31st Annual Conference of the International Group for Lean Construction (IGLC 31) - Lille, France - 2023

https://doi.org/10.24928/2023/0140

Process Analysis With an Automatic Mapping of Performance Factors Using Natural Language Processing

Svenja Lauble1, Philipp Zielke2, Hongrui Chen3 & Shervin Haghsheno4

1Research Assistant, Karlsruhe Institute of Technology, Germany, +49-721-608-41513, [email protected]
22 Research Assistant, Karlsruhe Institute of Technology, Germany, +49-721-608-41518, [email protected] 3 M. Sc. Student, Karlsruhe Institute of Technology, Germany, +49-721-608-43650
3M. Sc. Student, Karlsruhe Institute of Technology, Germany, +49-721-608-43650, [email protected]
4Professor, Karlsruhe Institute of Technology, Germany, +49-721-608-42646, [email protected]

Abstract

In lean construction projects, much information is collected during the process analysis with the trades. This data is increasingly documented as a reference for use in future construction projects. By doing this, efficient methods are required to use this data. Often, the unstructured naming of data is a challenge for a rule-based allocation of information, and manual work is required to identify the needed data. Therefore, the aim is to develop an automatic mapping of historical performance factors to the tender specifications of a new construction project. To support the process analysis with historical project data, a case study is executed using Natural Language Processing (NLP). With a NLP model, the process descriptions from the tender specifications of the new construction project can be compared with a master database, to filter the right performance factor and calculate the duration for a process. This procedure can be used to support the further process analysis together with the trades to generate a validated construction schedule. The case study shows promising results in the prediction results. First, the mapping quality and second, the prediction accuracy are evaluated. With the developed mapping concept, last planners can validate their estimations of durations in lean construction process planning with a target to support stability in a project. Still, a more detailed description of the processes could increase the prediction results.

Keywords

Digitization, lookahead planning, work structuring, process, complexity.

Files


Full Text
 

Reference

Lauble, S. , Zielke, P. , Chen, H. & Haghsheno, S. 2023. Process Analysis With an Automatic Mapping of Performance Factors Using Natural Language Processing, Proceedings of the 31st Annual Conference of the International Group for Lean Construction (IGLC31) , 59-68. doi.org/10.24928/2023/0140

Download: BibTeX | RIS Format

 

Founded in 1993, the IGLC is an international network of researchers from practice and academia in architecture, engineering, and construction (AEC) who feel that the practice, education, and research of the AEC industry have to be radically renewed in order to respond to the global challenges ahead.

2015 © All Rights Reserved.