Predictive Maintenance: The Future of Industrial Efficiency
Predictive maintenance tools are reshaping the way industries approach equipment management and automation. Powered by artificial intelligence (AI), these tools detect faults early and recommend timely repairs, minimizing downtime, reducing costs, and increasing equipment availability.
In this blog, we’ll explore how leading companies like ABB, Siemens, Mitsubishi, and Schneider Electric are harnessing the power of predictive maintenance to transform industrial automation.
ABB and Viking Analytics: A Partnership for Smarter Automation
ABB, a global leader in industrial automation, has recognized the growing demand for predictive maintenance tools among its customers. To meet this demand, ABB invested in Viking Analytics, a Swedish condition-monitoring startup.
Viking Analytics developed MultiViz Vibration, an AI-driven solution for vibration analysis. ABB integrated this technology into its Ability Asset Manager, creating a comprehensive system capable of predicting and preventing machinery faults.
The collaboration between ABB and Viking Analytics began in 2020, following Viking's victory in the ABB Electrification Startup Challenge. Together, they have advanced applications and visualizations for condition monitoring sensors, enabling seamless automated solutions for industries such as iron casting.
Siemens Xcelerator: AI at the Core of Industrial Automation
Siemens has developed Xcelerator, a powerful software platform housing innovative AI applications like MindSphere and Predictive Services.
MindSphere is Siemens’ Internet of Things (IoT) solution, leveraging machine learning to provide predictive maintenance, process optimization, and obstacle detection in complex systems such as sewer lines. Siemens has successfully deployed MindSphere models in its facilities, identifying potential faults, ensuring process stability, and enhancing product quality.
Predictive Services focuses on analyzing machine conditions and planning maintenance activities. In one instance, Predictive Services improved production line availability by 10% at a tissue paper manufacturing facility by predicting motor failures and optimizing maintenance schedules.
Mitsubishi Maisart: Compact AI for Precision and Efficiency
Mitsubishi Electric offers its AI solutions under the Maisart brand, featuring tools like Compact AI, automated design deep learning, and natural language models for user-friendly interfaces.
Compact AI focuses on predictive maintenance for Mitsubishi's servo systems and variable frequency drives, identifying wear and corrosion before they cause equipment failure.
Mitsubishi’s AI solutions also extend to machining applications, where pre-trained algorithms continuously adapt machining parameters to optimize processes such as laser cutting and electrical discharge machining. Moreover, Mitsubishi is exploring quantum machine learning, offering unparalleled efficiency in feature recognition for ultra-high-frequency imaging.
Schneider EcoStruxure: AI-Driven Edge Computing
Schneider Electric’s EcoStruxure platform empowers users to create and deploy custom AI applications in industrial automation. By utilizing edge computing technology, intelligent algorithms operate directly next to equipment, making it ideal for legacy systems and distributed environments.
One notable application of EcoStruxure is in oil pumpjack monitoring. By automating the analysis of data from dynamometers, Schneider’s AI solutions identify faults, leaks, and wear without extensive human intervention. This approach minimizes unexpected failures and significantly reduces maintenance costs.
Conclusion: Why Predictive Maintenance Matters
Predictive maintenance is more than a trend; it’s a transformative approach to industrial automation. From ABB’s innovative partnerships to Schneider Electric’s edge-based solutions, AI-driven predictive tools are improving efficiency, cutting costs, and preventing downtime.
As these technologies evolve, industries worldwide can expect even greater reliability and performance in their automation systems. The future of industrial automation lies in intelligent, predictive solutions that empower businesses to operate smarter and faster.