Back to Volume 4 | Summer 2019

Concurrent Digital Engineering for Capital Projects

Executive Summary

Ongoing analysis of efficiency in construction compared to other industries indicates construction continues to fall further behind. There are several reasons for this, but one that is most prevalent is the difference in approach to design and engineering between advanced industries such as aerospace, automotive, etc. and the construction industry.

Over the past several decades, advanced industries have used different processes, methods and tools to design and engineer their products. With the advent of ever-increasing computer power and network speed, artificial intelligence (AI), machine learning (ML), robotic process automation (RPA) and enormous data complexes fed by sensors, new and more effective ways to design and engineer will emerge, no doubt reshaping design and engineering as we know it today.

In this paper, the Project Production Institute (PPI) proposes an alternative approach for design and engineering of capital assets. PPI proposes Concurrent Digital Engineering as the framework forward.

Keywords: Operations Science; Concurrent Digital Engineering; Artificial Intelligence; Machine Learning; Automation

Authors:

Todd R. Zabelle, Founder & CEO, Strategic Project Solutions, Inc., tzabelle@spsinc.net
Alex G. Kunz, Principal, A.G. Kunz LLC, alex@agkunz.con
Ben Amaba PhD P.E., Chief Technology Officer (CTO) for Industrial Manufacturing and Engineering Sector
Artificial Intelligence and Data Science Elite Team, IBM, baamaba@us.ibm.com

James E. Craig P.E., Manager of Project Production Management & Innovation, Chevron, Project Resources Company, jim.craig@chevron.com



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