When data becomes actionable

When downtime is a cost for the customer

By the time a customer calls, the impact is already real. Production is stopped or slowed. Pressure is rising. That is why the first minutes matter. The customer wants certainty. The technician wants facts.

Without usable data, service becomes a slow funnel. You ask questions. You interpret descriptions. You try to infer whether the issue is the tube, the generator, a connector, cooling, or power electronics. And if the system cannot be understood remotely, the next step is unavoidable: travel, on-site time, and manual troubleshooting under pressure.

Pierre-Emmanuel describes this clearly: “If you have no web user interface, you need to check the system manually.” Manual means systematic work on site: “We must check the power supplies, all the connectors, the filaments, and the cooling system. You must do the measurement yourself.” And it always starts the same way: “The first thing is for you to go to the customer site, which takes time, sometimes longer than others, as you can imagine”. 

The frustration is not the complexity of the work, but the lack of direction at the start. Time is lost in travel and preparation before we can focus on the work that actually matters.

A maintenance mindset built over decades

Pierre-Emmanuel did not come to X-ray technology from a lab or academic background. He came through maintenance - the kind that trains you to think in systems, sequences, and consequences. His professional identity is consistent: “Maintenance… It’s basically the baseline of my life.” At the Belgian railroads, he saw how monitoring and thresholds shape behavior: “We had a network diagnosis. It was full of sensors and thresholds. If data was going up, we were checking it every morning.” That experience still informs how he thinks about service today.

At X-RIS, he works with systems installed in real world conditions. Some operate in cold environments where oil thickens, and flow switches stop switching. “Sometimes the oil is getting thicker, and the flow switch isn’t switching anymore.” Others run in dusty or hot facilities: “It was a casting factory… very, very dusty. The heat exchanger was totally full of dust.” This is why Pierre-Emmanuel values tools that work in imperfect conditions. The goal is not a dashboard. The goal is clarity amid messy reality.

Field reality - where data makes the difference

Certain failure patterns repeat. On iVario systems, one component frequently dominates support discussions: the power cell (POC). Pierre-Emmanuel explains why: “The power cells of the iVario are driving almost everything.” When it fails, the impact is immediate: “When this cell is missing, nothing is working anymore.”

What matters is not only frequency, but the speed of understanding. When system data is accessible, the situation becomes clear early: “You can see this directly: the power cell is missing.” That changes preparation completely: “So, you don’t have to go on-site without knowing. You take the power cell with you.”

When the issue is not the POC, his diagnostic logic follows a known sequence: connectors, cables, boards, boot sequence, filament health. “I check the three green LEDs that indicate the booting sequence.” If needed, he verifies components directly: “You can check the filament with a resistance meter.”

Environmental stress is always part of the picture as well. The challenge is not identifying possible causes - it is identifying the right one early.
When information is available, service arrives prepared. When it is not, service arrives with a checklist and uncertainty.

What BLOX changes and what it does not

The value of BLOX builds on data already generated inside the iVario generator. The system records events, error codes, and sensor values. The limitation before was not data availability, but usability. Pierre-Emmanuel describes the previous situation: “It was mandatory to send these logs to Comet, because we were unable to display them correctly.” That created a second delay after log collection: “Sometimes we waited two or three days before having the diagnosis.” Only then could action begin.

Preventive maintenance - protecting uptime through early signals

While predictive maintenance remains a future goal, preventive maintenance is already part of Pierre-Emmanuel’s approach today. The key is trend visibility. When operational behavior or conditions drift outside recommended limits, the risk becomes visible early. One example is cycling behavior. Pierre-Emmanuel explains: “The number of cycles per day… it should not exceed 15.” In reality, he sometimes sees far more: “And sometimes it’s 150.”

That insight allows action before damage occurs. “The non-cyclical tube will fail if you don’t change the way you use the tube.” The response is preventive: “You must change the tube, change the way you work, or retrofit the system and put a shutter.”
The same logic applies to temperature and environmental stress. “There are many temperature probes… anodic, cathodic side, cooler, power cells.” When values trend too high, service can recommend changes before shutdowns occur. This is preventive maintenance as Pierre-Emmanuel understands it: not predicting dates but identifying risk early enough to protect uptime.

Proof in the field

BLOX has already changed how Pierre-Emmanuel communicates with customers. He uses visuals directly in reports: “I can do a print screen, and I can teach my customers.” When a discussion involves operating behavior, the data speaks for itself. “I showed him directly graphically.”

In one case, cycling behavior clearly exceeded datasheet recommendations. Pierre-Emmanuel showed both views side by side: “See, this is the data sheet… and this is how many cycles.” The mismatch was visible. This changes the tone of the conversation. It is no longer based on opinion or memory. It is based on recorded system behavior. BLOX does not escalate discussions. It clarifies them.

From unreadable logs to actionable service

For Pierre-Emmanuel, the impact of BLOX is clear: “The most important thing is to analyze the data before it’s too late.” What changed is not the presence of data, but access to it: “It was not readable to us… it was totally impossible before.”

BLOX reduces diagnosis delays, supports preventive maintenance, and creates clearer service conversations. The immediate result is faster, more confident decisions. The longer-term result is a foundation for planned service and improved uptime.
For customers, that means less uncertainty between failure and action.

For service teams, it means fewer blind steps.
And for the relationship, it means decisions based on what the system recorded - not what someone remembers under pressure.