{"id":42172,"date":"2025-06-23T13:38:28","date_gmt":"2025-06-23T11:38:28","guid":{"rendered":"https:\/\/blpredict.com\/blog\/project\/la-maison-saint-jean\/"},"modified":"2025-06-25T12:03:36","modified_gmt":"2025-06-25T10:03:36","slug":"la-maison-saint-jean","status":"publish","type":"project","link":"http:\/\/blpredict.com\/en\/blog\/project\/la-maison-saint-jean\/","title":{"rendered":"La Maison Saint Jean"},"content":{"rendered":"\t\t
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The customer<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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La Maison Saint Jean<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Saint Jean<\/strong>, a historic player in fresh pasta in France, has 5 production sites in the Auvergne Rh\u00f4ne 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. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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  • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tSaint Jean: 500 employees, 18,000 tons of products, sales of 115 million euros<\/strong><\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
  • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tProject start-up: 2024<\/strong><\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
  • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tDeployment on all production sites<\/strong><\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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    The challenge<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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    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<\/strong>, while keeping<\/strong> maintenance and energy consumption costs under control<\/strong>. The density of equipment to be monitored, such as air handling units, chillers, steam boilers and heat pumps, makes these operations complex. <\/p>

    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.<\/p>

    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.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    Our answer<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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    BLPredict deployed a tailor-made solution<\/strong>, complementary to the Carl Source CMMS and BMS, to enable Saint Jean to better control its maintenance operations.<\/p>

    The aim was to integrate real-time monitoring of critical equipment, by cross-referencing data from drives, fans and environmental sensors.<\/p>

    BLPredict has made it possible to automate the generation of interventions, while providing technicians with new indicators:<\/p>

    • monitoring of excess energy consumption due to filter clogging,<\/li>
    • performance comparison between equipment,<\/li>
    • defrost analysis, monitoring of untimely PAC restarts.<\/li><\/ul>

      The integration of contextual data such as weather or site pollution levels has enhanced these analyses and facilitated decision-making.<\/p>

      All the data collected – more than 2.3 million per day from 60 pieces of equipment and 2 sites – is used to anticipate drifts<\/strong> and optimize settings<\/strong>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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      Deployment<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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      • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tSet up monitoring on 60 equipment units<\/strong> at 2 sites<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
      • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tCollects 2.3 million data records\/day<\/strong><\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
      • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tMulti-parameter analysis: equipment comparison, long-term monitoring<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
      • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tAutomated alerts to anticipate drifts (BMS pressure switches, overconsumption, restarts, etc.).<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t
      • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tIntegration with CMMS<\/strong> to create maintenance orders<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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        Some benefits<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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        Improving production line availability<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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        <\/path><\/path><\/svg><\/div><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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        \n\t\t\t\t\t\t\t\t\tReduce energy costs by detecting over-consumption\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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        <\/path><\/path><\/svg><\/div><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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        \n\t\t\t\t\t\t\t\t\tAnticipation of interventions on AHUs and PACs\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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        <\/path><\/path><\/svg><\/div><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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        \n\t\t\t\t\t\t\t\t\tOptimizing equipment operation: cadence, settings, defrosting\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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        <\/path><\/path><\/svg><\/div><\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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        Data enhancement: integration into technical and maintenance processes<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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        What next?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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        Saint Jean continues its partnership with BLPredict to extend the scope of its analyses<\/strong>. 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. <\/p>

        The aim remains the same: to take the digital transformation of<\/strong> site maintenance<\/strong> and energy management<\/strong> one step further, in the interests of industrial and environmental performance<\/strong>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

        Optimize energy efficiency at Le Havre’s Oc\u00e9ane Stadium<\/p>\n","protected":false},"featured_media":42163,"template":"","meta":[],"project_category":[186],"project_tag":[154],"class_list":["post-42172","project","type-project","status-publish","has-post-thumbnail","hentry","project_category-industrial","project_tag-cover-project"],"yoast_head":"\nLa Maison Saint Jean - BLPredict<\/title>\n<meta name=\"description\" content=\"Succ\u00e8s client BLPredict : Optimize energy efficiency at Le Havre's Oc\u00e9ane Stadium (La Maison Saint Jean)\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"http:\/\/blpredict.com\/en\/blog\/project\/la-maison-saint-jean\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"La Maison Saint Jean - BLPredict\" \/>\n<meta property=\"og:description\" content=\"Succ\u00e8s client BLPredict : Optimize energy efficiency at Le Havre's Oc\u00e9ane Stadium (La Maison Saint Jean)\" \/>\n<meta property=\"og:url\" content=\"http:\/\/blpredict.com\/en\/blog\/project\/la-maison-saint-jean\/\" \/>\n<meta property=\"og:site_name\" content=\"BLPredict : plateforme IIoT de gestion intelligente des \u00e9quipements\" \/>\n<meta property=\"article:modified_time\" content=\"2025-06-25T10:03:36+00:00\" \/>\n<meta property=\"og:image\" content=\"http:\/\/blpredict.com\/wp-content\/uploads\/2025\/06\/saint-jean.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1280\" \/>\n\t<meta property=\"og:image:height\" content=\"720\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"http:\\\/\\\/blpredict.com\\\/en\\\/blog\\\/project\\\/la-maison-saint-jean\\\/\",\"url\":\"http:\\\/\\\/blpredict.com\\\/en\\\/blog\\\/project\\\/la-maison-saint-jean\\\/\",\"name\":\"La Maison Saint Jean - 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