Waites Expands AI-Powered Prescriptive Maintenance Solutions to Help Manufacturers Eliminate Downtime
Waites, a leader in AI-driven and analyst-verified prescriptive maintenance solutions, today announced an expanded range of technology capabilities and services designed to help global manufacturing teams improve overall equipment effectiveness (OEE), strengthen asset reliability, and reduce unplanned downtime.
The latest advancements reinforce Waites’ mission to create “a world where nothing breaks®” by helping maintenance teams move beyond simply identifying potential equipment failures. Through a combination of artificial intelligence, advanced sensing, machine learning, and human expertise, Waites is focused on turning machine data into clear, prioritized actions that maintenance teams can take before failures occur.
Unplanned downtime remains one of the biggest challenges facing manufacturers, costing U.S. companies hundreds of billions of dollars each year. According to MaintainX’s 2026 State of Industrial Maintenance survey, cited in Waites’ The Execution Era of Predictive Maintenance: Outlook to 2030, 79% of maintenance teams reported that downtime either remained unchanged or increased during the previous year.
For manufacturers seeking to reverse that trend, predictive maintenance alone is no longer enough. Waites is advancing toward prescriptive maintenance, helping organizations bridge the gap between detecting an emerging problem and determining what action should be taken, when it should happen, and which issues should receive priority.
Proven Results in Industrial Reliability
The impact of Waites’ approach is demonstrated through its work with Domtar, a leading manufacturer of paper, packaging, and diversified forest products.
At Domtar’s modernized Kingsport Mill, Waites analysts and AI-powered condition monitoring helped reduce mechanical and electrical downtime from approximately 10% to 3%. By combining early fault detection with a collaborative human-in-the-loop approach, Domtar avoided approximately 1,138 hours of unplanned downtime.
The program monitors more than 600 assets and provides maintenance teams with earlier visibility into vibration-related issues, allowing them to investigate potential problems and address root causes before they develop into costly failures.
“Waites has become a core part of our reliability program,” said Matthew A. McLaughlin, CRE, Reliability Superintendent at Domtar. “Across more than 600 assets, we’re consistently detecting vibration-related issues early and addressing root cause issues, avoiding 483 hours of downtime in one year alone.”
These results illustrate how modern condition monitoring can help manufacturers improve asset reliability while protecting production throughput and building more resilient operations.
Expanding Precision Monitoring with ImpactVUE
As part of its expanded technology capabilities, Waites is extending the role of ImpactVUE®, its high-frequency vibration signal processing capability.
Integrated with Waites’ portfolio of advanced sensors, ImpactVUE captures ultrasonic vibration data that can help identify developing bearing, lubrication, looseness, and other impact-related faults. The technology has been used for more than a decade to identify equipment conditions that may be difficult to detect through conventional vibration trends, particularly in slow-speed machinery.
Rather than relying solely on basic ultrasonic measurements, ImpactVUE isolates high-frequency stress-wave peaks generated by repeated mechanical impacts. It filters surrounding noise and produces waveform and spectral information that can provide more detailed diagnostic insight.
When combined with conventional vibration measurements and reviews from Waites’ global team of ISO-certified analysts, ImpactVUE provides maintenance teams with a clearer understanding of developing equipment conditions. This combination of high-quality data and human expertise enables teams to respond with greater confidence and precision.
Microsecond-Level Time Synchronization
Waites has also developed wireless, microsecond-level time synchronization across sensors throughout an industrial facility. This capability enables condition-monitoring systems to correlate vibration data from multiple machines with significantly greater precision.
With sensors capturing data simultaneously, maintenance teams and AI systems can perform phase and coherence analysis across connected or coupled assets. This provides insights that were previously associated primarily with expensive wired systems or specialized portable equipment.
Waites sensors can achieve synchronization accuracy of less than three microseconds—approximately three millionths of a second. This advancement expands what is possible with wireless condition monitoring and can improve machine-learning-based fault classification and diagnostics.
For complex manufacturing environments with interconnected equipment, precise synchronization can provide a more complete view of machine behavior and help maintenance teams identify relationships between assets that might otherwise remain difficult to detect.
Strengthening Reliability Expertise
Technology is only one component of a successful reliability strategy. To support customers as they expand enterprise reliability programs globally, Waites has also strengthened its reliability services team with the appointment of Jeff Parker, CMRP.
Parker brings 30 years of operational, reliability, and maintenance experience to the company. His expertise will support Waites’ customers as they work to improve asset performance, strengthen maintenance execution, and create greater alignment between reliability, operations, and other functions across industrial organizations.
His addition reflects Waites’ broader focus on combining technology with practical reliability expertise to help customers translate data and AI-driven insights into measurable operational improvements.
Research Highlights Growing Demand for Predictive Maintenance
Waites is also investing in research to better understand the changing maintenance and reliability landscape.
The company recently sponsored a research report focused on digital transformation across maintenance and reliability organizations in the United Kingdom and Ireland. Mainstream’s Industrial Asset Management Technology Investment Report examines investment decisions, implementation challenges, and strategic opportunities across 17 maintenance and reliability technology solutions.
The research highlights the growing importance of technology as industrial organizations look for ways to improve asset performance, reduce operational risk, and make more effective use of maintenance resources.
Combining AI with Human Expertise
A defining element of Waites’ approach is its human-in-the-loop methodology. While AI and industrial IoT technologies enable organizations to collect and analyze vast amounts of machine data, Waites believes human expertise remains essential for determining which signals matter most.
Every AI-generated alert is validated by an ISO CAT II+ certified vibration analyst before being delivered to customers. Analysts provide context, verify the relevance of detected conditions, and help maintenance teams understand which issues require attention.
This combination helps reduce the noise that can accompany large-scale predictive maintenance programs. Instead of overwhelming maintenance professionals with alerts, Waites aims to provide information that is accurate, relevant, and actionable.
Waites’ wireless mesh network supports large industrial environments by connecting sensors, nodes, repeaters, and gateways to move machine-health data securely from equipment to the cloud. The network uses 2.4 GHz IEEE 802.15.4 wireless communication with AES-128 encryption, while cellular MQTT communication and TLS encryption help protect data transmitted to the Waites Cloud.
Turning Machine Data into Action
Founded in 2006 and headquartered in Cincinnati, Ohio, Waites supports industrial organizations around the world. Its technology combines wireless vibration monitoring, machine learning, AI, and expert analysis to help companies detect equipment issues before they become failures.
The company says its technology has collected more than 12 trillion data points from over half a million sensors deployed across six continents. Its global team supports 16 languages and processes billions of machine readings every day.
Waites has received recognition including a Titan Innovation Award for manufacturing technology and the Best IoT Solution Award from ReliabilityWeb. It was also named a finalist for the Fierce Sensors Best of Sensors Award in the Best Industrial and IIoT Solution category.
Through its continued investment in sensing, AI, synchronization, analytics, and reliability expertise, Waites is working to move industrial maintenance from reactive response toward proactive, prescriptive action.
The goal is straightforward: give maintenance teams the information, context, and confidence they need to act before equipment failure occurs—helping manufacturers improve OEE, reduce downtime, extend asset life, and keep production running at peak performance.
About Waites
Waites is on a mission to create a world where nothing breaks. Founded in 2006 and headquartered in Cincinnati, Ohio, with team members around the world, Waites provides AI-powered predictive and prescriptive maintenance solutions for industrial organizations.
By combining wireless sensors, machine learning, advanced analytics, and human expertise, Waites helps maintenance teams identify equipment issues early and determine the actions needed to improve reliability. Its technology enables organizations to transform machine data into actionable insights, supporting higher uptime, improved operational efficiency, and longer asset lifecycles.
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