Driving Predictive Maintenance into ThyssenKrupp Elevators

CGI’s development team built a pilot, cloud-based elevator monitoring system using Microsoft’s Azure-based Intelligent System Service (ISS), Microsoft’s Azure Maching Learning, HDInsight and our own Intelligent Enterprise Framework (IEF), which facilitates the rapid deployment of IoT applications. Integrated with TKE’s elevator sensors, the system harnesses data from each sensor, processes the data using business rules defined by TKE, and generates rich data insight using predictive analytics. The resulting insight is then made available to supervisors and site technicians via two different user interfaces in the form of maintenance alerts, instructions and recommendations. Feedback from users is integrated within the system, enabling it to become more accurate over time. CGI worked with Microsoft to develop predictive data models using Microsoft’s Machine Learning Azure service. Years of historical data from elevators across North America were analysed to generate sequence mappings of alarms to identify the root causes of faults. he system was implemented for a small number of elevators run by TKE in the Seattle, Washington area in the summer of 2014. The pilot project was a success, enabling TKE to reduce elevator downtime and improve resource planning, cost forecasting and maintenance scheduling. In turn, TKE has been able to provide a more competitive offering to its customers.