Leveraging Supply Chain Data for Structural Steel Design

Project Team

M. Fischer, F. Flager, S. Barg, H. Hamamji, P. Havelia, B. Peng, M. Ramsey, F. Ranalli, T. Trinelle

Problem Addressed

Architects and engineers today lack methods to accurately assess the cost and material availability of steel structures for buildings and civil infrastructure during early design. Conventional practice is to estimate cost based on the total weight of the steel structure, however, the majority of the total cost of a completed steel structure can be attributed to the fabrication and erection which do not necessarily scale linearly with material weight. The availability of material also varies based on section type and size. Member selection can, therefore, also have a significant impact on procurement time and, ultimately, the project delivery date. Early design decisions can, therefore, have a significant impact on cost, procurement time and, ultimately, the project delivery date. 

Research Objectives

The goals of the project are to enable architects and engineers to: 

  • Quickly and accurately estimate the cost and material availability of structural design alternatives;
  • Rapidly and systematically search through large numbers of design alternatives to identify the most economical design solutions that satisfy project schedule and structural performance criteria.

Research Approach

Our approach is work with suppliers, namely steel mills, fabricators and erectors, to accurately estimate steel structure cost and material availability. The estimation method has the following steps:

  1. Designer submits analytical model describing steel material specification, member centerline geometry, and connection type specification.
  2. The analytical model is automatically detailed according to code requirements and user preferences to produce specific quantities that are required for supplier estimates (e.g., cut lengths, weld volumes by type). 
  3. The model material quantities are checked against the mill inventories storied in a secure online database to determine material availability. 
  4. Unit cost parameters maintained individual steel suppliers in a secure online database are applied to the quantities to produce the cost estimate.

The research team is developing the following methods to utilize the cost and material availability estimate provided to inform design decision-making: 

  1. Model-based visualization: visualization of availability by member and cost by member and by connection in the context of the building information model.
  2. Computational design optimization: Utilization of computer algorithms to automatically generate and evaluate large numbers of design alternatives in order to identify the best performing solutions from within a range of options defined by the project team.

Interim Results

MODEL-BASED VISUALIZATION

To quantify the impact of providing engineers with real-time feedback on how their structural design decisions impact the project cost, the research team conducted a design charrette involving 28 structural engineers with an average of 8 years of experience. Engineers were divided into two groups, one group had access to visual cost feedback and the other did not. The design problem asked engineers to size members for a steel moment frame structure with known loading in order to minimize total frame cost will meeting structural performance criteria for strength and serviceability. The results of the experiment demonstrated that engineers provided with BIM-based visual cost feedback were able to design structures  that were 13% more economical, on average, compared to engineers without such tools. For more information, see the Documentation section below. 

COMPUTATIONAL DESIGN OPTIMIZATION 

Walt Disney Imagineering (WDI) has engaged with the research team to apply a topology and member sizing computational design optimization (CDO) methodology developed collaboratively by CIFE and Disney Research China to their rockwork design process, specifically to a large mountain show element supported by a steel braced-frame structure that is part of the Adventure Isle theme park project that is currently under construction in Shanghai. Interim results of this case study application show that the CDO method compares favorably to the structural design completed using conventional methods: the cost of the optimized design is 21% lower than the original design and reduces the number of structural elements that must be installed on site by over 70%. For more information, see the Documentation section below. 

Expected Impact

The research team expects that this work will enable designers to make better decisions and that it will demonstrate the value of improving vertical integration of project information in AEC industry. Fundamentally improving the design process in this way will promote design innovation by making it easier to analyze and iteratively improve new design concepts based on current and accurate data provided by the product supply chain. Ultimately, this will result in higher quality and more economical buildings for the public.

Presentations

Using Fabricator Data to Optimize Steel Structures.” Fabricator’s Forum, Autodesk University. Las Vegas, NV. November 30, 2015.   (see Documentation for slides)

“Empowering Fabricators and Suppliers to Improve the Design of Steel Structures.” NASCC – The Steel Conference. Orlando, FL. April 15, 2016.  (see Documentation for slides)

“The Internet of Steel Things: Optimizing Structural Designs in a Connected World.” Engineering News Record FutureTech Conference. San Francisco, CA. June 1, 2016. (see Documentation for slides)

“Optimizing Steel Structures Using Real-time Market Data." Washington Buiding Conference - Leading Edge Technology Conference. Washington D.C. March 9, 2017.

Publications

Ranalli, Filippo, Forest Flager and Martin Fischer (2017).  ""A Ground Structure Method to Minimize the Total Installed Cost of Steel Frame Structures." Working Paper 1441. Center for Integrated Facility Engineering: Stanford University. (see Documentation for manuscript)

Barg, Steve, Forest Flager and Martin Fischer (2017).  "An Analytical Method to Estimate the Total Installed Cost of Steel Frames During Early Design." Technical Report 220. Center for Integrated Facility Engineering: Stanford University. (see Documentation for manuscript)

Hamamji, Henry. 2017. 'Quantifying the Impact of Providing Model-based Cost Visualization on the Design of Steel Frame Structures'. Engineers Thesis, Department of Civil and Environmenal Engineering, Stanford University. (see Documentation for manuscript) 

Havelia, Pratyush. 2016. 'A Ground Structure Method to Optimize Topology and Sizing of Steel Frame Structures to Minimize Material, Fabrication and Erection Cost'. Engineers Thesis, Department of Civil and Environmenal Engineering, Stanford University. (see Documentation for manuscript) 

IN PREPARATION

Barg, S. K., H. Hamamji, P. Havelia and F. Flager (2016). "An Analytical Method to Estimate the Total Installed Cost of Steel Frames During Early Design."  Automation in Construction. (in review; submitted February, 2017).

Peng, B. and F. Flager (2016). "Sizing and Connection Type Optimization of Steel Frame Structures Using Dimension Increasing Search." Structural and Multidisciplinary Optimization. (in preparation; submission planned July, 2017)

Documentation

AttachmentSize
CIFE Seed Proposal - Written216.81 KB
CIFE Seed Proposal - Presentation Slides1.3 MB
Autodesk University 2015 - Presentation Slides1.61 MB
NASCC 2016: The Steel Conference - Presentation Slides1.43 MB
ENR FutureTech 2016 - Presentation Slides6.08 MB
Havelia Engineer Thesis.pdf1.05 MB
Hamamji Engineer Thesis.pdf1.27 MB
CIFE Technical Report 220.pdf1.62 MB
CIFE Working Paper WP141.pdf1.09 MB

Last modified Tue, 8 Aug, 2017 at 14:15