Intelligence across the full machine lifecycle.

A collision event caused sudden spindle bearing degradation, putting production at risk of unplanned failure. The customer was alerted about the defect and tracked the component’s degradation over time, allowing them to schedule a targeted bearing replacement before failure occurred. A critical failure was avoided, production remained uninterrupted, and downtime was minimized.

A milling machine exhibited abnormal axis movement, signaling a potential loss of precision. The customer performed IPercept’s Loop Test-cycle, which detected a localized defect in the ball-screw grooves, later confirmed via a double ballbar test. Repairs were scheduled before production quality was affected, preventing expensive rework and unplanned stoppages.

A gradual wear-out of multiple axis components was detected over six months. The customer used IPercept’s Portal to monitor wear progression and adjust their maintenance plan accordingly. Since the machine was used for roughing, no immediate action was required during this period.

A wide-frequency anomaly on the X-axis indicated increased friction due to poor lubrication, risking premature wear. The customer was alerted to the issue and took immediate corrective action before serious damage occurred. Lubrication cycles were optimized, reducing friction and extending the component’s lifespan.

The customer observed a continuous degradation trend in the ballscrew via IPercept Portal. Upon further inspection, the fault was confirmed, and maintenance was scheduled proactively. Unplanned downtime was avoided, and maintenance was optimized based on simplified visual insights.

Unusual vibration patterns indicated a developing fault in the drive-side bearing, posing a risk of failure. The customer was alerted early and pinpointed the exact issue, allowing them to schedule a targeted replacement rather than performing unnecessary troubleshooting. Downtime was minimized, unnecessary repairs were avoided, and operational costs were reduced.

A 2-spindle grinding machine was monitored using both traditional RMS values and IPercept’s algorithms. Traditional RMS values failed to detect early-stage spindle degradation, while IPercept’s advanced physics-based algorithms identified subtle condition changes much earlier. The customer was alerted in advance and scheduled timely interventions, preventing unexpected machine failures.

A localized defect appeared suddenly on the ballscrew shaft surface. The customer used IPercept Portal to pinpoint the issue, which suggested a severe machine collision. Although no damage was found in other subsystem components, the early warning allowed maintenance teams to investigate root causes and prevent further issues.

A 5-axis milling machine’s ballscrew nut showed subtle reversal spikes, which appeared normal to traditional inspection methods. However, the customer requested an expert report from IPercept for a high-resolution degradation trend - revealing early-stage wear. With this data, maintenance teams tracked component health with precision, ensuring timely interventions if needed.

The customer used IPercept’s service to assess the condition of six spindles across two mill-turn machines. The benchmarking process identified Spindle 3 of Machine B as exhibiting early signs of bearing degradation. By using this data, the customer optimized the order of spindle maintenance, ensuring targeted servicing without premature replacements.

IPercept detected localized defects in the guideways of a machine’s axis, which were deemed stable at the time. Instead of taking immediate action, the customer chose to continuously monitor the defect on the IPercept Portal. Months later, an inspection confirmed that the defect positions matched the precise locations identified by IPercept, validating the system’s accuracy. This allowed the customer to plan maintenance only when truly necessary.

For several months, the machine showed stable health scores, but then a sudden degradation drop occurred. IPercept investigated and confirmed that the machine had undergone milling experiments with titanium, which placed unexpected strain on the system. The customer, unaware of the damage extent, was able to log the degradation, adjust production planning, and order replacement parts in advance. A few weeks later, degradation continued, leading to a failure - but because the replacement part had arrived in time, downtime was minimized.

Within the first week after deployment, IPercept detected significant ball screw degradation, that already existed in the machine before the monitoring started. The degradation trend continued, signaling an imminent risk of quality issues or failure. By acting fast, the customer ordered specific replacement parts and scheduled maintenance proactively.

IPercept alerted the customer that the rotary table RPMs were causing excessive vibrations. By analyzing the data, they adjusted their production processes, optimizing RPM settings to reduce vibrations and extend the subsystem’s operational life and postponing replacement.

IPercept detected critical degradation in the axial mounting of the ball-screw drive, which over time propagated to other parts of the assembly, affecting additional components. The customer was alerted, and after replacing the ball-screw and coupling, IPercept continued monitoring and verified that some degradation remained in the drivetrain system, but the overall machine health was stable. By tracking these effects, the customer gained key insights into how single component replacements influence overall machine health, allowing them to refine their maintenance strategy and prevent future cascading failures.

IPercept identified critical degradation in the axial mounting of the ball-screw drive, which was already affecting multiple components. Over time, the degradation propagated to other parts of the drivetrain, causing further wear. The customer scheduled a ball-screw and coupling replacement. While some minor degradation remained, the machine returned to a stable condition, confirming the effectiveness of the maintenance action.

IPercept detected early-stage defects in the milling spindle, signaling a potential failure risk. The customer scheduled maintenance - allowing them to address the defect before it could lead to a critical failure. The customer requested a maintenance review and received a detailed renovation report showing comparisons of before and after.

IPercept detected severe degradation in the ballscrew of a linear axis, which had already begun affecting surface roughness in produced parts. The degradation was severe, and IPercept recommended an immediate replacement. After replacing the ballscrew, the customer verified a direct improvement in surface roughness, ensuring quality standards were met and preventing further production defects.