PREDICTIVE MAINTENANCE

Real-time Machine Visibility for Predictive Maintenance Software

Downtime is not just a machine problem, it’s a production problem. Get real-time data for implementing predictive maintenance across your shop floor helping you reduce downtime, eliminate blindspots, and act on real operating conditions instead of assumptions.

CONNECT ANY MACHINE

Easily collect and standardize data across your shop floor. No gaps, regardless of age or control type.

ONE SYSTEM, EVERY VIEW

Power utilization, OEE, and predictive maintenance from the same machine data across modern and legacy equipment.

KEEP PRODUCTION ON SCHEDULE

Identify issues earlier, notify the right people, and take action before downtime impacts production.

THE GAP

Where Traditional Maintenance Falls Short

Downtime is not just a machine problem, it’s a production problem. Get real-time data for implementing predictive maintenance across your shop floor helping you reduce downtime, eliminate blindspots, and act on real operating conditions instead of assumptions.

Reactive maintenance costs more than repairs

When a machine goes down unexpectedly, the real cost is rarely isolated to the event itself. It shows up in missed production, labor disruption, rush parts, overtime, and delivery risk.

Preventive schedules miss real-time signals

Time-based maintenance is better than waiting for failure, but it still does not tell you what is happening right now. Some assets get serviced too early. Others fail between intervals.

Manual tracking creates blind spots

Clipboards, spreadsheets, and shift summaries do not create the continuous machine-level visibility needed to catch issues early. By the time the data is reviewed, the opportunity to act passes.

OUR APPROACH

How Juxtum Supports Predictive Maintenance

Juxtum’s software adapters collect a broad range of data directly from your manufacturing equipment, including axis positions, spindle loads, feed rates, overrides, block and line numbers, cycle times, and part counts, all standardized using the MTConnect ANSI standard format. Once that data is flowing continuously, Juxtum View monitors alarm patterns and signal behavior across every connected asset in real time. Deviations from normal operating conditions surface as notifications before they become failures. Maintenance teams gain an earlier view into equipment health so repairs can be scheduled strategically rather than reactively.

Most shop floors run a mix of control types and equipment vintages. Juxtum’s patented adapter software automatically discovers each machine’s unique configuration, including its axes, spindles, geometry, and physics, without interrupting production. For most CNC machines, data is flowing within approximately ten minutes of deployment. No downtime. No manual configuration. No production interruption.

For assets where additional physical monitoring adds value, Juxtum supports supplementary sensor data collection as a layer on top of native machine data. Vibration analysis, temperature monitoring, and other condition signals can be incorporated into the same standardized data stream, giving maintenance teams a more complete picture of equipment health without requiring a separate system.

Juxtum deploys in the cloud for operations that want rapid time-to-value, or on-premises for manufacturers with strict data security requirements. This is a critical distinction for aerospace and defense facilities where sensitive production data must stay within facility boundaries. Most machine monitoring solutions offer cloud-only deployment. Juxtum gives operations teams a choice.

THE IMPACT

What Becomes Possible With Continuous Equipment Data

When machines are continuously streaming standardized data, maintenance decisions can be based on actual equipment condition rather than elapsed time or failure events. Alarm patterns and signal trends point to potential failures before they occur. Maintenance teams gain the lead time to schedule repairs at planned intervals, with the right parts on hand. Better resource allocation across your maintenance team means lower maintenance costs over time and downstream production that stays on schedule.

One manufacturer connected through Juxtum discovered that machines scheduled to run for seven hours were averaging six hours and fifteen minutes of actual production time. That forty-five-minute gap represented recoverable capacity that required no additional capital investment to address. Identifying and reducing unplanned downtime is one of the fastest paths to increased throughput in a facility you are already running.

Standardized, continuous equipment data gives maintenance teams and operations leadership a shared view of shop floor performance. Utilization rates, alarm histories, cycle time trends, and condition signals are all visible in Juxtum View dashboards and reports. The objective basis for maintenance scheduling, capital planning, and process improvement is there when the team needs it.

The same data foundation that supports condition monitoring today can support predictive maintenance analytics and AI-driven decision-making as your operation’s digital maturity grows. Juxtum Connect provides the clean, structured, real-time shop floor data those initiatives require. The foundation does not need to be replaced as your ambitions grow.

With real-time machine monitoring, abnormal behavior becomes visible as it develops, surfacing hidden issues earlier and giving teams time to act before production is impacted.

From early visibility → to fewer disruptions → to measurable cost avoidance.

$50,000+

AVOIDED ON A SINGLE EVENT

OUR EDGE

Why Manufacturers Choose Juxtum for Predictive Maintenance

Broad connectivity

Juxtum connects across mixed machine environments, enabling data collection from CNCs, PLCs, and legacy equipment that other platforms struggle to reach. This ensures predictive maintenance and condition monitoring are built on complete equipment data—not partial visibility.

Deeper equipment data

Go beyond basic machine states with access to real operating signals—alarms, load, feed rates, and more. This depth of equipment data strengthens both condition monitoring and predictive maintenance by providing the context needed to understand true machine performance.

Faster time to value

Juxtum is designed for rapid data collection and deployment, allowing manufacturers to begin predictive maintenance efficiently without interrupting production or requiring complex setup.

Flexible deployment

Deploy in the cloud or on-premises depending on your operational and security requirements. Juxtum supports predictive maintenance and condition monitoring strategies across a range of manufacturing environments.

“We’ve moved from reacting to identifying problems before they impacted production. Juxtum made our maintenance approach more proactive without adding burden to the team.”

– Mark R., Maintenance Manager, Wichita, KS 

Predictive Maintenance Is Not a Separate Strategy. It Starts With Visibility.

If you do not have reliable machine data, predictive maintenance stays theoretical. Juxtum helps manufacturers turn existing equipment into a stronger source of operational insight so maintenance teams can react less, plan better, and support more reliable production.

Predictive Maintenance FAQs

Predictive maintenance requires continuous, accurate machine data collection across your entire operation. Without standardized, real-time equipment data, you cannot identify patterns in equipment behavior, detect abnormalities in data reporting, or build predictive models to predict failure and identify potential failures before they occur. Without that foundation, maintenance decisions fall back to schedules or assumptions instead of actual performance—driving higher maintenance costs over time.

Most shop floors run a mix of machines from different vendors, control types, and production eras. CNC platforms like Fanuc, Siemens, Heidenhain, and Mazak all output data differently, and older equipment often has no native connectivity. This creates gaps in data collection and visibility, making it difficult to implement predictive maintenance and build reliable predictive models across the full asset base.

Predictive maintenance does not start with dashboards or algorithms, it starts with reliable data collection. If equipment data is incomplete, inconsistent, or delayed, predictive models cannot accurately predict failure or identify potential failures. The first step is collecting and standardizing data from every machine so production can be monitored in real time and used to support meaningful analysis.

They are the foundation of predictive maintenance. Signals like load, speed, temperature, alarms, and cycle behavior provide the context needed to understand how a machine is actually performing. Monitoring changes in these conditions over time allows teams to identify potential failures earlier, reduce risk, lower maintenance costs, and take action before issues lead to downtime.

Juxtum enables comprehensive data collection across machines of all types, brands, and vintages, then standardizes that equipment data at the source. This creates a complete, consistent dataset that supports condition monitoring, predictive maintenance, and the development of reliable predictive models. With that foundation in place, teams can detect abnormalities, predict failure earlier, and make more informed decisions that help lower maintenance costs and improve overall equipment performance.

Get More From Your Shop Floor

The data you need is already in your machines. Juxtum makes it actionable so you can turn production into performance that moves your operations forward.