Quality (philosophy)

External quality assessment

Quality assurance

Engineering

Philosophy

Transport engineering

Compatibility (geochemistry)

Computer security

Building information modeling

Set (abstract data type)

Civil engineering

Computer science

Chemical engineering

Construction engineering

Business

Information security

Epistemology

Information assurance

Operations management

Grading (engineering)

Programming language

Engineering management

Automation in Construction

A primary motive for adopting the methodology Building Information Modeling (BIM) in planning processes is to improve planning accuracy, cost security, and in turn quality. Up to now, however, a generally applicable, standardized means of validating design quality has been lacking. To address this shortcoming, this article presents 14 quality parameters in the domains of clash detection, semantics as well as quantities and costs, that apply to the field of infrastructure planning. The sets of rules outlined in the article are adaptable and extendable in order to respond flexibly to different model structures. The investigation focuses on how important and recurring tests can be carried out automatically and how to make the results analyzable in a transparent and standardized manner. The proposed concept thoroughly extends well-known methods such as attribute testing and clash detection analysis of the 3D model. Doing so, the paper presents a set of novel methods for quality assurance, including 4D clash detection and checks for semantic-geometric coherence. The paper discusses in detail: the influence of modeling errors on clash detection, the difference of 3D and 4D clashes, formal methods for checking the correct linkage between 3D BIM and the bill of quantities, formal approaches for checking the semantic-geometric coherence of BIM objects. The quality assurance concept presented in the article concludes with a standardized evaluation for the individual quality criteria using a school grading system, traffic light, and percentage scale. Finally, the concept is applied in a comprehensive case study on a large-scale infrastructure project and the results of the formal quality assessment are presented.

Model-based quality assurance in railway infrastructure planning