The client is one of the world's leading high-quality chocolate & cocoa products manufacturer. They are the heart and engine of the chocolate industry.

Like many manufacturing companies in the Food Industry, they face an all-times challenge: High Machine Availability.

Even though manufacturing processes require strict control over certain production parameters, the ability to predict and prevent machine downtime is what truly makes the difference in helping them avoid inefficiencies. To achieve that, they needed to understand in detail the equipment maintenance and the processes associated with it. 

They needed a solution to monitor critical parameters in rotative machines and boilers in real-time and predict anomalies to control production and raw materials efficiently, reduce downtime, and machine recalibration and inefficiencies associated with it.​

Webee's Approach

Webee provides a simple to install IIoT solution to monitor several variables, and not only access the data in real-time but also predict anomalies by controlling machine behavior.
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​The client needed a solution that could also be installed in a complex factory setup with machinery located in long distances with scarce connectivity. We offered the client a set of sensors that could monitor parameters critical for machines. The LoRaWAN sensors were automatically on-boarded into our platform through our built-in network server.

Through drag & drop visual designer, our pre-built application lets them organize the data and create dashboards to visualize and distribute it any way they want. Webee software lets them set up SMS-Email alerts and ‘’forms’’ to tag the data of each machine.

Our built-in AI models detect patterns that to prevent machine malfunction. It’s not just alerting in real-time but also a ‘’predictive artificial intelligence’’ system.

Real-time control of acceleration and velocity of multiple rotative machines

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Historical data of rotative machines and temperature in boilers

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The Results ​

• Drastically reduce food loss and increase sustainability
• Save $2M in losses due to downtime
• Prevent machine malfunction by monitoring and predicting if a variable is behaving unexpectedly before it happens.
• Visualize the data in real-time through our VIoT Dashboards. Receive SMS/E-mail alerts if there is an anomaly with the machine.
• Receive AI data training forms. Extract the historic data in a CSV file for future analysis.​