Intracol Predictive Maintenance Solution for Manufacturing in IoT



Intracol was approached by one of the leading manufacturers of high-quality complete bathroom solutions for both residential, commercial and health buildings to assess, explore and eventually demonstrate the possibilities of “digitalizing” manufacturing machines, collecting and analyzing data out of them. Intracol was choosen because this project requires deep knowledge in two of our main competences – Big Data and Internet of Things (IoT).

The Predictive Maintenance project is for building an IoT platform aiming to bring real-time visibility, data insights and alerting mechanisms for the manufacturing process of one of the largest industrial facilities in the region.

The Challenge

The project was very challenging in terms of on-site environment (i.e. 24/7 real operating manufacturing machines), industrial operating regimes (i.e. temperatures as high as 1000C) as well as distributed team setup.

The Solution

The system uses a variety of termo and electrical sensors, some of them built specifically for the project, which send the data to a data center via independent communication infrastructure. There the data is being transformed, stored and analyzed.

The technology stack includes Node.js based application server, TCP server for handling sensor data, MongoDB as a backing data store and JavaScript as UX/front-end functionality. The information is visualized in a dashboard UI, bringing contextual representation with navigable functionality.

The Project

To fulfill the requirements, Intracol architectured, designed and built the fundamentals of a dedicated Industry 4.0 solution. During the project, Intracol was working closely with 2 hardware vendors assessing, testing and deploying different types of data sensors. The end goal has been to come up with high quality, reliable and affordable measurement devices which will further facilitate the solution’s availability and scalability needs.

Another key aspect of the project was the on-site environment which consists of production operating machines and therefore thorough and extensive in-house testing is required before attempting a deployment.

End result

Intracol integrated and demonstrated the solution’s strengths from the very beginning of the actual deployment and launch. Being able to see the benefits and ROI early on, the client expressed a strong willingness to further enhance the platform and deploy the solution into their entire facility.

Intracol Predictive Maintenance Solution for Manufacturing in IoT

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