Algist Bruggeman Uses Insights from InfluxDB to Optimize Industrial Processes and Production

3 minutes

Founded in 1884 and located in Ghent, Belgium, Algist Bruggeman supplies fresh, liquid, and dried yeast to industrial, semi-artisanal, and artisanal bakeries, as well as to the beer, wine, and pharma industries. Algist Bruggeman is part of the Lesaffre Group, a key global player in fermentation for more than a century.

Even with more than a century of industrial production behind it, Algist Bruggeman continues to evolve its manufacturing processes. Most recently, the company sought to upgrade and automate many of the manual processes that still existed at its production facility.

Monitoring and tracking the yeast fermentation process draws data from multiple sources in the Algist Bruggeman facility. This included recipe data from ERP systems, machine sensor and system data from SCADA servers, and lab results from a Laboratory Information Management System (LIMS). All these systems required human intervention to collect and analyze data, which created gaps between and opportunities for input errors.

Data sources diagram - Algist Bruggeman
Source: Factry

Algist Bruggeman partnered with Factry to implement a digital factory built on open source technologies. This new system automatically loads recipe data directly from the ERP into the Factry Manufacturing Execution Systems (MES) on the factory floor. The MES pushes the relevant data to the SCADA system so the PLCs know how to control the fermentation process for a specific recipe.

High resolution data from the PLCs gets sent to InfluxDB where it gets analyzed and stored. The Bruggeman team uses Grafana dashboards to visualize that analyzed data.

High resolution data from the PLCs gets sent to InfluxDB
Source: Factry

The team at Algist Bruggeman started off by simply tracking temperature during the fermentation process. Now, they collect a wide array of measurements, leveraging approximately 50 PLCs and over 4,000 tags for data that hits InfluxDB at a resolution of 1 Hz.

Having this kind of granular data provides Algist Bruggeman with greater observability into their production processes, deeper insights that drive optimization, and better quality control. They can use time series data to track the quality of raw materials and understand how varying quality of raw material affects the end product for specific yeast recipes.

The shift to the digital factory also brought several unexpected benefits. Having real-time data about supply levels and being able to cross-reference those with the needs of specific recipes made the company’s material requirements planning (MRP) more efficient and streamlined operations on the factory floor.

Real-time data also aids Algist Bruggeman with equipment monitoring. Granular data about machine performance enables predictive and preventative maintenance. This type of data also helps with anomaly detection, like uncovering events that occur after hours when no one was present to witness them.

Real-time observability of the digital factory itself provides useful information to all departments across the company, providing a degree of transparency that helps keep the entire operation running more consistently and efficiently.

Harnessing the power of time series data and leveraging open source technologies, like InfluxDB and OPC-UA, completely transformed industrial fermentation at Algist Bruggeman.

For more details on how Algist Bruggeman configured its digital factory and the benefits of using InfluxDB with IIoT data, see the full case study.

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