System for Predictive Life cycle Management of Buildings and Infrastructures
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
The Life Cycle Management System (LMS) aims at supporting decision-makers and engineers in their efforts to achieve a more optimised proactive life cycle design and maintenance management strategy. LMS is an open and integrative system, which has to be adapted and developed in order to meet the needs and requirements of users. This process should be geared to and governed by the clients. The Architecture, Engineering, Construction and Facility Management (AEC/FM) sector includes all varieties of clients and stakeholders, all of them having different qualifications, possibilities and requirements for implementing, or increasing the feature of predictive maintenance management and optimised proactive strategies. The possibilities of adopting predictive maintenance management are dependent on the availability of performance-over-time and service life forecasting models and methods. The relevance of these models and methods depends on the required level of detailing. Furthermore, the use of the models and methods depends on the availability of reliable input data, such as material data and environmental exposure/in-use condition data. The thesis aims at analysing the possibilities of implementing predictivity in different fields of applications and at evaluating relevant tools facilitating management of information associated with predictive maintenance management systems. The thesis includes studies of three different clients and fields of application; Swedish Road Administration – management of bridges, Locum AB – management of hospital buildings, and Gävle Energi AB – management of district heating distribution systems. While the Swedish Road Administration is responsible to ensure an economically efficient, sustainable transport system for the society throughout the country, Locum AB and Gävle Energi AB compete on an "open" market. The Swedish Road Administration have gathered information about their bridges since 1944, for what reason their bridge management system includes a large amount of valuable data for performance-over- time analyses and service life forecasting. Locum AB has recently begun to systematically gather condition data, why the amount of data is limited. However, since the performance of buildings generally is well known, it is assumed that possibilities of implementing predictive maintenance management tools are rather good. Since district heating pipes are buried into the ground, it is difficult to assess the condition. Therefore, data for service life estimation rely mainly on damage reports. Environmental exposure data on macro or meso level can be obtained from meteorological and environmental institutes, thus making it possible to apply available dose-response and damage functions. Environmental exposure data on a micro level are lacking. Guidelines, methods and tools for environmental measuring and modelling on a micro level are therefore strongly needed. Efficient management of information plays an important role in predictive life cycle management systems. The ongoing development and implementation of open Building Information Model (BIM) tools in the AEC/FM sector is a promising progress of making the information management more cost effective and valuable, especially when open BIM solutions being fully integrated into the AEC/FM business. Geographical Information Systems (GIS) are tools for efficient handling of spatial positioned information. GIS provide possibilities of processing and presenting, e.g., environmental exposure data and environmental risk factors.
Place, publisher, year, edition, pages
Stockholm: KTH , 2009. , viii, 100 p.
Life Cycle Management System, service life, performance-over-time, maintenance management
IdentifiersURN: urn:nbn:se:kth:diva-10312ISBN: 978-91-7415-262-3OAI: oai:DiVA.org:kth-10312DiVA: diva2:214580
2009-04-24, Gävle Teknikpark, Hörsalen, Nobelvägen 2, Gävle, 10:00 (English)
Lacasse, Michel, Dr.
Sjöström, Christer, Professor
QC 201007162009-05-062009-05-062012-03-14Bibliographically approved
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