University of Tübingen

Analytics embedded into asset management to keep critical campus and hospital systems running strong

Published on 29-Oct-2013

"The insights we’ve gained have enabled us to make more proactive maintenance decisions and to deploy our resources more efficiently." - Stefan Nussbaum, head of operations, technical support team

Customer:
University of Tübingen

Industry:
Education

Deployment country:
Germany

Solution:
Asset Management, Smarter Planet

IBM Business Partner:
IBM Business Par tner EAM Sof tware GmbH

Overview

University of Tübingen is a public research university located in the city of Tübingen, Baden-Württemberg. It is one of Germany’s most famous and oldest universities, internationally noted in medicine, natural sciences and the humanities. The affiliated University Hospital Tübingen functions as a district hospital for the city and district of Tübingen in southwestern Germany.

Business need:
With thousands of assets to support across multiple campuses and clinics, the university’s technical support team needed to prioritize workloads

Solution:
The solution uses analytical models to guide technicians, for the hospital and for the university as a whole.

Benefits:
The solution covers 100 percent of the assets of the hospital and the university. In addition to cutting failure rates, moving from a reactive to a predictive maintenance mode has increased the technical staff ’s productivity by making it possible to reduce travel distances, to group work orders when it makes sense and to optimize inventory planning so that spare parts are there when needed.

Case Study

University of Tübingen is a public research university located in the city of Tübingen, Baden-Württemberg. It is one of Germany’s most famous and oldest universities, internationally noted in medicine, natural sciences and the humanities. The affiliated University Hospital Tübingen functions as a district hospital for the city and district of Tübingen in southwestern Germany.

The Opportunity
With thousands of assets to support across multiple campuses and clinics, the university’s technical support team needed to prioritize workloads using a systematic and proactive approach that would cut costs, optimize the allocation of tight budgets and maximize operational stability.

What Makes It Smarter
The solution uses analytical models to guide technicians, for the hospital and for the university as a whole, regarding whether to replace or repair broken parts for systems — ranging from emergency backup generators to ventilation and fire control systems — and, if a part’s usage levels and past failure patterns point to failure risk, advise preventive repair or replacement. Dashboard insights help dispatchers prioritize pending work orders and stay within budget.

Real Business Results
The solution covers 100 percent of the assets of the hospital and the university. In addition to cutting failure rates, moving from a reactive to a predictive maintenance mode has increased the technical staff ’s productivity by making it possible to reduce travel distances, to group work orders when it makes sense and to optimize inventory planning so that spare parts are there when needed. And with more transparent access to decision-support data, dispatchers can better prioritize work order scheduling based on part cost, budgetary sense and regulatory requirements.


For More Information
Please contact your IBM representative or IBM Business Partner.
Visit us at ibm.com.

To learn more about University of Tübingena, visit
www.uni-tuebingen.de/en.

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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