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  • By Lanner
  • In News
  • Posted 06/06/2014

Lanner’s Predictive Simulation Platform Supports Manchester Metropolitan University and Lahore University of Management Science to Develop Elevator Effectiveness Model

Lanner, a provider of simulation software proven to maximise performance and optimise resources, today announced that WITNESS has been successfully used in a project to optimise elevator call strategies. Initiated by Manchester Metropolitan University and Lahore University of Management Science, the project was designed to reduce waiting times and improve service levels for elevator users across a variety of settings.

The project team at the universities selected WITNESS based on its experimentation capabilities; flexibility; and proven track record within similar projects. As a result of adopting the predictive simulation platform, the team was able to model three strategies for multi-car elevator systems. The models were used to identify the position of the elevator and the floor calling it in order to reduce waiting times by users at all floor call points.

“As the number of tall buildings, flats, hospitals and offices continues to increase, elevator efficiency has become a hot topic,” comments Dr Muhammad Latif, School of Engineering, Manchester Metropolitan University. “Buildings often experience elevator congestion as a result of heavy traffic, and long wait times can inhibit service levels and convenience. Through using Lanner’s predictive simulation platform, WITNESS, we have been able to evaluate a number of strategies to reduce congestion and improve quality of service, resulting in insight which can be used by any organisation tasked with installing, renovating or enhancing an elevator system.”

“We live in a world where speed and quality of service are paramount, and reduced elevator waiting times can result in substantially improved service levels and greater efficiency in how people move through a building,” comments David Jones, CEO, Lanner. “WITNESS can help to boost confidence in selecting the most effective strategies through mapping large volumes of variables, presenting a number of scenarios, and demonstrating the impact of each.”

Please click here to view a copy of the paper.


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