Leveraging Quantity Surveying Data and BIM to Automate Mechanical and Electrical (M & E) Construction Planning

Despite the great potential of LPS and BIM to improve construction project productivity, the full integration of these modern production and information management systems at the data processing level is not yet achieved. After matching the literature to empirical studies in a Constructive Research...

Full description

Saved in:
Bibliographic Details
Published inApplied sciences Vol. 12; no. 9; p. 4546
Main Authors Sbiti, Maroua, Beladjine, Djaoued, Beddiar, Karim, Mazari, Bélahcène
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.05.2022
Multidisciplinary digital publishing institute (MDPI)
Subjects
Architecture
automation
BIM
Building information modeling
Collaboration
Construction industry
data warehouse
Decision making
Engineering
Engineering Sciences
Explicit knowledge
Information management
Knowledge management
Labor productivity
lean
LPS
Planning
Production management
data warehouse
lean LPS ® BIM data warehouse information management automation
automation
lean
information management
BIM
LPS
Online AccessGet full text
ISSN2076-3417
2076-3417
DOI10.3390/app12094546

Cover

More Information
Summary:Despite the great potential of LPS and BIM to improve construction project productivity, the full integration of these modern production and information management systems at the data processing level is not yet achieved. After matching the literature to empirical studies in a Constructive Research Approach, it emerged that very few studies have investigated how buildings’ data could be preserved and continuously evolve during the project lifecycle. Accordingly, we underline the potential role of data warehousing in rendering operational data as a strategic asset for decision making. These findings motivate the present research, which aims to capitalize on quantity surveying data in order to automate the generation of M & E installation schedules. This paper first introduces the system functional requirements. Then, it proposes a conceptual scheme for the planning data mart (a data warehouse subset dedicated to planning subject area). Furthermore, we shed light on the M & E fragnet standardization procedure and how data have been processed. Finally, we present the current software developments to demonstrate the feasibility of this concept.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2076-3417
2076-3417
DOI:10.3390/app12094546