Indeed, it's hard to imagine what modern city life would be like without tall buildings and skyscrapers. Since its invention, the technological complexity of elevators has increased dramatically.
Since the early 20th century, modern high-speed elevators have become far more complex than their creaking predecessors. However, the more complex the elevator, the harder it is to maintain its availability and safety through traditional physical inspections and fixed-schedule maintenance procedures. When IoT and AI technologies come into play, they greatly simplify the work of facility managers and building owners, especially those who must oversee elevators spanning multiple buildings.
Centralized interface, supports multiple elevator management
Bosch.IO, the IoT division of the Bosch Group, and TÜV SÜD, an independent elevator certification and inspection organization, recently announced the "Lift Manager" solution, designed to help large real estate companies and elevator maintenance companies manage their portfolios of different types of elevator brands and models. Created as a non-intrusive system, it can easily retrofit elevators from various manufacturers across multiple properties and connect them to a single interface. A unified dashboard provides a comprehensive view of the current status of all elevators, eliminating the need for regular on-site inspections.
Thus, in installations at Singapore business parks, the solution reportedly saves up to 14,000 man-hours annually solely for physical lifting inspections, allowing facility managers to shift their time and energy to other tasks.
24/7 elevator monitoring and real-time anomaly detection
The elevator management system continuously tracks key performance indicators of the elevator and collects data on its condition, usage, and passenger comfort. The operation monitoring function outlines all major operating parameters and physical characteristics of the elevator and its components. Among other important parameters, it includes cabin floor flatness, number of trips, door movement, mileage, and environmental conditions. Standards related to passenger comfort (such as jerkiness and acceleration/deceleration) are also monitored. Operators can view current data and historical trends on the dashboard. This information will later serve as the basis for predictive maintenance.
Most importantly, the system quickly detects elevator parameters that exceed predefined ranges for normal elevator operation. Typical examples include: traps, incorrect floor level in the cabin, door opening and closing problems, and abnormal vibrations or noises. In the event of a major problem, the elevator manager immediately alerts the appropriate personnel, significantly reducing response time for critical events.
Predictive maintenance allows for advance planning of elevator repairs.
Before an anomaly detection threshold is reached, Lift Manager's predictive maintenance module identifies and assesses abnormal behavior or changes in operating parameters. It uses data interpretation and AI algorithms to predict and detect initial and ongoing degradation processes before actual failures occur. This sophisticated and advanced feature provides operators with a significant advantage, enabling them to proactively schedule elevator service interventions at least 30 days in advance.
Knowing when a failure will occur: Remaining downtime indicator
When a potential abnormal process is detected, Lift Manager's predictive maintenance module sends an alert to the dashboard. This alert indicates when the relevant elevator component or subsystem is likely to fail. This information is displayed in a dedicated area of the dashboard as Downtime To Date (RTD).
The RTD indicator has three priority categories to specify the urgency of the required intervention:
Green status: Low urgency; recommended maintenance should be taken during one of the subsequent monthly maintenance checks.
Orange status: Emergency level is normal; recommended measures should be taken during the next scheduled maintenance check.
Red status: High level of urgency; it is recommended to take immediate measures to prevent elevator malfunction.
In addition, the system can identify the root cause of detected anomalies and provide clear guidance on which components need to be repaired. This allows for more targeted maintenance planning, saving building operating costs and minimizing elevator downtime. Specific problems can be communicated to elevator technicians in advance, avoiding lengthy standard checklists for root cause identification and thus reducing on-site time.
