California Polytechnic State University, San Luis Obispo
College of Architecture and Environmental Design
Project 10, Number 3 November 2010
Determining Multidiscipline Time ‐ Space Relationships for Building Information
Modeling of Mechanical, Electrical, and Plumbing Systems (MEP) Systems
Thomas M.
Korman, Ph.D, PE, PLS
Associate Professor
Department of Construction Management tkorman@calpoly.edu
Summary
The recent introduction of BIM software solutions is able to provide a virtual construction solution, which includes the following elements: design (3 ‐ D), scheduling (4 ‐ D), cost (5 ‐ D) and life ‐ cycle (6 ‐ D).
These elements can be interlinked; however, practitioners still face similar problems as they have in the past.
Entry of incorrect data or faulty assumptions into the BIM system results in project personnel being misled by the output from the system.
While most BIM software solution have the ability to contain information and data regarding a project, they do not contain knowledge ‐ based logic and reasoning structures to assist users during the planning and design and therefore lack the capability to assist in the resolution of time ‐ space conflicts.
To be able to fully realize to the potential of BIM software solutions in the future, knowledge capture and the integration of logic and reasoning structures is imperative.
As stated above, by using BIM software solutions, the determination of physical interferences has become a mundane task.
BIM software solutions are able to contain scheduling (4 ‐ D) data and link it with the geometric model.
The research funded by the PDCI assisted me to devote the necessary time to collect the data needed to prepare an improved proposal to submit
to NSF under the Research for Undergraduate Institutions (RUI) grant program.
This involved identifying and classifying time ‐ space relationships for MEP systems and developing a preliminary theory for a logic
and reasoning structure to assist with the project scheduling of MEP systems in BIM
Table of Contents
Executive Summary......................................................................................................................... 1
NSF Grant Application..................................................................................................................... 3
Project Summary ......................................................................................................................... 3
Project Description ...................................................................................................................... 4
Background, Motivation, and Point of Departure for the Research ...................................... 4
Research Questions ................................................................................................................ 9
Research Objectives.............................................................................................................. 10
Research Methodology.............................................................................................................. 10
Knowledge acquisition.......................................................................................................... 10
Knowledge representation ................................................................................................... 11
Building reasoning structures ............................................................................................... 12
Methodology Example.......................................................................................................... 14
Project Work Plan ...................................................................................................................... 16
Year 1 – Data Acquisition, Identification, and Analysis ........................................................ 16
Year 2 – Prototype Tool Development, Testing, and Validation .......................................... 17
Year 3 – Development of Teaching Modules and Dissemination......................................... 17
Significance and Impact of the Research................................................................................... 18
Intellectual Merit .................................................................................................................. 18
Broader Impacts.................................................................................................................... 18
Educational and Outreach Activities..................................................................................... 19
Appendix – Field Notes ................................................................................................................. 20
Executive Summary
Building Information Modeling (BIM) technology provides a virtual construction solution including four elements: design (3 ‐ D), scheduling (4 ‐ D), cost (5 ‐ D) and life ‐ cycle (6 ‐ D), where these elements can be interlinked.
Prior to the use of BIM software solutions, the collusion detection phases of mechanical, electrical, and plumbing (MEP) coordination was a major challenge.
The process involved overlaying two ‐ dimensional drawings representing each trade over each other to determine physical interferences in the effort to spatially arrange the numerous components of each MEP system.
Using BIM technology, the collusion detection task has become an automated routine task.
With the ability of BIM systems to associate scheduling (4 ‐ D) data, time ‐ space conflicts can also be identified between multiple disciplines;
however, no logic or reasoning structure currently exist to resolve them.
In July 2009, I submitted a multi ‐ year research proposal to the National Science Foundation
(NSF) titled “Non ‐ Concurrent Product Lifecycle Integration for Co ‐ Existing Systems” in the amount of $453,933 under the Faculty Early Career Development (CAREER) grant program.
The premise of the research proposal expanded on my research from my doctoral dissertation on
Mechanical Electrical and Plumbing (MEP) coordination, where I studied the MEP coordination process and identified critical factors necessary for consideration of the spatial arrangement of
MEP systems.
This work was completed prior to the use and development of BIM technology software.
The spatial coordination of the MEP systems has always been a challenge due to the fact that it must consider critical design, construction, performance, operations, and maintenance criteria.
With the recent development of BIM software, specialty contractors have been able to greatly reduce the number of physical interferences of MEP systems with each and with the structural and architecture of a facility prior to the construction.
This is primarily due to the ability of specialty contractors to represent the MEP building systems in a single three ‐ dimensional model and perform collision checks to identify physical interferences between the multiple systems.
The research proposed under the CAREER grant sought to identify and classify time ‐ space relationships for MEP systems and develop a logic and reasoning structure to assist with project scheduling in BIM systems, and as the course co ‐ champion for the Specialty Contracting Construction Management course in the CAED
Construction Management Department, it has always been a primary interest of mine to further pursue research in MEP coordination considering the scheduling, estimating, and life ‐ cycle aspects of mechanical, electrical, and plumbing systems.
Therefore, the emphasis of the research proposal was to first generate fundamental knowledge regarding the integration of non ‐ concurrent product lifecycles for co ‐ existing systems, and second, develop a new comprehensive theory for integrating the non ‐ concurrent lifecycles for co ‐ existing systems for
use in performing coordination.
The recent introduction of BIM software solutions is able to provide a virtual construction solution, which includes the following elements: design (3 ‐ D), scheduling (4 ‐ D), cost (5 ‐ D) and life ‐ cycle (6 ‐ D).
These elements can be interlinked; however, practitioners still face similar problems as they have in the past.
Entry of incorrect data or faulty assumptions into the BIM
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system results in project personnel being misled by the output from the system.
While most
BIM software solution have the ability to contain information and data regarding a project, they do not contain knowledge ‐ based logic and reasoning structures to assist users during the planning and design and therefore lack the capability to assist in the resolution of time ‐ space
.
conflicts.
To be able to fully realize to the potential of BIM software solutions in the future, knowledge capture and the integration of logic and reasoning structures is imperative.
As stated above, by using BIM software solutions, the determination of physical interferences has become a mundane task.
BIM software solutions are able to contain scheduling (4 ‐ D) data and link it with the geometric model.
The research funded by the PDCI assisted me to devote the necessary time to collect the data needed to prepare an improved proposal to submit to NSF under the Research for Undergraduate Institutions (RUI) grant program.
This involved identifying and classifying time ‐ space relationships for MEP systems and developing a preliminary theory for a logic and reasoning structure to assist with the project scheduling of
MEP systems in BIM
I would like to acknowledge and thank Rosendin Electric, Marelich Mechanical, and the
International Brotherhood of Electrical Workers (IBEW) who assisted me in collecting data for this project as well as the staff at Stanford Universities Center for Integrated Facility
Engineering (CIFE) for their time and assistance in assisting me during my office and site visits.
During the next month, I will be submitting the proposal to NSF under the RUI grant program.
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NSF Grant Application
Project Summary
This proposal proposes to support an integrated program of research and teaching that will both strengthen professional engineering design activity and enhance engineering and construction education by broadening the fundamental understanding of integrating non ‐ concurrent lifecycles for co ‐ existing systems, as applied to the active systems of buildings.
The educational component of this proposal promotes the explicit recognition of system lifecycles as a common thread through the engineering design and construction curriculum.
It will prepare students for a recently approved integrated design and construction curriculum and beyond, where they are engaged in the solution of realistic problems as they study a specific sector of the construction industry in a synergistic, multi ‐ disciplinary project ‐ based learning environment.
Research in the role of integrating non ‐ concurrent lifecycles for co ‐ existing systems will complement the educational efforts described above.
This research focuses on advancing a more thorough and fundamental understanding of the "systems integration and assembly" and its application through the extension of current design, analysis, fabrication, and
assembly methods.
The basis for this research is the development of a model to assist with the constructability and coordination evaluations for the active systems of a building; i.e., mechanical, electrical, plumbing, etc.
The broader impacts of these activities include: (a) involvement of engineering and construction management students in the entire life ‐ cycle of a project – conceptual design through disposal/recycle, (b) collaboration with other educational institutions ‐‐ universities, community colleges, and institutions serving underrepresented groups ‐‐ in the dissemination of teaching techniques and materials related to constructability and coordination, (c) outreach to K through12 students and teachers in "science summer camp" and ACE mentorship programs, (d) participation in the development of national standards for building information modeling that accurately reflect the current state of knowledge in systems lifecycles, and (e) partnering with industry to validate research results and facilitate the transfer of new analysis
methods to practitioners.
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Project Description
Background, Motivation, and Point of Departure for the Research
The active systems of a building/facility include, but are not limited to the mechanical, electrical, plumbing, fire detection and protection, and control and communication systems.
These systems co ‐ exist to meet the programming expectations of the facility users.
They are critical to the building’s function and must meet performance expectations for comfort and safety.
For example, the mechanical system provides, circulates, filters, and tempers fresh air for occupants.
The electrical system provides energy to power lighting and electrical circuits to serve workspace equipment as well as for other building systems.
The plumbing system provides water to plumbing fixtures and conveys water utilized by building occupants to an exit point.
The fire detection and protection system provides a safety mechanism by sensing and detecting the presence of a fire and executing a method to extinguish and deter the spread of a fire.
The control and communication systems provide a means for monitoring the facility and enable communication among occupants.
It is not uncommon to encounter facilities with as many as a dozen or more co ‐ existing systems depending on the programming of the facility.
For example residential building may have as little as four systems, while a biotechnology manufacturing facility may have eighteen systems in order to meet key manufacturing equipment requirements.
As shown in Table 1, the active systems of a building range from 25 to 70 percent of the total building cost.
In an effort to create a sustainable environment, green building construction practices will force the technology for these systems to evolve.
Table 1 – Building systems as a percentage of total building cost (Korman)
Facility Type Percentage of total building cost
High Medium Low
Biotechnology plants
Commercial office buildings
Heavy industrial plants
Hospitals
70
40
60
50
55
30
50
40
45
25
40
30
Multi ‐ residential complex
Research laboratories
35
50
30
40
25
30
Semiconductor plants 65 50 40
A phase common to all buildings during the project delivery process is the arrangement and positioning of all active building system components (piping, conduit, equipment, etc.) within the constraints of the buildings architecture and structure.
Most engineering and construction professionals refer to this phase as building systems coordination.
Building systems coordination involves defining the locations for and arranging the components of building systems, in what are often congested spaces, in order to avoid physical interferences, so that they fit within the constraints of the building architecture and structure.
The problem, however, is that simply arranging all building system components so that they do not physically interfere with each other does not ensure constructability of the systems, nor does it ensure
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that the systems have been well coordinated.
Furthermore, during the building systems coordination process, the entire project lifecycle knowledge is rarely considered, which means that design, construction, operations, and maintenance criteria, is overlooked and ignored, which ultimately affects the systems fabrication and installation cost, performance, and the
amount of energy consumed by the system over its lifespan.
Although the life spans of the active building systems overlap, they are not necessarily installed at the same time, they are often commissioned and decommissioned at different times, and their life spans are rarely the same.
As technology for the individual systems evolves, upgrades are required at different times and maintenance schedules for each system do not coincide with one other, either.
In addition, expansion of systems is often required as the programming for the building/facility changes.
Each individual system requires a specialized knowledge for commissioning, operations, maintenance, and possibly future expansion.
Therefore, the active building systems are essentially co ‐ existing systems with non ‐ concurrent lifecycles.
In order for the building systems coordination effort to be considered successful, the building systems coordination process must comply with diverse design, construction, operations, and maintenance criteria.
Ideally, the result of the coordination evaluation is the most economical arrangement that considers the lifecycle of each building system, meeting critical design, construction, performance, operations, and maintenance criteria.
The level of difficulty
associated with this process directly relates to the complexity and number of active building systems necessary for the programming of the building.
Figure 1 – Rendering of building systems located within a typical building corridor
While construction cost estimators are able to quantify the building system’s cost, the cost associated with building systems coordination is more difficult.
Many engineering and construction industry professionals have cited building systems coordination as one of the most
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challenging tasks encountered during the construction project delivery process.
Most professionals agree that the difficulty is due to inherent fragmentation that exist throughout the architecture, engineering and construction (AEC) industry.
For example, each system is independently designed without consideration of the other.
Furthermore fabrication and installation of each system is performed by others unassociated and unfamiliar with the design of the system they install.
There are many reasons why this occurs: engineering designers usually limit themselves to the design of one type of system due to the specialized knowledge that is required to perform the engineering design.
Specialty construction engineers, who fabricate and install the systems, usually limit themselves to the fabrication and installation of one type of system due to the large capital investment required to manufacture and fabricate
each system.
During the building system coordination phase, the multiple organizations for each system must interact to share critical knowledge in order to converge.
However, there are no current guidelines to assist architects and engineers in the coordination of building systems.
The current work process is as follows: Engineering design consultants or design ‐ build construction engineers design their own systems (mechanical, electrical, plumbing, etc.), independently focusing only on their systems.
(There are often multiple design consultants due to the specialized knowledge required and national and state board licensing requirements for the design of various building systems.) The design is then provided to a specialty construction engineer who will fabricate and install the multiple systems.
(Again, there are typically different construction engineers for each individual building system due to the specialized training required and state licensing requirements.) Contract specifications commonly place the responsibility of a constructability and coordination evaluation of the building systems on the specialty construction engineers who fabricate and install the systems.
During the process, in the effort to eliminate the physical interferences between the multiple building systems so that they can be fabricated and installed by the multiple specialty construction engineers, the design intent and performance of the building systems is often compromised in order to
position the systems’ components in the allocated space.
Recently, a technology known as Building Information Modeling (BIM) software has assisted in improving the current process, primarily with its ability to represent the co ‐ existing building systems in a single three ‐ dimensional model and with its capability to identify physical interferences between the multiple systems.
However, the primary limitation of BIM technology is that it only resolves the physical interferences, whish as stated above is know by most familiar with the product design cycle, as configurationally design.
The current use of BIM
technology does not consider the other diverse design and other product life ‐ cycle criteria as shown in Figure No.
2.
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Maintenance
Disposal/ recycle
Evaluate market share, quality and cost
Perceived need or technical opportunity
Conceptual product
Custom er support
Synthesis
Customer feedback
Distribution
Design of design process
Mass production Abstraction
Organization assembly
(staff + tools)
P refabrication or manufacturing of small lots
Creation of construction equipment or m anufacturing facilities
Detailed design of construction/ manufacturing process
Configurational
Detailed design or simulation design
Building System s coordination using
BIM
Figure 2 – Tasks/Information related to the product cycle
As mentioned above, each active building system has a unique product lifecycle, but must co ‐ exist within the building/facility to meet its performance expectations.
This research seeks to focus on the point where current BIM technology ends and seeks to build a knowledge ‐ based model that will consider the entire lifecycle for each individual system while considering the requirements of the other systems with which it must co ‐ exist.
My vision is to develop a comprehensive theory and model to assist with the integration of non ‐ concurrent product lifecycles for co ‐ existing systems, as applied to the active systems for buildings.
Ideally, my goal is to fundamentally change the design methodology to optimize the physical arrangement of building systems while considering the non ‐ concurrent lifecycles of the co ‐ existing systems.
The development of the model will assist with building systems coordination, while increasing the fundamental understanding of integrating non ‐ concurrent lifecycles for co ‐ existing systems.
In addition, we desire to advance the knowledge and understanding in the areas of project ‐ based learning, multi ‐ disciplinary projects, undergraduate research, and teamwork, as we will
elaborate upon below.
Effective building systems coordination requires recalling and integrating the lifecycle knowledge for each system ‐‐ design, construction, operations, and maintenance, etc.
‐‐ not only resolving physical interferences.
Missing from the use of BIM technology is the critical lifecycle knowledge regarding each individual building system.
A work process utilizing BIM still requires individuals to meet and share knowledge regarding their system.
Currently, using BIM
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technology only assists in resolving physical conflicts, through computational geometry.
As described above, resolving all physical interference during the building systems coordination process does not necessarily ensure that a facility has been well coordinated.
This concept expands current professional practice and suggests that there are multiple types of interferences beyond physical interferences, which affects the overall cost and schedule of a project.
During coordination, trades must consider all aspects from design, construction, and operations, and maintenance.
It is difficult to integrate this lifecycle knowledge into the building systems coordination process.
As described above, the AEC is inherently fragmented and often the stakeholders involved do not take the opportunity to align goals and define requirements.
In addition, design engineers have not been educated on lifecycle issues.
For example, designers must make assumptions about the constructability about a particular system or ignore the issue completely.
There is a lack of understanding between the design engineers who design the systems and the construction engineers who fabricate and install the systems.
Each engineering discipline focuses on its own design and construction requirements, failing to consider the how all the co ‐ existing systems will interact.
Many building systems construction engineers are unaware of unique installation requirements for the other building systems and lack a mechanism for learning more about the other building systems.
A knowledge based model that is able to integrate the life ‐ cycle knowledge (design, construction, operations, maintenance, etc.) regarding multiple systems would be able to provide valuable insight to design and construction engineers assisting them in performing coordination.
Based on the experience of the engineering and construction faculty and feedback from the
California Center for Construction Education (CCCE) industrial advisory board, a knowledge and skills gap exists between the engineering and construction curriculum, which creates a communication barrier between those who design and those who build.
The Construction Management (CM) department at California Polytechnic State University, San
Luis Obispo (CPSLO) recently approved an integrated design and construction curriculum, where students are engaged in the solution of realistic problems as they study a specific sector of the construction industry in a synergistic multi ‐ disciplinary, project ‐ based learning environment.
One required laboratory course in this new curriculum is the specialty contracting laboratory course, of which we were elected to be the course “champion” by the department because of my professional work experience and educational background in the
related field.
The course brings engineering and construction engineering students together to study the design, fabrication, installation, operations, and maintenance of active building systems in a project ‐ based learning environment, in which we plan to include building systems coordination laboratory exercises.
The impetus of the integrated curriculum proposal at CPSLO was the completion of the Construction Innovations Center (CIC) on the CPSLO campus.
During the early programming process for this building, faculty and industry representatives were encouraged to think about the future of the design and construction industry and knowledge that will be required by future professionals who enter into it.
Academic programs build new
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buildings perhaps every 50 years, so participants wrestled with the question, “What will the profession of construction be like in 2050?” Only then could they ask, “What is the best curricular model to prepare those professionals in 50 years?” Only then could the question be addressed, “What physical spaces are needed to support that curriculum model?” While the specifics of this industry cannot be discerned 50 years in advance, certain trends can be identified.
Design and construction professionals will need to be prepared for multiple changes in job assignments and perhaps companies during their careers, so specializing in just one area will not support that flexibility.
Collaboration will be the key to successful projects, so future engineers will need to master the ability to solve multiple problems at once that cut across boundaries of expertise and responsibility.
Working in a complex profession, design and construction engineers will need to realize that, for most of these problems, there will not be a single solution, but instead many possible approaches and strategies, some more applicable than others.
Unlike the product design process for mass manufacturing, the production of a prototype model is not feasible due to financial or scheduling constraints.
As discussions evolved, it became increasingly clear that a knowledge and skills gap exists between the engineering and construction professionals.
Engineers are educated on design fundamentals through theory and calculations often lacking practical applications.
Construction engineerins are educated on construction and fabrication methods lacing the design fundamentals necessary to comprehend the complex engineering decision and reasoning involved in the design process.
In professional practice, a design must translate into something that can be fabricated and installed, and historically education, for design and construction engineers has occurred in discipline specific silos.
More importantly, neither receives an education that considers the entire project or product lifecycle.
In a multi ‐ disciplinary integrated project ‐ based curriculum, both engineering and construction students will be educated on life ‐ cycle issues related to a particular system through project ‐ based laboratory exercises.
Furthermore, as the use of integrated project delivery methods, such as design ‐ build, continues to grow, the depth of lifecycle knowledge students will need, will continue to
increase as well.
My intent is all that students who will participate in the project ‐ based learning course will use the model developed as part of the research in this course and beyond.
This arrangement will allow students to experience true concurrent engineering through an integrated design, manufacturing, and testing experience.
By using the model developed with this research, students will learn how to communicate and overcome obstacles in a multidisciplinary team and they will gain valuable skills needed to transition to jobs in industry and to participate in more advanced projects.
The new integrated curriculum and project ‐ based learning component will provide students with an enriched learning experience and will address engineering and construction program assessment outcomes.
Research Questions
The research has been designed to answer the following research questions:
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1.
How can project lifecycle knowledge for co ‐ existing systems be structured in a knowledge based model to provide reasoning capabilities that will assist in the coordination process?
2.
How are engineering and construction students currently educated on the lifecycle issues that concern the projects and systems they design and build?
3.
How can the education for engineering and construction students be enhanced to include lifecycles regarding project and systems they design and build?
Research Objectives
The research has been designed with the following research objectives:
1.
Generate fundamental knowledge regarding the integration of non ‐ concurrent product lifecycles for co ‐ existing systems
2.
Develop a new comprehensive theory for integrating the non ‐ concurrent lifecycles for co ‐ existing systems for use in performing coordination.
3.
Standardize a methodology for integrating the non ‐ concurrent lifecycles for co ‐ existing systems for use in performing coordination, as applied to the active systems for buildings/facilities.
4.
Develop, test, and validate knowledge based model for integrating the non ‐ concurrent lifecycles for co ‐ existing systems
5.
Determine and develop an approach, including teaching modules, laboratory activities, etc.
that will better serve engineering and construction students to learn about product lifecycles using the knowledge collected during the observation of professionals.
6.
Outreach to K through 12 students and teachers in "science summer camp" and
Architecture Construction and Engineering (ACE) mentorship programs.
Research Methodology
The method of research involves participating in and collecting data regarding current coordination activities on complex buildings and industrial projects.
The data will then be analyzed and used to describe current coordination processes.
Furthermore, it will identify potential improvements through the use of information technology.
The primary method for representing and implementing reasoning to the knowledge for a knowledge based model will be symbolic modeling.
This approach has been used to formalize product and process models in engineering and has allowed researchers to solve engineering and construction ‐ engineering problems as discussed.
Knowledge acquisition
Knowledge acquisition begins with choosing and defining the tasks that the knowledge ‐ based system or expert system is to perform.
These tasks directly affect the type of knowledge acquired; therefore, knowledge acquisition becomes the transfer or transformation of potential problem ‐ solving knowledge from one source to another (Dym).
Therefore, acquiring knowledge becomes extremely important in building knowledge frameworks.
This research will use four major approaches to acquire knowledge regarding building systems coordination:
• review of written information sources
• personal interviews with experts in the field
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• observations of experts working in project meetings
Review of written information sources is often a very effective initial technique for acquiring knowledge.
Possible sources include trade journals, books, government publications, company procedure manuals, and current and historical project data.
These materials provide information in a very unobtrusive manner.
No expert time is required and knowledge engineers can accomplish most of the review independently by studying project documents
(Carrico).
The majority of construction knowledge originates from experience in previous projects and requires a feedback loop that crosses organizational boundaries.
Currently, there are no generally accepted methods to formalize construction knowledge (Luiten).
Therefore, researchers collect an abundant amount of written information (Carrico).
In this research project, data from current and completed construction projects will be the primary source of written information since very little published information is available about building systems coordination.
The personal interview is one of the most effective ways to gain expertise and to receive immediate feedback.
Communication with experts is essential.
It allows researchers to acquire a portion of the “domain vocabulary” experts develop to deal with specific types of problems in their field.
It is preferable to consult more than one expert for multiple perspectives on the problem (Carrico).
In this research, interviews will be conducted with engineering managers,
design engineers, project coordinators, detailers, and construction journeymen.
Observations of experts on the job and in project meetings are also excellent ways to gather information and to understand how participants exchange information.
One is able to observe design and construction engineers involved in building systems coordination naturally without feeling that they are being put on the spot.
This allows observation of how they deal with actual problems and how they handle surprises during problem ‐ solving sessions.
This process helps to define the problem and feeds further stages of knowledge acquisition (Carrico).
Knowledge representation
Once the knowledge acquisition is completed, knowledge will be encoded in a form usable by a knowledge ‐ based system (KBS).
Most knowledge engineers consider this step the most critical activity.
The goal is to create a structure that reflects the complexity and variety of all the components, yet remains simple enough to facilitate decision ‐ making and assist in problem solving.
Therefore, the trade ‐ off a knowledge engineer must is between trying to represent the knowledge completely and creating a robust reasoning structure (Hunter).
Object hierarchies and slot tables serve as the primary form of representation in this research.
The structure of the object hierarchy is important because its layout determines how the represented objects interact with each other in the symbolic model.
The attributes of the slot tables also require careful study because these slots determine what data about objects are stored.
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Good representation of knowledge should make things very explicit and expose natural constraints that are inherent to the problem being solved (Hunter).
Representing knowledge from large domains is difficult; the larger the domain, the more difficult it becomes to create a reasoning structure (Carrico).
A key limitation in knowledge representation is the inability to account for all possible global interactions in the representation structure (Hunter).
Other problems often arise when structuring knowledge into flowcharts to provide a basis for good decision ‐ making.
These include overlap of knowledge representation overlap and incorrectly classifying knowledge.
For this research, in order to the meet the objectives and avoid these problems, the knowledge structure will focus directly on those components most pertinent to building systems coordination.
In addition, specific attention will be applied to how the reasoning structure would use the knowledge framework.
Building reasoning structures
Reasoning structures found in KBS perform diagnostics.
The reasoning methods described below provide a general framework for the reasoning commonly found in these systems.
Reasoning typically uses the following methods: heuristics, model ‐ based reasoning (MBR), and case ‐ based reasoning (CBR).
A KBS can use heuristics, MBR, or CBR only, or it can combine two, or all three, of the reasoning methods (Kunz).
The intent of this research is to assist engineers during the design stage, which requires integrating design, construction, operations, and maintenance knowledge.
In this research, heuristics and MBR will be utilized to provide the necessary feedback for building systems coordination.
Heuristic reasoning
Heuristics provide a basis for reasoning mechanisms in classic expert systems.
A traditional KBS uses heuristics to express its knowledge.
The heuristic classification system works by abstracting measurable data and relating them to a predefined potential problem.
The system matches the problem with a solution, and then refines the solution.
Heuristics can represent many different kinds of knowledge.
They may express aspects of fundamental principles, experimental rules of thumb, and high ‐ level knowledge about how to use other kinds of
knowledge (Dym).
Figure 2 shows how a heuristic reasoning structure works.
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Problem class –
Identification of
Interference Type
2. Heuristic matching
Solution class –
Detailing, Layout, Positioning,
Application, Layout
3. Solution refinement 1. Data Abstraction
Raw data –
Components interfering
Specific solution –
Alter component attributes based on recommendation of solution class
Figure 2 ‐ Heuristic reasoning structure
In this research, the heuristic reasoning will be utilized because it is able to match the human process for resolving coordination conflicts.
It lends itself well to programming the building systems coordination tool to determine and resolve coordination problems.
First, the heuristic reasoning structure is able to abstract coordination information (raw data) from a geometric model.
Second, the reasoning structure can then classify the conflicts by classes by making heuristic matches.
Finally, the solution refinement mechanism can select a specific solution to resolve coordination conflicts.
Model ‐ based reasoning
Model ‐ based reasoning (MBR) involves creating a product model to form the basis for the reasoning mechanism.
In this research, the geometric representation inside the computer tool will serve as the model.
In order to use heuristic reasoning effectively, MBR is essential.
MBR provides the means to create a virtual representation of the building systems.
Groups of individual components from each building system collectively comprise the product model.
For reasoning purposes, each component consists of a description of the information needed to represent and reason about the component; experts often refer to this as component definition
(McKinney).
Heuristic reasoning uses MBR to abstract, test, and analyze data.
The advantage of MBR is the ability to abstract graphical, geometrical, topological, and behavioral characteristics from the components in the model for the reasoning processes.
In this research, MBR reasoning tracks
the effects of the geometrical and topological changes made during the resolution of coordination issues and conflicts found.
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Scheduling Data
(4th-Dimension)
Architectural System
Structural System
Electrical System
Mechanical System
3-D Model
Coordinated
BIM Model considering Time-
Space Relationships
Plumbing System
Architecture
Fire Protection System Time-Space
Logic and Reasoning
Structure
Figure 3 – Logic and Reasoning Structure Module for use with BIM software solutions
Case ‐ based reasoning
Case ‐ based reasoning (CBR) uses pre ‐ formulated solution sets for a specific problem as the basis for the reasoning mechanism.
In CBR, an expert creates a set of cases, each of which includes some descriptions of a situation and an associated statement of the problem’s cause and suggested correction method.
Reasoning essentially involves matching observed data with the data of each case.
The advantage of CBR is its ability to test a prototype solution through a series of libraries that contain alternative solutions.
This method can find an optimal solution.
The prototype solution can also be refined to meet the specific needs of the problem at hand
(Dym).
In this research, CBR is not used due to the number of diverse solutions possible for resolving coordination issues and conflicts.
Heuristics and MBR provide a more robust reasoning system because they rely more heavily on individual component attributes rather than solution sets as used with case based reasoning.
Methodology Example
Figure 3 depicts an example of how the methodology described above will be applied.
In this example, two components from co ‐ existing systems are found to interfere with each other ‐‐ a pressurized domestic water supply pipe and a gravity ‐ driven waste pipe.
The KBS may classify the interference by evaluating the attributes in question.
In this case, the two components
physically interfere; however, the slope attribute of the gravity line is also in question.
Therefore, the KBS may further classify the interference as a functional interference.
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Problem class –
(Identification of Interference Type)
Functional
Interference
1. Data Abstraction
Raw data –
Components interfering
Pressurized domestic water supply pipe
Solution class –
2. Heuristic match
- Horizontal Layout
- Vertical Positioning
- System Performance
- Etc.
Specific solution –
Move component based on recommendation of solution class
3. Solution refinement
Gravity driven waste pipe
Figure 4 – Methodology example
Using heuristics, the KBS may select a solution, which includes: horizontal layout, vertical positioning, system performance etc.
However, the solution must involve considering all aspects of the co ‐ existing systems’ lifecycles.
In this basic example, the design intent of both systems must be maintained.
The gravity ‐ driven waste line must convey waste away from a use point in a downward sloping pipe.
The pressurized domestic water supply pipe must convey water to a point of use.
Any changes from the original design must be evaluated from constructability (fabrication and installation) point of view considering time and cost to fabricate and install any reconfiguration of either system.
Coincidentally, any changes from the original design must be evaluated from an operational point of view – i.e.
considering the changes in the amount of energy used from any reconfiguration.
In addition, the proposed reconfigured solution must be evaluated from a maintenance point of view, considering how the reconfigured layout will affect the ability to maintain the system.
In this case, after a complete lifecycle evaluation and in order to maintain the design intent of the gravity ‐ driven waste pipe, the pressurized domestic water supply line must yield to a the gravity ‐ driven waste pipe.
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Detection of Time-Space Conflict
Gravity Sewer piping is scheduled to installed prior to domestic water supply piping, but Gravity Sewer piping is located at a higher elevation creating conflicts during installation
Pressurized domestic water supply pipe
Identify Solution Set
1. Reschedule conflicting components
2. Relocate conflicting components
3. Reconfigure conflicting components
Gravity driven waste pipe
Figure 5 – Example of Time ‐ Space Conflict
Project Work Plan
To perform the proposed research, the research objectives and activities are scheduled to occur over the five years allotted by the grant requirements:
•
Year 1 – Data Acquisition, Identification, Analysis, and Development of a Knowledge framework
•
Year 2 ‐ Prototype Tool Development, Testing, and Validation
• Year 3 – Development of Teaching Modules and Dissemination
A summary of the proposed research to be conducted, by year, is described below.
Year 1 – Data Acquisition, Identification, and Analysis
The research will begin be identifying the types of lifecycle knowledge that will be collected.
This will include the identification of relevant constructs regarding effective coordination practices and team processes that influence the coordination of multiple systems with non ‐ concurrent project lifecycles.
The step will include documenting and analyzing the practices of building systems coordination teams through videotaping and interviews.
In order to achieve
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and ensure that the correct type of data is being collected a preliminary step will be to identify attributes and indicators of good coordination efforts.
Additionally, during the first year we will focus data analysis and development of the knowledge framework to represent the knowledge collected during the first year.
The knowledge framework will be designed so that an analysis methodology can be applied in the knowledge ‐ based system.
Factors affecting the knowledge framework development include comparing the building systems coordination teams practices and results for project which meet the criteria of a well coordinated project to the practices and results of projects with others who did not meet the criteria of a well coordinated project using the methods described above.
Year 2 – Prototype Tool Development, Testing, and Validation
The focus of the third year will be on the development, testing, and validation of knowledge ‐ based model.
Activities will focus on 1) developing an empirically grounded theory to explain what work practices and team processes affect coordination and how 2) validate the theory by predicting the overall constructability of the systems based on observed coordination practices.
This phase of the research will include partnering and collaborating with industry to validate results and facilitate the transfer of new analysis methods to practitioners.
Year 3 – Development of Teaching Modules and Dissemination
The focus of the fourth year will be on the development of teaching modules and exercises.
The design approach for the teaching modules and exercises will incorporate two qualities that are critical for engineers in the 21st century: 1) utilizing a systems approach to design and 2) emphasizing ethical, environmental, health and safety, sustainability, social, political, and manufacturability issues.
In addition, we plan to incorporate six principles that have proven to be effective in achieving higher retention of underrepresented individuals in engineering and promoting deeper learning in the students: 1) providing meaningful context (i.e., a "real world" application); 2) integrating concepts from math, science and technology; 3) emphasizing active learning and design; 4) facilitating meaningful connections among students; 5) promoting reflection and self ‐ assessment of learning; and 6) creating significant interaction between students and faculty, with faculty acting as coaches.
We plan to identify and establish collaborations between disciplines and institutions, among the U.S.
academic institutions, industry and government and with international partners, which will help me to develop, adopt, adapt or disseminate effective models and pedagogic approaches to science, mathematics and engineering teaching.
During this stage we plan to develop research ‐ based educational materials or contribute to databases useful in teaching, specifically in the form of a “summer science” program aimed at students in the K through 8 levels and the through the ACE mentorship program for students in the 9 through 12 level.
Both of which will broaden participation of underrepresented groups.
The educational and outreach activities will increase the participation of industry and students in the study of building systems coordination.
Dissemination activities include: (1) Workshops and seminars for practitioners, apprenticeship programs, and community colleges.
The close
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collaboration with industry associations and centers will function both as a source of expertise and access to projects, and as channels for systematic dissemination of the effective practices.
(2) Integration of the research with graduate and undergraduate specialty contracting courses who focus on the active systems of a building.
Case studies and research ‐ based field assignments will increase the students' exposure to the actual work practices, and provide them with a framework for understanding and interpreting practice.
Field assignments will also be used for data collection during validation.
(3) Development of simulation games as learning modules.
These activities will increase awareness of product and system lifecycles and will be design to attract underrepresented students to engineering disciplines as they see how design engineering and construction professionals work together.
(4) Make campus visits and presentations at institutions that serve underrepresented groups.
(5) Participate in developing new approaches (e.g., use of information technology and connectivity) to engage underserved individuals, groups, and communities in science and engineering.
(6) Participate in conferences, workshops and field activities where diversity is a priority.
Lastly, we plan to disseminate the knowledge to the broader community, specifically by designing a prototype museum exhibit, which would be appropriate for a science and industry museum, to educate the general public on the importance of lifecycles of the active systems of buildings.
We intend to demonstrate, through the exhibit, how the systems provide comfort and safety to our buildings/facilities and how the consideration of their lifecycles affects energy use.
Significance and Impact of the Research
This work has significant scientific and intellectual merit as the research proposes to generate fundamental knowledge regarding the integration of non ‐ concurrent product lifecycles for co ‐ existing systems, and standardize a methodology for performing building systems coordination, which can then be applied to other fields.
The proposed project is part of the principal investigator's research program to increase fundamental understanding of processes of construction innovation and to provide mechanisms and strategies for technological advancement in construction.
Intellectual Merit
This research will generate fundamental knowledge regarding the integration of non ‐ concurrent product lifecycles for co ‐ existing systems.
It will develop a new comprehensive theory for conducting building systems coordination for building systems, grounded on several fields of knowledge and validated with empirical studies.
This theory will integrate the concepts of product lifecycles considering constructability and coordination and open the way for new directions the design and construction of co ‐ existing building systems.
The research will also develop a new methodology for performing building systems coordination.
The new theory and methodology will be of value to other researchers.
Finally, the findings will provide a basis for future modeling and simulation.
Broader Impacts
Most researchers in the engineering and construction fields envision computer aided design system to become more than what they are used for today, which is essentially an electronic drafting tool with little ‐ to ‐ no knowledge base.
BIM technology has allowed use to expand to
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project planning and control systems, but still has a limited knowledge base that must be input by the user.
This research seeks to integrate lifecycle knowledge into models.
Capturing and formalizing the knowledge related to the integration of systems whose lifecycles are non ‐ concurrent will enable systematic development of a future design methodologies and work processes.
This will have a significant impact on how the universities educate and train future engineers.
Educational and Outreach Activities
The proposed work will advance the understanding of how to design learning experiences for greater retention of engineering and construction students.
Students are motivated by the experience of mastery.
The educational component of this research will be focused on designing an educational experience not only to enable students to experience varying degrees of mastery, but also to allow them to experience the joy of being able to assist individuals in need.
Providing these experiences is particularly important for both engineering and construction students.
These experiences are also critical during the first two years, since that is when students are most likely to drop out of engineering because they lack to see how their
designs will translate into something tangible.
The proposed work will advance the understanding of how to design learning experiences to equip engineers for the complex constructability and coordination issues that they will face as the products they design transfer into tangible products.
The Accreditation Board of
Engineering and Technology (ABET) requires programs to demonstrate that students are able to formulate engineering solutions within the design constraints of ethical, environmental, health and safety, sustainability, social, political, and manufacturability issues in design.
The American
Council for Construction Education (ACCE) requires programs to demonstrate responsiveness to social, economic, and technical developments and reflects the application of evolving knowledge in construction and in the behavioral and quantitative sciences.
However, no clear methodology has emerged to integrate these considerations into the engineering and construction curriculums.
Designing for constructability and coordination requires an understanding of these issues.
This work will demonstrate the effectiveness in developing the
intellectual attributes required of the 21st century design and construction engineers.
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Appendix – Field Notes
Appendix – Field Notes