OpexMX Articles
Insights and best practices on maintenance management, reliability, and manufacturing operations.
Systematic Comparison of Deep Learning Approaches for Vibration-Based Bolt Looseness Detection: Why Attention Matters More Than Features
Five deep-learning approaches compared on the same shaft-vibration dataset. An SE-attention CNN hits 93% accuracy and 87% faulty recall; removing attention collapses recall to 15%.
Vibration Monitoring: Reading What Your Machines Are Telling You
Vibration is the earliest, loudest language a failing machine speaks. Here is how to read it — from ISO velocity bands to bearing defect frequencies.
Weibull Analysis for Maintenance: Turning Failure Data Into Remaining-Useful-Life Predictions
Your CMMS already holds years of failure data. Weibull analysis turns it into remaining-useful-life predictions with confidence bounds — no machine learning required.
70% of CMMS Implementations Fail — Here
Most CMMS projects fail because they
The Cost of Unplanned Downtime: By the Numbers
Unplanned downtime costs industrial manufacturers $260,000 per hour. Here
OpexMX Platform White Paper: The CMMS Your Technicians Will Actually Use
Comprehensive technical and business overview of OpexMX — a next-generation CMMS+ platform combining maintenance management, gamification, predictive analytics, and mobile-first field operations.
Closing the Loop: From Predictive Maintenance to Reliability Engineering
Predictive maintenance tells you when something will fail. Reliability engineering tells you why — and how to prevent it from happening again. Here
Southeast Asia CMMS Adoption: The $80 Billion Opportunity
65% of Southeast Asian factories still track maintenance on paper or Excel. Here
WhatsApp is Not a CMMS (And Your Maintenance Data is Proving It)
65% of Southeast Asian factories still run maintenance on WhatsApp, Excel, and paper. Here