- February 28, 2019
February 28, 2019 -- IBM announced a new portfolio of Internet of Things (IoT) solutions that team artificial intelligence (AI) and advanced analytics designed to help asset intensive organizations, such as the Metropolitan Atlanta Rapid Transit Authority (MARTA), to improve maintenance strategies. The solution is designed to help reduce the risk of failure from physical assets such as vehicles, manufacturing robots, turbines, mining equipment, elevators, and electrical transformers. IBM Maximo Asset Performance Management (APM) solutions collect data from physical assets in near real-time and provide insights on current operating conditions, predict potential issues, identify problems and offer repair recommendations.
According to Analyst firm Aberdeen Research, unplanned downtime can cost a company as much as $260,000 an hour. IBM’s APM solutions help organizations shift asset maintenance strategies from preventative to predictive and prescriptive by integrating disparate data sources to find assets in need of attention and recommending actions.
This solution complements a company’s existing enterprise asset management (EAM) capabilities, such as IBM’s Maximo EAM solution, and integrates with other EAM providers. It includes:
- Asset Health Insights: Provides asset health assessments in near real-time using asset records, sensor data, and other external data to inform maintenance and replacement decisions.
- Predictive Maintenance Insights: Predicts asset health using statistical models and machine learning. Includes failure date/probability, key drivers, degradation curves, and anomaly detection.
- Equipment Management Assistant: Enables technicians to repair equipment with an AI-powered assistant providing quicker access to documentation, diagnostics and recommendations for repair
IBM will also offer the APM suite customized for specific industries, beginning with APM for Energy and Utilities (E&U). This provides industry-specific capabilities to analyze and act on insights from utility assets and includes risk/criticality scoring, health and degradation models, standard industry data model, and weather data integration.
The Metropolitan Atlanta Rapid Transit Authority (MARTA), the principal public transit agency in the Atlanta metropolitan area, is working with IBM to implement a predictive maintenance solution to improve 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 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 move from tracking asset performance KPIs to predicting and preventing asset failures.
“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,” said Remy Saintil, director of facilities at MARTA.