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SMARTS-Based Decision Support Model for CMMS Selection in Integrated Building Maintenance Management

Title
SMARTS-Based Decision Support Model for CMMS Selection in Integrated Building Maintenance Management
Type
Article in International Scientific Journal
Year
2023
Authors
Rodrigues, RC
(Author)
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Hipólito Sousa
(Author)
FEUP
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Gondim, IA
(Author)
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Journal
Title: BuildingsImported from Authenticus Search for Journal Publications
Vol. 13
Final page: 2521
ISSN: 0007-3725
Publisher: MDPI
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Publicação em ISI Web of Knowledge ISI Web of Knowledge - 0 Citations
Publicação em Scopus Scopus - 0 Citations
Other information
Authenticus ID: P-00Z-53J
Abstract (EN): An Integrated Maintenance System (IMS) represents a coordinated methodology including different maintenance policies, such as preventive and corrective. These systems rely on Computerized Maintenance Management Systems (CMMSs), specialized software available from multiple suppliers. Given the diverse features of commercial CMMS software, this work aims to develop a decision support model for CMMS evaluation emphasizing an integrated perspective within IMS. A Simple Multi-Attribute Rating Technique using Swings (SMARTS) method was used to build the decision model. Five existing market software were evaluated, and a minimum profile was defined for IMS requirements. Three of the assessed software types met these minimum IMS requirements, while the absence of certain features limited scores for others. The results obtained from the decision support model provide a simple and synthetic way to support decision-makers and promote a systemic view of the software features. The evaluation model has the advantage of adopting criteria that integrate software evaluation; its framing in a building maintenance management model; and new technological trends, such as Building information modeling (BIM), Virtual Reality (VR), Augmented Reality (AR), and Internet of Things (IoT). Considering these outcomes, future developments and alternatives can capitalize on these trends.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 13
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