Use cases about remote access and Industrial IoT | IXON

How SANOVO enhanced performance and maintenance insights with IXON

Written by Shelly Boom | 21-1-2025

How SANOVO uses IXON Cloud for remote monitoring of a wide range of egg processing machines for service and optimization.

SANOVO TECHNOLOGY GROUP is a leading machine builder manufacturing a wide range of egg handling and processing machines: from egg grading, breaking and processing machines to pasteurizers and powder dryers. SANOVO serves customers in several markets with its machines, such as large packing stations and liquid egg producers.

SANOVO's GraderPro machine - World's highest capacity egg grader machine

Challenge

As in all industries, it's difficult to find employees in the egg packaging and processing industry. Therefore, it's important for SANOVO's customers to be able to run their production lines as efficiently as possible. Data collection and information retrieval is extremely important to determine where performance issues are occurring in a production facility or processing line.

Solution

SANOVO uses the IXrouter3 and the IXON Cloud, which are white labeled with SANOVO branding. This total solution is offered to the market under the name LinkPro. New machines are always equipped with an IXrouter, which allows for remote maintenance and support. "The IXON solution is easy to maintain and the performance and stability is very good," Gerben says.

The advantage of IXON is that you can configure it remotely. We can quickly make any adjustments at the customer's request.

- Gerben Heinen, Teamleader Software at SANOVO Technology Group


Data is collected and visualized to get insights in the performance and maintenance of the machines. How well is the machine performing? When are machine parts going to break?

A few examples of machine data SANOVO is monitoring:

  • Operating hours of machine parts to monitor wear, for example from chains;
  • The amount of graded eggs;
  • The amount of errors or machine stops, such as double packs (2 egg cartons on top of each other);
  • How many eggs were transported to a certain packaging lane.

   

On the left: Production dashboard in SANOVO's LinkPro portal, on the right: dashboard with double packs per lane.

SANOVO’s customers can also access these dashboards. “Thanks to IXON’s role-based user management we have the freedom to apply customer-specific modifications. There are live dashboards for different roles such as production managers and service engineers," Gerben explains.

The machine KPIs that are monitored give a quick insight into the machine status. If desired, it’s then possible to zoom in on specific, detailed information. "The customers have access to their own machine production dashboard. For service purposes we have a dashboard with fault reports," Gerben says.

LinkPro also contains a dashboard that shows the OEE (Overall Equipment Efficiency). This is calculated based on the availability multiplied by the performance of the machine.

Performance dashboard showing the availability, performance and OEE.

Result

Currently, customers who buy a machine from SANOVO get one year of free access to LinkPro dashboards in which they can monitor their production and OEE. After this year, a subscription license is offered. 

SANOVO is getting a lot of positive feedback from customers about their service contracts about the following aspects:

  • Live production insights worldwide: they can track production processes in real time, regardless of their location.
  • Secure remote access via VPN and VNC: their customers can easily connect to their machines, even outside the production site.
  • Quick remote support: SANOVO is able to provide quick remote support to their customers.

The unique selling points of having our LinkPro solution definitely help in selling our service contracts.

- Gerben Heinen, Teamleader Software at SANOVO Technology Group

In addition to the purposes for which data is already being used today, machine data is logged for future developments such as predictive maintenance. "It's still difficult to determine when a sensor breaks down, which is why we are collecting the data now to discover trends later," Gerben points out.