In today’s interconnected production chain, strategic maintenance gives you a significant competitive advantage.  SparkBeyond’s Discovery platform identifies and mitigates the root causes of asset failure by analyzing thousands of multi-layered patterns found in breakdowns, identifying high-risk components and recommending prescriptive action.  

To detect anomalies and unknown events in machinery, Discovery leverages historic and real time data on process failures, process/component variables (temperature, pressure etc), indirect parameters (raw materials, vehicle/road characteristics, fuel mix) and sensor information (speed, rotation).  Using this data, the platform generates targeted failure prediction insights and recommends highly reliable preventative actions and optimal maintenance schedules.

Results, ready within hours and clearly visualized to enhance process understanding, update automatically.  Outcomes include better productivity, extended asset lifetime, streamlined spare parts management, lower fuel costs and fewer environmental and safety risks.

Applicable across discrete industries like CPG, automotive, electronics, textiles and aerospace and process industries like food and beverage, chemicals, oil & gas and pharma, predictive maintenance dramatically cuts waste in raw material, energy, labor and machine time.

With sustainability and environmental protection fast becoming a core strategic priority, a FTSE 100 company sought to improve operations continuity by predicting water pollution build-up.  By integrating Discovery with the company’s legacy software and data architecture, SparkBeyond discovered ‘hidden’ signals in previously unexplored geospatial and mapping data to produce:

• A dynamic risk score for each pumping station component.
• Explainable models, showing asset failure drivers of pollution.
• Hundreds of novel insights after just three days.
  

AI-powered technology helps companies organize, implement and scale maintenance to maximize runtime, ease logistics and grow revenues.