IBM intros industrial AI and IoT suite to help manage asset downtime and maintenance
IBM has introduced a new suite of industrial internet of things (IoT) solutions for preventative and predictive downtime and maintenance that leverage artificial intelligence and advanced analytics.
The solution will reduce the risk of failure of physical assets including vehicles, manufacturing robots, turbines, mining equipment, elevators, and electrical transformers, the company said. Its new asset performance management (APM) solutions, part of its Maximo enterprise asset management (EAM) family, collect data from physical assets in near real-time and provide a view of their operating conditions, predict potential issues, and offer repair recommendations.
In its press note, IBM quoted research from Aberdeen Research that says unplanned downtime cost companies in asset-intensive industries like energy and utilities, chemicals, oil and gas, manufacturing, and transportation as much as $260,000 an hour. The Maximo APM suite takes disparate data sources and uses statistical models and machine learning to find assets in need of attention. Its drivers Include failure dates, failure probability, degradation curves, and anomaly detection, IBM said.
An AI-powered assistant provides access to documentation, diagnostics and recommendations for repair. IBM is customising the APM suite for specific industries, beginning with energy and utilities. The energy-and-utilities suite includes risk scoring, degradation models, and weather data integration.
Kareem Yusuf, general manager for IBM Watson IoT, said: “It’s critical for companies to think about how effective their maintenance practices are. IBM is helping organisations make insight-driven decisions…to help them improve operational effectiveness and efficiency.”
IBM issued a case study with its announcement. This focuses on the Metropolitan Atlanta Rapid Transit Authority (MARTA), the principal public transit agency in the Atlanta metropolitan area. MARTA is working with IBM to implement a predictive maintenance solution to improve reliability of assets, minimise costs and create a transit asset management (TAM) tool that provides asset inventory, condition assessment, performance measures and decision support.
“Through data mining, machine learning and AI, MARTA can access and analyze data to better understand the condition of equipment classified in the categories of life safety, operation critical and operation support to identify potential concerns of a “system” with multiple stakeholders. Ultimately, the solution will allow MARTA to seamlessly move from tracking asset performance KPIs to predicting and preventing asset failures,” said IBM in a press note.
Remy Saintil, director of facilities at MARTA, commented: “MARTA is on track to become the first North American public transit agency to achieve ISO 55000 certification. Collaborating with IBM provides MARTA with the innovation from a technology icon, which fortifies us as an industry leader in Transit Asset Management.”