| DOI | Trouver le DOI : https://doi.org/10.1080/09613218.2018.1459004 |
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| Auteur | Rechercher : Gunay, H. Burak; Rechercher : Shen, Weiming1; Rechercher : Yang, Chunsheng2 |
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| Affiliation | - Conseil national de recherches du Canada. Construction
- Conseil national de recherches du Canada. Technologies numériques
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| Format | Texte, Article |
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| Sujet | building operations; building performance; diagnostics; facilities management; fault detection; HVAC systems; maintenance; operator logbooks; text-mining |
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| Résumé | Operators’ work order descriptions in computerized maintenance management systems (CMMS) represent an untapped opportunity to benchmark a facility’s maintenance and operation performance. However, it is challenging to carry out analytics on these large and amorphous databases. This paper puts forward a text-mining method to extract information about failure patterns in building systems and components from CMMS databases. The method is executed in three steps. Step 1 is pre-processing to convert work order descriptions into a mathematical form that lends itself to a quantitative lexical analysis. Step 2 is clustering to focus on interesting sections of a CMMS database that contain work orders about failures in building systems and components – rather than less interesting routine maintenance and inspection activities. Step 3 is association rule-mining to identify the coexistence tendencies among the terms of cluster of interest (e.g. coexistence of the terms ‘radiator’ and ‘leak’). This text-mining method is demonstrated by using two data sets. One data set was from a central heating and cooling plant with four boilers and five chillers; the other data set was from a cluster of 44 buildings. The results provide insights into per equipment breakdown of failure events, top system and component-level failure modes, and their occurrence frequencies. |
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| Date de publication | 2018-04-30 |
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| Maison d’édition | Taylor & Francis |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Numéro NPARC | 23003958 |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | 7c420300-9790-4255-9b1b-bcefb642f8e8 |
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| Enregistrement créé | 2018-08-24 |
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| Enregistrement modifié | 2020-03-16 |
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