The customer
Saint Jean, a historic player in fresh pasta in France, has 5 production sites in the Auvergne Rhône Alpes region. Specializing in ravioli, fresh pasta, gnocchi and crozets, it produces over 18,000 tons a year and employs 500 people. The company is investing to triple its production capacity, and is committed to environmental issues such as eco-design, solar panels, energy recovery and sustainable resource management.
- Saint Jean: 500 employees, 18,000 tons of products, sales of 115 million euros
- Project start-up: 2024
- Deployment on all production sites
The challenge
Against a backdrop of strong growth, Saint Jean wanted to take up several key challenges to support the industrialization of its sites. The priority was tooptimize the availability of production lines, while keeping maintenance and energy consumption costs under control. The density of equipment to be monitored, such as air handling units, chillers, steam boilers and heat pumps, makes these operations complex.
Teams were faced with interventions that were often scheduled on a systematic basis, without always having the necessary indicators to anticipate drifts, notably clogged AHU filters, a source of over-consumption and loss of efficiency.
Saint Jean was therefore looking for a solution capable of complementing its existing BMS and CMMS, by providing usable data in real time and long-term analysis tools.
Our answer
BLPredict deployed a tailor-made solution, complementary to the Carl Source CMMS and BMS, to enable Saint Jean to better control its maintenance operations.
The aim was to integrate real-time monitoring of critical equipment, by cross-referencing data from drives, fans and environmental sensors.
BLPredict has made it possible to automate the generation of interventions, while providing technicians with new indicators:
- monitoring of excess energy consumption due to filter clogging,
- performance comparison between equipment,
- defrost analysis, monitoring of untimely PAC restarts.
The integration of contextual data such as weather or site pollution levels has enhanced these analyses and facilitated decision-making.
All the data collected – more than 2.3 million per day from 60 pieces of equipment and 2 sites – is used to anticipate drifts and optimize settings.
Deployment
- Set up monitoring on 60 equipment units at 2 sites
- Collects 2.3 million data records/day
- Multi-parameter analysis: equipment comparison, long-term monitoring
- Automated alerts to anticipate drifts (BMS pressure switches, overconsumption, restarts, etc.).
- Integration with CMMS to create maintenance orders
Some benefits
Improving production line availability
Data enhancement: integration into technical and maintenance processes
What next?
Saint Jean continues its partnership with BLPredict to extend the scope of its analyses. New projects underway include vibration monitoring of choppers and a rolling mill, integration of boiler room and compressed air data, and automated particle monitoring in production areas.
The aim remains the same: to take the digital transformation of site maintenance and energy management one step further, in the interests of industrial and environmental performance.
