CIFE Center for Integrated Facility Engineering •Stanford University
CIFE Seed Proposal Summary Page
2008-2009 Projects
Proposal Title: Communicating, Integrating, and Visualizing MultiDisciplinary Design Processes
Principal Investigator(s): John Haymaker, Vladlen Koltun
Research Staff: Reid Senescu, Forest Flager, Ben Welle
Proposal Number: (Assigned by CIFE):
Total Funds Requested:
First Submission?
Yes If extension, project URL:
Abstract (up to 150 words):
Despite advances in Building Information Modelling (BIM) and building simulations, ineffective
communication and integration of process limits industry’s ability to improve design. Current
projects at CIFE are refining the characteristics and metrics for effective communication and
integration of processes by reviewing literature in process modelling and human computer
interaction, and observing and measuring current practice. In this seed project, we propose to
create and test an open-source tool called PIP (Process Integration Platform) that aims to help
distributed and collocated multidisciplinary teams to iteratively communicate and integrate, their
processes as well as to visualize the resulting information. This work has the potential to improve
design team productivity and effectiveness, resulting in better performing buildings and quicker
delivery.
1 Introduction: If BIM revolutionizes the process, where is the
revolution?
To some, BIM is a process (Eastman 2007). To many others, BIM at least changes the design
process (Autodesk; General Services Administration 2007). The association of BIM with process
change pervades Architecture, Engineering and Construction (AEC). Yet, little commercial
development of BIM is process-centric, and the major BIM-authoring tools do not provide explicit
support for defining and sharing processes. As a result, new tools are often applied to a process
that was not developed with current technology in mind. Therefore, while the capabilities and
efficiency of modeling and simulation tools expand exponentially, corresponding improvements in
design process efficiency and effectiveness have not been observed. This proposal describes the
characteristics for and presents a storyboard of a tool called PIP (Process Integration Platform)
which is designed to help designers communicate, integrate and visualize their multidisciplinary
design processes and the resulting information. First, we describe the observed problem in more
detail.
2 Observed Problems: Communication, Integration, an Visualization
of Multidisciplinary Processes
On the Stanford Graduate School of Business campus project, stakeholders used MACDADI
(Haymaker and Chachere 2006) to communicate the importance of material responsibility when
choosing structural systems. The engineer created schematic Revit Structure models of steel and
Haymaker, Koltun Communicating and Integrating Multi-disciplinary Design Processes 1
concrete structural options. Many tools (e.g. Athena, BEES, LCADesign) aim at assisting
designers in making environmentally sustainable material decisions. A researcher at CIFE had
even used an IFC model and LCADesign software to assess the environmental impacts of
another project on campus (Tobias and Haymaker 2007). However, given the time and budget
constraints, the Arup engineer was not able to find this model-based process nor create a new
process that would allow the team to effectively use the BIM model to further inform the team’s
structural system decision with environmental impact data. Project teams have difficulty
communicating design processes across projects.
On the same project, a lighting engineer needed to perform a daylight analysis to decide which
skylight configuration provided the best quality of light. The engineers’ process for constructing
this day lighting model from the Revit model involved over 15 distinct steps and 30 hours to
reformulate the model constructed by the architect to appropriately meet the requirements of his
Radiance day lighting analysis routine. Significant improvements in this process were possible,
but the designer and architect lacked the clarity of each other’s process to assure the right
information was contained in the architects’ model to eliminate many of these steps. A recent
survey (Flager & Haymaker, 2007) reinforces this observation, where respondents stated that
they spend nearly two thirds of their time managing information during concept design. Project
teams have difficulty integrating their processes among disciplines.
In both cases the designers produce performance feedback on a particular design option, but do
not have effective tools/methods to manage a range of options (design space) or to quickly
assess and visualize multidisciplinary system performance over that range. This made it
challenging for them to know what aspects of their designs had the greatest impact on building
performance, or to decide which designs provided the best value, and to understand which
design variables they should focus on moving forward to further improve the design. Project
teams have difficulty visualizing the results of their multidisciplinary design processes.
3 Intuition: A Process Integration Platform
In order to better communicate, integrate, and visualize design processes, we propose
practitioners require a web-based Process Integration Platform (PIP) (see Figure 2) with the
following characteristics:
Transparent: A transparent design process is quickly and accurately understood by those not
involved in the design.
Usable: Most engineers lack the extra time to document and improve their design process.
Features, such as drag and drop, drop down menus, and a familiar graphical user interface allow
new users to utilize PIP with no training.
Sharable: For effective communication of processes, sharing must be embedded in the design
process, so that engineers share their work by default. Still, engineers must be able to control
access privileges, allowing processes to be accessed by the public, by the project team, or only
to internal to the company.
Incentivized: The first users of PIP must be incentivized to embed the tool in their design
process. In addition, users must be incentivized to improve their processes. PIP must provide
mechanism that encourages this use by tracking and rewarding user input.
Searchable: Designers need to filter the searches and browse through the results in numerous
ways. They need algorithms that are intelligent and learn from their users. A structural engineer in
San Francisco, for example, is more likely to be looking for a process created by a structural
engineer in Los Angeles for finding the environmental impact of concrete than a plumbing
engineer in Thailand looking at the environmental benefits of bamboo.
Haymaker, Koltun Communicating and Integrating Multi-disciplinary Design Processes 2
Modular: Designers should be able to use old processes as the basis of new processes, and to
easily combine different disciplines processes – assembling multidisciplinary design processes by
combining several parts of other processes. The development of new design processes is a
creative design process in itself. Thus, organizational scientists would view modularity as
important, because, “creative solutions are built from the recombination of existing ideas”
(Hargadon and Bechky 2006).
Scalable: Designers need to use these processes at different levels of process and product
detail. For example, they may want to analyze just a particular room, the entire building, or the
entire project. Similarly, they may want to model a “Structural Material Responsibility Analysis”
node that lies within a process containing other analysis nodes such as “Structural Analysis” and
“Lighting Analysis.” This level of detail falls beneath an even higher level node called simply
“Analysis.”
Computable: Designers need to be able to use these process models to drive the automation of
their processes. The tool should contain general, simple mechanisms for helping user to invoke
the reasoning contained with each node in the process.
Support Design Space Exploration : Designers need to be able to view the results of several
iterations through these process models, to help them understand the solutions spaces they have
generated and analyzed to help them further refine their processes, and choose the best designs.
4 Points of Departure
Section 2 demonstrates how the lack of interoperability solution development and sharing
fundamentally limit BIM’s impact on AEC. Section 3 intuits several characteristics of a Process
Integration Platform that can address these limitations. Before proposing such a tool, we review
related work in defining and sharing design process information and assess the extent to which it
helps address these characteristics.
Integrated Project Delivery is a design, procurement, and construction approach that integrate
people, systems, business structures and practices (AIA, 2007). They specify design process
milestones and people included in each process, but do not formalize the information flow and
tools needed to ensure effective interoperable processes.
Lee et al. (2007) use Process Models to improve product data models. They argue that product
models must have a closer linkage with workflow and that mapping between processes and the
product model data should become an explicit part of the definition activity. Lee et al. seek to use
process models to develop future product data models. Information Delivery Manuals (IDMs)
are an integral component of the International Alliance for Interoperability’s (IAI) buildingSMART
initiative. The purpose of IDMs is to provide a human-readable integrated reference identifying
“best practice” design processes and the data schemas and information flows necessary to
execute effective model-based design analyses. However, current process modeling approaches
are formulated at an abstract level to define general data exchanges, processes, and design
team requirements, and have limited value as a project-specific design guidance and
management tool. That is, software developers, not designers, use these process models, and
they are thereof not intended to be transparent, usable, and sharable tools used by project teams.
Design Rationale research develops methods for better understanding the design process and
ideas for improving its current state by representing the reasons behind the creation of a
particular artifact (Moran and Carroll 1996). Conklin and Yakemovic use Issue-Based Information
Systems (IBIS) and process tracking to better understand and track reasons behind design
decisions (1991). Professionals rarely implement Design Rationale systems, because they are
not incentivized & computable -- designers thus struggle to perform the extra step to document
their rationale concurrently to performing design.
Haymaker, Koltun Communicating and Integrating Multi-disciplinary Design Processes 3
Several CIFE methods have advanced the design of process models for use by AEC
professionals in practice. Geometric Narrator (Haymaker 2006), enables a designer to build a
scalable, computable process from sub processes, but lacks an intuitive visual interface and
mechanisms to easily share and collaborate with these processes. Narratives are formal, visual
descriptions of the design process that include representations, reasoning, and their
interrelationships (Haymaker 2006). Narrator addresses the communication deficiencies of
Geometric Narrator, but at the expense of its integration power. Decision Dashboard (Kam, 2005)
improves transparency by clearly communicates options, alternatives, and criteria, and contains
some preliminary ability to compute values associated with these process nodes from information
contained in related nodes. However DD is a single use tool that does not easily support multi
user sharing and collaboration. MACDADI (Haymaker & Chachere, 2006) further communicates
the people, tools, goals, preferences, options, analyses, and decisions associated in design, and
contains some mechanisms for collaborative modeling, however, MACDADI is not well integrated
into BIM-based design and analysis tools, limiting its computable power.
Design Space Exploration and Visualization - Talton (2008) combines crowd-sourcing and
artificial intelligence to teach computers about the appearance of photo-realistic renderings of
trees. As engineers use the database, the computer learns what processes a designer may want
to follow based on the current context of the design problem. For example, the computer may
observe stakeholders, goals, preferences, the user, and the current state of information available
and then, suggest the most efficient and effective design processes to follow. We seek to apply
this “collaborative mapping of a parametric design space” to a user-created database of design
processes.
To overcome the difficulties encountered in AEC specific design process modeling and sharing
work, we look to knowledge sharing, crowd sourcing, and virtual world work in other domains.
Knowledge Sharing, (1996) explains a “project memory system” to explicitly define informal
knowledge and make it available to others. However, Conklin generally applies this system to
capturing knowledge from meetings, whereas we focus on capturing design process information.
Software, media, internet companies, and academia open up their domains and turn to the crowd
to tackle huge challenges in their industries. These Crowd-Sourcing Open Source movements
transcend traditional organizational science explanation for why people innovate. Hippel and
Krogh (2003) proposes that contributors must learn from the experience to contribute, should
profit from networking effects of sharing or at least, not lose any money by sharing, and must
receive “selective incentives,” such as a sense of ownership or enjoyment of the process.
As the capture of information exchange becomes more comprehensive, the process maps
become difficult to comprehend and share. Virtual Worlds can assure ubiquitous access and
appropriate level of detail for distributed project teams. Chaundhuri et. al. (2008). Similarly, to
methods currently employed in virtual worlds, AEC teams need to show processes of interest in
detail, while providing contextual relations to processes of lower level detail on the periphery.
5 PIP Storyboard
Inspired by the Points of Departure, the story below illustrates the PIP by offering an alternative
scenario to the motivating case study described in Section 2. For this proposal, we will focus on a
hypothetical energy analysis challenge. As described above, we’ve identified seven fundamental
characteristics a process tool must have: Transparent, Usable, Sharable, Incentivized,
Searchable, Modular, and Scalable, Computable, and Supportive of Design Space Exploration.
We use the initials T, U, Sh, I, Se, M, and Sc, C, and Dse to identify examples of these
characteristics in the description.
It is early Concept Design for a new library on the Stanford Graduate School of Business.
Through the use of MACDADI, the stakeholders have communicated their relative value for a
design solution with minimized life cycle and capital costs. The design team would like to consider
the impact of various building lengths, orientations, and window to wall ratios on capital and
lifecycle costs of the school design, considering both the structural and energy performance of
the different configurations. The structural engineer has already conducted structural analyses
Haymaker, Koltun Communicating and Integrating Multi-disciplinary Design Processes 4
on a number of design alternatives. Now the mechanical engineer will evaluate the impact of the
same alternatives on energy performance, and the consequent cost implications.
The mechanical engineer has a Revit model of the school building, and he wants to know how
modifications to the building envelop impact the thermal performance of the building. He wants to
search for a process that uses an object-oriented building model for assessing the energy
performance of different envelope designs. Checking the box “Internal Search”, he searches for
“Location: California” and “Output: Energy Consumption” <Se>. A number of different processes
with spreadsheets come up, but none linked to an object-oriented model. He searches external to
his company and removes the location, but includes “Input: Revit Model.” He finds a process
documented by CIFE that uses a Revit model that eventually feeds into Trane Trace and
eQUEST to output energy performance <T>. The engineer has access to these applications. The
only problem is that this project did not consider daylighting performance, and the team was
asked to assess the impact of daylighting performance on energy consumption <T>. Next, he
searches externally for a Daylighting Analysis (Step 1). He finds a large number of processes for
daylighting analysis, but only two that leverage an object-oriented BIM model. Both processes
use Revit, but one process posted by Arup has been used 21 times by other design firms in the
state, it’s ranked 4.5 stars, and has been used 251 times <T>, while the other has only been used
twice outside of the US. He quickly glances at the projects that the other firms have used the
process on, and he finds that it has been used on several schools. There are several steps in the
process that are not applicable to his particular project, so he copies only a portion of the process
(Step 2).
Going back to the project browser showing the original energy analysis process, the mechanical
engineer creates a node called Daylighting Analysis (Step 3). Double clicking on the node to open
the empty Daylighting Analysis window, he drags and drops the Daylighting Analysis process
<M> <U> (Step 4). Next, the engineer draws arrows from the Revit model node, energy
simulation node, thermal load node, and analysis presentation node to the new Daylighting node
<Sc> (Step 5). The mechanical engineer now has a process map showing the path from his
Revit model to charts showing the impacts of length, orientation, and window to wall ratio on
energy and daylighting performance. This process is shown in the figure on the next page. The
design team can now decided on an envelope design based not just on structural performance
and cost, but also on energy performance and cost – a goal heavily weighted by the stakeholders
<I>.
As part of company policy, he shares the new process with the public <Sh>. Sharing pays off for
the firm as a few months later, the public has greatly improved the available BIM-based energy
and daylighting process databases, and now his firm can more easily provide feedback on
projects using a wide range of BIM models <I>.
Haymaker, Koltun Communicating and Integrating Multi-disciplinary Design Processes 5
Haymaker, Koltun Communicating and Integrating Multi-disciplinary Design Processes 6
Haymaker, Koltun Communicating and Integrating Multi-disciplinary Design Processes 7
6 Research Methods
6.1 POD Review
We are currently reviewing the Points of Departure and observing and modeling several industry
projects to inform PIP’s features. This work is funded as part of projects with Arup, ConX,
Precourt Institute for Energy Efficiency, and Stanford University.
6.2 Define Desired Process Modeling Functionality
Based on a literature review and surveys of professional engineers, we will develop a framework
for describing processes based on the characteristics. The framework will include both an
underlying data schema and a graphical visualization (a notation).
6.2.1 Data Schema
An example of a data schema for each process node may include:
Actor: The person or organization responsible for the action
Input: The information on which the process is dependent
Tool: The method by which the input is transformed to output (usually, the tool is a
particular software).
Output: The information that the process creates.
Time to Execute: The average time required to transform input to output.
Update Status: Indicates whether input information has been changed since the last
process run.
Automation Status: Indicates whether the entire process is automated within the process
model or whether the user needs to run the process manually outside the process model.
6.2.2 Notation / Visualization
In this proposal, we use the Narrator notation shown in Figure 1 (Haymaker 2006). As we further
define PIP’s functional requirements, we will revisit and improve the notation.
Figure 1:Legend of process notation in Narrator.
6.3 Develop and Implement Process Searching and Prediction Algorithms
With increased emphasis on integrated design, design teams are unsure of the best method for
integrating traditionally disparate building analyses, such as daylighting, energy, and cost
analysis. The “best practice” design process for a particular project depends on project goals,
preferences, budget, schedule, and project team members. Given these inputs, we will develop
prediction algorithms to propose a project design process to the user. We will then implement
intelligent process searching tools into PIP, so users can find project-specific processes and
modify the automatically proposed process as required.
Haymaker, Koltun Communicating and Integrating Multi-disciplinary Design Processes 8
6.4 Develop interoperability between analysis and process models. FF
Current PIDO work. Demonstrate that these integrated processes are improve the efficiency of
design processes. Also, that they are robust and reusable on a variety of design problems.
6.5 Integrate design space visualization into process models. FF
Integrated processes allow for the generation of many more options and analysis results
than conventional design processes. Designers need a way of quickly documenting and making
decisions between design options. We propose a ways for designers to define and visualize
trade studies within the context of the process model.
7 Validation
7.1 Defining and Communicating Process
Once the tool is developed, we will test the methodology’s success with respect to the metrics
discussed below. We will use these metrics in three validation strategies:
•
•
•
Student and Professional Charrettes: Using sample design problems, we will use the tool
for some participants, and for others, we will not.
Professional Case Studies: We will integrate a few CIFE member design processes and
measure the effectiveness of the tool by comparing design processes before and after
integration.
Survey: After describing the tool in detail, we will survey students and professionals.
We will measure the tool with respect to the characteristics in Section Error! Reference source
not found., and we will measure improvements to the efficiency and effectiveness of design
processes after the tool’s introduction.
7.1.1
What Characteristics Does PIP Exhibit?
Frequency of PIP Use
We will include a hit count on the PIP browser. Using a pilot project, the counter will track how
often the site is accessed. As engineers’ use of the tool is voluntary, their use demonstrates that
the tool is incentivized and usable.
Link Development
The browser will measure the number of links created by engineers. This metric demonstrates
that engineers are incentivized to develop new processes. We will also look at links to see
whether they are being developed at different levels of detail to measure whether PIP is scalable.
Link Sharing
The browser will measure how often engineers copy and paste process links into their projects.
This copying represents process knowledge sharing, which verifies that the tool is sharable. It
also confirms that the tool is searchable, because engineers would not be able to copy other
processes if they could not effectively search and find an appropriate process. The metric also
measures transparency, because engineers would not use other processes unless they
understood them. Finally, link sharing shows that the tool is sufficiently modular such that links in
one process can be copied and applied to another process.
7.1.2
Are Design Processes More Efficient and Effective?
Percentage of Time Spent on Non-Value Added Work
As engineers use the browser, we will prompt them to track time spent recreating information
already present in a different format divided by total time spent on design. A reduction in nonvalue added work indicates increased efficiency.
Haymaker, Koltun Communicating and Integrating Multi-disciplinary Design Processes 9
Number of Design Options Considered
We will assume that the quantity of iterations is indicative of the effectiveness of the design
process. A design process that permits wide exploration of the design space improves the
likelihood of finding the optimal design.
Time Per Design Option
Engineers may choose not to run more iterations, but instead be more efficient. If time per design
of each option decreases, then efficiency increases.
Quality of Design Solution
MACDADI provides a subjective comparison of different projects. Using MACDADI as a metric,
we will measure project MACDADI scores that use PIP versus those that do not, to see whether
PIP aids in achieving project goals.
8 Research Impact
8.1 Industry Contribution: CIFE 2015 Goals
PIP promotes design process sharing. By bringing together global design processes in a common
language, PIP allows companies to more easily take innovative processes from other countries
and appropriately apply them to their design.
Sustainability requires design integration. PIP permits the project team to make more informed
multi-disciplinary decisions to ensure that designs meet stakeholder’s sustainability goals.
Project teams rarely fully understand the cost impact of their decisions on other disciplines. By
mapping out information for the entire project, participants can conform costs to the budget by
avoiding unforeseen design impacts.
Similarly, understanding the impact of design decisions or changes on other disciplines reduce
the likelihood of schedule delays. Moreover, increased sharing of design processes and design
process integration ensures that the project team is using the best design process available;
therefore shortening the schedule.
8.2 Academic Contribution
We will develop a new process modeling methodology that includes the characteristics discussed
above. We will develop new methods for sharing design process knowledge, integrating
processes, and visualizing the relationships between the design process and the design space.
9 Milestones
June 2008: Finish Description of tool
October 2008: Complete first prototype of tool
December 2008: Complete Student Charrettes
January 2008: Begin implementation of tool on CIFE member company projects
March 2008: Complete validation process
10 Risks
The development of the tool is dependent on the contributions of two computer science graduate
students that have yet to be determined.
Haymaker, Koltun Communicating and Integrating Multi-disciplinary Design Processes10
11 Funding
Not included in this version of the proposal
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Haymaker, Koltun Communicating and Integrating Multi-disciplinary Design Processes12