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When energy data becomes asset intelligence

Industry: Industrial and Agricultural Systems

  • Predictive Asset Intelligence
  • Cogeneration optimisation
  • Energy market integration

 challenge

FANIN operates complex production lines with highly energy-intensive equipment. Limited visibility into machine behaviour made it difficult to identify avoidable consumption during idle and standby periods and detect early changes in equipment performance.

At the same time, rising electricity costs were putting pressure on production margins, while limited machine-level diagnostics made it harder to anticipate maintenance needs and reduce the risk of unplanned downtime.

 solution

FANIN implemented E-BOOST to bring energy and operational intelligence into a single framework, connecting asset performance with production requirements and energy market dynamics.

The solution combines AI-driven analytics with Veil Energy’s operational guidance, transforming plant data into actionable insights for more informed energy, maintenance, and operational decisions.

E-BOOST supports FANIN in:

  • Monitor machine-level energy performance: Analyse energy performance across critical equipment, including aspirators, compressors, and processing lines, to identify consumption patterns and deviations at asset level.
  • Anticipate asset performance issues: Apply predictive maintenance to the vegetable-oil engine to identify early failure signals, support maintenance planning, and reduce the risk of unplanned downtime.
  • Benchmark idle & standby behaviour: Compare consumption across operating states to identify avoidable energy use and deviations in asset behaviour during idle and standby periods.
  • Optimise CHP against energy market conditions: Dynamically optimise gas CHP operation according to electrical and thermal demand, electricity prices, and gas market data to improve the economics of on-site generation.
  • Bring energy performance into production decisions: Integrate energy KPIs into production planning and operational reviews, supporting corrective actions based on measured asset performance.

 impact

Within a few months, FANIN gained greater control over both energy-intensive assets and maintenance priorities. By combining energy performance analysis with predictive diagnostics, FANIN was able to reduce avoidable consumption and support more targeted maintenance planning. At the same time, real-time CHP optimisation improved the economic management of on-site generation by incorporating both energy demand and market conditions into operational decisions.

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Reduction in energy consumption Through standby optimisation and maintenance schedules

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yearly saving