Early Contractor Involvement and Observational Method Supported with Artificial Intelligence for Equitable Risk Management - NAT2024

Society for Mining, Metallurgy & Exploration
K. Bhattarai David J. Hatem
Organization:
Society for Mining, Metallurgy & Exploration
Pages:
9
File Size:
218 KB
Publication Date:
Jun 23, 2024

Abstract

Effective risk management in major subsurface projects involves ways to mitigate adverse impacts to final design and construction approaches due to changed subsurface conditions. An Early Contractor Involvement (ECI) collaborated with Observational Method will be an effective contractual tool to address risk developed due to encountering differing site conditions. Observational Method (OM) can further be supported with artificial intelligence (AI) technologies with automated data-driven decision-making features in risk mitigation and implementation of proper design and construction approaches. This paper presents collaborative applications of ECI, OM, machine learning, and risk baselining in risk management and productivity enhancement in tunneling projects.
Citation

APA: K. Bhattarai David J. Hatem  (2024)  Early Contractor Involvement and Observational Method Supported with Artificial Intelligence for Equitable Risk Management - NAT2024

MLA: K. Bhattarai David J. Hatem Early Contractor Involvement and Observational Method Supported with Artificial Intelligence for Equitable Risk Management - NAT2024. Society for Mining, Metallurgy & Exploration, 2024.

Export
Purchase this Article for $25.00

Create a Guest account to purchase this file
- or -
Log in to your existing Guest account