Understanding ENERGY USAGE across assets, products and services
Behind The Meter
Challenges and Pressures
- Rising energy costs
- Little understanding of how and where energy is being used
- Carbon and sustainability goals
- Complicated tariffs
- Market competitiveness pressures
Solution
- Non intrusive connectivity
- Energy usage breakdown visualised in detail
- Analytics converting data into insights
- Expert advice to implement changes
Benefits
- 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
Features
- 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
Reducing energy bills
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
Our Projects
Helping industrial companies harness the power of AI. Our consultative approach to automating and enhancing industrial operations allows us to deploy customised AI solutions that deliver tangible improvements to production efficiency, machine uptime, maintenance scheduling and quality control applications.
Predictive Maintenance
Advance warnings 9 months before potential failures and £150k operational savings per turbine.
Predictive Maintenance
Predictive Failure Detection
Predict 90% failures before they occur saving over £100k per composite part and reducing energy and material waste.
Predictive Failure Detection
Automated Defect Detection
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.
Automated Defect Detection
Automated Quality Inspection
An automated product quality inspection system which has increased quality levels and saves £20m per plant annually.
Automated Quality Inspection
Inventory Optimisation
£1M savings in a single quarter, and potentially achieving £6M savings within 18 months.
Inventory Optimisation
Fault Detection
Computer vision based fault detection, automating the inspection process and increasing coverage by over 3 fold.
Fault Detection
Scrap Reduction
Detecting scrap in the single grain crystallisation casting process using regression modelling and advanced analytics.
Scrap Reduction
Smart Robotics Object Detection
Robotic fulfilment rig that demonstrates how robotics and machine learning can be used to help support staff.
Smart Robotics Object Detection
Ultra Precision Manufacturing
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.
Ultra Precision Manufacturing
Preventive Maintenance Support
Health Indicator application provides early alerts that equipment is degrading and likely to need maintenance.
Preventive Maintenance Support
Energy Usage Optimisation
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.
Energy Usage Optimisation
Tool Life Optimisation
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.
Tool Life Optimisation
AI-based Security at the Edge
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.
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