Shift MRO Buying Toward Predictive Maintenance and Cyber-Aware Monitoring

Recent events, including the Hugging Face security incident, highlighted how vulnerabilities in the AI software supply chain can affect organizations that rely on open-source tools and AI models

Recent events, including the Hugging Face security incident, highlighted how vulnerabilities in the AI software supply chain can affect organizations that rely on open-source tools and AI models. While open AI platforms have accelerated innovation, they have also demonstrated the importance of ensuring that models, software dependencies, and development tools are secure before they reach production environments

But as AI becomes another critical operational technology, it also introduces new cybersecurity and trust challenges that plant managers cannot afford to ignore. Recent events, including the Hugging Face security incident, highlighted how vulnerabilities in the AI software supply chain can affect organizations that rely on open-source tools and AI models

Ottawa-based Gastops, a company specializing in condition monitoring and predictive maintenance, has delivered its 20,000th MetalSCAN oil debris monitoring sensor to the aerospace market

According to a company press release, MetalSCAN sensors detect and monitor metallic wear debris in lubricated systems, giving maintenance teams insight into equipment condition and supporting condition-based maintenance programs. Gastops said the technology can help reduce unnecessary inspections and optimize lifecycle costs

Gastops said the technology can help reduce unnecessary inspections and optimize lifecycle costs

Predictive maintenance insights Process manufacturers can strengthen uptime, safety and performance by breaking down data silos and using advanced analytics and AI to turn scattered operational information into actionable predictive maintenance insights. Predictive maintenance helps plants shift from calendar-based repairs to condition-based interventions, enabling earlier detection of degradation, fewer unplanned shutdowns and measurable gains in reliability, efficiency and cost control

Predictive maintenance insights Process manufacturers can strengthen uptime, safety and performance by breaking down data silos and using advanced analytics and AI to turn scattered operational information into actionable predictive maintenance insights

To drive the transition to a predictive approach, the team deployed Seeq — an analytics and AI platform — to integrate valve, process and maintenance data, enabling detection of issues like stiction and excessive cycling, along with collection of benchmark performance data across critical assets

Figure 3: Restored metal parts ready for preservation. Courtesy: Cortec Layup of process heating and cooling equipment: Whether working with a water treatment service provider or overseeing shutdown and startup themselves, maintenance teams also should be aware of the heightened risk for corrosion during layup and of the simple protective options that are available

By being alert to corrosion threats and understanding practical alternatives to more cumbersome and dangerous methods of corrosion control, facilities can save money and downtime — and even expand storage space. How do plant maintenance employees think about corrosion?

Learn the value of vapor corrosion inhibitors over traditional forms of corrosion protection. Corrosion insights A proactive corrosion strategy strengthens asset management by helping facilities reduce downtime, preserve critical spares and recover costs that traditional maintenance approaches often overlook