Efficient maintenance management system

Siemens Mobility Services cuts costs and increases availability with predictive maintenance

Published on 05-Jun-2013

"IBM Maximo has already reduced the costs of implementing and operating an enterprise asset management solution for new systems by around 30 percent. Furthermore, we have significantly improved our competitiveness because we can offer better services more efficiently." - Lutz Grote, Senior Process Manager, Siemens Mobility Services

Customer:
Siemens Mobility Services

Industry:
Travel & Transportation

Deployment country:
Germany

Solution:
Asset Management, Information Integration, Smarter Planet

Smarter Planet:
Smarter Transportation

Overview

Headquartered in Erlangen, Germany, Siemens Mobility Services is responsible for ensuring that its rail systems run smoothly at all times all over the world. The company generates optimized maintenance plans for its 50 major global customers, because every hour of vehicle downtime is expensive. Problems in infrastructure or rolling stock must therefore be detected and eliminated as quickly as possible to reduce the costs of each train over its lifetime and minimize the risk of breakdowns.

Business need:
Unplanned maintenance works are expensive for train operators: it is hard to predict when components will break down, and trains need to be taken out of service when repairs are needed.

Solution:
Siemens Mobility Services chose IBM® Maximo® Asset Management for Transportation as part of its maintenance solution, helping to optimize dynamic maintenance intervals based on data collected about the condition and actual usage of individual components.

Benefits:
Predictive maintenance reduces costs and out-of-service time significantly. Standardization cuts costs of implementing and operating customer maintenance systems by around 30 percent. IBM Maximo Asset Management prescribes individual maintenance intervals using data from sensors in the rail systems, helping Siemens to avoid accidents by identifying potential dangers early on. This helps Siemens to cut costs (for both itself and its customers) and increase availability at the same time.

Case Study

To read a German version of this case study, click here.

Smarter Transportation: Increased availability and lower maintenance costs
Instrumented: Streams of data from sensors on Siemens rail systems and their key components are combined with data on the production, usage and maintenance of trains in a data warehouse.

Interconnected: Siemens technicians and maintenance personnel stationed around the world access the central solution online and complete the tasks listed in automatically generated maintenance request forms.

Intelligent: The IBM Maximo solution provides deep insights into the predicted capacity and lifecycles of systems and components. With this information, Siemens can decrease the risk of breakdowns, reduce repair times, and cut maintenance costs.

Headquartered in Erlangen, Germany, Siemens Mobility Services is responsible for ensuring that its rail systems run smoothly at all times all over the world. The company generates optimized maintenance plans for its 50 major global customers, because every hour of vehicle downtime is expensive. Problems in infrastructure or rolling stock must therefore be detected and eliminated as quickly as possible to reduce the costs of each train over its lifetime and minimize the risk of breakdowns.

Lutz Grote, Senior Process Manager at Siemens Mobility Services, explains the main responsibilities of his department: “After we sell our products to a transport company, we are legally obliged to keep those systems running smoothly according to the terms agreed in the warranty. In practice, we usually do this by asking our own specialists to work on customer sites for long placements.”

After the warranty period has expired, Siemens Mobility Services usually negotiates long-term maintenance contracts with its customers. These contracts enable customers to fully concentrate on their core businesses and minimize risks by giving Siemens Mobility Services full responsibility for maintenance.

Train maintenance is very expensive, because trains and rail systems cannot operate when faulty components need to be replaced or repaired. Since systems and components in different customer environments have different lifecycles and wear out at different times, Siemens Mobility Services wanted to provide a new maintenance concept for its customers’ trains to make them run even more reliably than before.

Improving maintenance with integrated data
The new trend is service supported by diagnostics. Modern trains are equipped with intelligent sensors, recording devices and cameras, which constantly record variables such as the temperature, energy usage, switching time, condition, position and deterioration of components.

Sensor readings are sent to the maintenance system over telecoms links and via wireless networks in train stations. Continuous streams of data from sensors at railway crossings, tracks, signals and points are also sent to the maintenance system.

Siemens Mobility Services evaluates information about the condition of individual components to better predict when different parts need to be replaced or repaired. By dynamically optimizing maintenance intervals and predicting which components are likely to fail, Siemens Mobility Services has reduced the total costs of running its trains. This solution has enabled Siemens Mobility Services to cut maintenance costs, and at the same time improve its customer service in the long term.

IBM solution wins in the evaluation process
Siemens Mobility Services evaluated possible solutions looking at different criteria such as functionality, adaptability, scalability, costs, usability and prevalence, and decided to implement IBM Maximo Asset Management as its central asset maintenance solution.

It was an easy choice for Lutz Grote: “We selected IBM Maximo because it offered us an out-of-the-box solution with excellent functionality, a modular structure and worldwide support. The open standards interfaces enable us to integrate the solution with existing tools in our systems and at customer sites.”

Siemens Mobility Services worked with IBM specialists to place IBM Maximo at the heart of its maintenance strategy. When new maintenance projects begin, they are set up and run using Maximo, and some ongoing projects are being migrated to the new platform. Since Siemens Mobility Services can use the solution very competently, IBM rarely needs to offer support.

Within Maximo, important data relating to Siemens trains and essential components, such as bogies, axles and wheels, is recorded as an inventory list. The list includes information such as the product number, time of manufacture, manufacturer, periods of use, places of use, mileage and a full record of faults and maintenance works carried out. With this information, Siemens would be able to quickly and easily identify all the components in a series and examine them for faults in the event of a construction error.

Promptly identifying faulty components
The service provider’s expertise plays a key role in ensuring the success of this approach to maintaining trains. Based on its many years of experience with parts and components, Siemens Mobility Services technicians add optimal maintenance times to the Maximo records.

Based on these figures, Maximo calculates the most cost-effective maintenance schedules for each train, and provides the local teams with lists of essential maintenance tasks and replacement parts. Current mileages and faults of new components continuously flow into the system and are used to determine new maintenance schedules, optimized according to the revised data. The solution constantly learns, and informs technicians and development engineers of its findings.

The data collected by diagnostics and maintenance works flows into a central data warehouse. Siemens Mobility Services uses its own intelligent processes to analyze this data, together with the historical data of trains and components stored in IBM Maximo, to predict possible breakdowns.

Lutz Grote demonstrates the potential of predictive maintenance: “For example, the sound picked up by a trackside sensor may indicate that the bearings on a particular axle need to be changed. With this method, Siemens Mobility Services can use the most advanced monitoring and diagnostic tools to detect problems before they lead to major breakdowns, damage or accidents. Predictive and intervention-based maintenance reduces the service times required and extends maintenance intervals, both of which cut maintenance costs.

Lutz Grote says: “With unified configuration management and the advanced evaluation and reporting system in Maximo, we can compare different maintenance projects using the relevant data. These comparisons help us to further optimize our activities. IBM provides strong partnership in this endeavor, providing us with low operational risks, continuous product development and global support.”

By integrating data sensors on trains and in rail systems with a central asset management solution, Siemens Mobility Services has modernized its maintenance processes.

Faster repairs at lower costs
Continuously documenting solutions to technical problems in the global maintenance management system enables Siemens maintenance teams stationed all over the world to identify problems and carry out the correct repairs quickly. Shared knowledge increases the first-time-fix rates, and cuts maintenance costs.

Lutz Grote describes the benefits of the new solution for Siemens Mobility Services: “It is hard to quantify the value of high levels of standardization, improved data quality and integrated interfaces. But we can say that IBM Maximo has already reduced the costs of implementing and operating an enterprise asset management solution for new systems by around 30 percent. Furthermore, we have significantly improved our competitiveness because we can offer better services more efficiently.”

To further increase efficiency, Siemens Mobility Services is planning to expand its IBM Maximo Asset Management solution by using Radio Frequency Identification tags (RFID) for configuration management. Lutz Grote explains: “Using RFID tags, we will be able to see from a distance which wheels, axles and bogies need to be replaced, so technicians will no longer need to arduously identify all the serial numbers.”

Mobile solution improves productivity
The implementation of mobile maintenance request management is already underway, allowing technicians to receive relevant information about maintenance requests on their smartphones or tablet computers. By scanning barcodes, employees can record spare parts used and tasks completed in the central system quickly, accurately and easily. Mobile maintenance request management greatly improves the speed and quality of maintenance tasks, reduces time spent on manual administration, improves stock-keeping and speeds up the replacement of critical parts.
Lutz Grote is considering developing the system in other ways: “We are currently thinking about integrating a new module, which would enable us to use the IBM Maximo Asset Management system to manage the maintenance of railway lines. This would further improve safety in rail transportation.”­

Products and services used

IBM products and services that were used in this case study.

Software:
Maximo Asset Management

Legal Information

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