IBM Case Studies Improving “people flow” in 1.1 million elevators globally

Edit This Case Study Record

	Improving “people flow” in 1.1 million elevators globally IBM

Improving “people flow” in 1.1 million elevators globally

IBM

Technology Category	Analytics & Modeling - Predictive Analytics Functional Applications - Remote Monitoring & Control Systems Platform as a Service (PaaS) - Connectivity Platforms Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries	Equipment & Machinery
Applicable Functions	Maintenance
Use Cases	Predictive Maintenance
Challenge	KONE already provided traditional maintenance services for its more than 400,000 building owner and facilities management customers, but it sought cloud-based analytics technology to capture and use the vast amount of data generated by its elevator and escalator equipment worldwide to transform its service offerings. “We knew that digitalization was changing the industry, and we wanted to become a forerunner, not a follower in this development,” says Markus Huuskonen, the Director of Maintenance Processes and Connected Services at KONE. Read More
About Customer	KONEKONE’s mission is to improve the flow of urban life. As a global leader in the elevator and escalator industry, KONE provides elevators, escalators and automatic building doors, as well as solutions for maintenance and modernization to add value Read More
Customer Name	KONE Read More
Solution	KONE chose the IBM Watson IoT Platform running on an IBM Cloud platform to connect, remotely monitor and optimize managing more than 1.1 million elevators and escalators worldwide. Connecting all that equipment to IBM Watson IoT is a game changer, according to Huuskonen. “We have real-time visibility into what’s happening, and we are then providing that visibility to our customers so that they have more information available. That makes their job easier, especially with their own customers, who are users of the equipment or tenants in the building.” Analytics embedded in the solution can predict equipment condition, thereby helping KONE customers better manage their equipment over its lifecycle. For example, instead of requiring a customer to call for a service engineer after an equipment breakdown, the solution helps KONE see imminent problems in real-time, quickly dispatching a technician to resolve issues before they can cause system malfunctions or interruptions. In other words, KONE can fix things before they break. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Functional Applications - Remote Monitoring & Control Systems

Platform as a Service (PaaS) - Connectivity Platforms

Platform as a Service (PaaS) - Data Management Platforms

Applicable Industries

Equipment & Machinery

Applicable Functions

Maintenance

Use Cases

Predictive Maintenance

Challenge

KONE already provided traditional maintenance services for its more than 400,000 building owner and facilities management customers, but it sought cloud-based analytics technology to capture and use the vast amount of data generated by its elevator and escalator equipment worldwide to transform its service offerings. “We knew that digitalization was changing the industry, and we wanted to become a forerunner, not a follower in this development,” says Markus Huuskonen, the Director of Maintenance Processes and Connected Services at KONE.

About Customer

KONEKONE’s mission is to improve the flow of urban life. As a global leader in the elevator and escalator industry, KONE provides elevators, escalators and automatic building doors, as well as solutions for maintenance and modernization to add value

Customer Name

KONE

Solution

KONE chose the IBM Watson IoT Platform running on an IBM Cloud platform to connect, remotely monitor and optimize managing more than 1.1 million elevators and escalators worldwide.

Connecting all that equipment to IBM Watson IoT is a game changer, according to Huuskonen. “We have real-time visibility into what’s happening, and we are then providing that visibility to our customers so that they have more information available. That makes their job easier, especially with their own customers, who are users of the equipment or tenants in the building.”

Analytics embedded in the solution can predict equipment condition, thereby helping KONE customers better manage their equipment over its lifecycle. For example, instead of requiring a customer to call for a service engineer after an equipment breakdown, the solution helps KONE see imminent problems in real-time, quickly dispatching a technician to resolve issues before they can cause system malfunctions or interruptions. In other words, KONE can fix things before they break.

Impact #1	[Process Optimization - Predictive Maintenance] 1.1 million elevators connected to a cloud-based system that predicts maintenance needs
Impact #2	[Efficiency Improvement - OEE] Improves equipment availability through reduced downtime, fewer faults and more detailed performance information
Impact #3	[Financial Growth - Market Opportunities] Fosters third-party innovation through application development to improve customer service and user experience

Impact #1

[Process Optimization - Predictive Maintenance]

1.1 million elevators connected to a cloud-based system that predicts maintenance needs

Impact #2

[Efficiency Improvement - OEE]

Improves equipment availability through reduced downtime, fewer faults and more detailed performance information

Impact #3

[Financial Growth - Market Opportunities]

Fosters third-party innovation through application development to improve customer service and user experience

Download PDF Version

Overview

Improving “people flow” in 1.1 million elevators globally

Operational Impact