The process of building a simulation model is one of the toughest and time-consuming part of the entire process.
An alternative method and a new approach for creating construction simulation models are provided in the in the presentation above which was presented at the Winter Simulation Conference 2013 in Washington D.C.
Verification of thevenin's theorem for BEEE Lab (1).pptx
A discrete Event Simulation Model of Asphalt Paving Operations, Ramzi Labban et al.
1. A DISCRETE EVENT SIMULATION MODEL
OF ASPHALT PAVING OPERATIONS
RAMZI LABBAN
PHD CANDIDATE
UNIVERSITY OF ALBERTA
DR. SIMAAN M. ABOURIZK
PROFESSOR
UNIVERSITY OF ALBERTA
MR. ZUHAIR HADDAD
CHIEF INFORMATION OFFICER
CCC
DR. AMR EL-SERSY
GROUP MANAGER LEARNING
& INNOVATION
CCC
2. AGENDA
• Introduction
• Asphalt Paving Simulation Model
• Alternative Method
• Potential Benefits
• Future Work
• Acknowledgements
• Q & A
3. INTRODUCTION
• The process of building a simulation model includes
four distinct phases:
– product abstraction phase
– process abstraction and modeling phase
– experimentation phase
– decision making phase
• Modeling is the most difficult and the most time-
consuming part of simulation
4. INTRODUCTION
• When building a new model, simulation practitioners
find themselves going through the full four-phase
process in its entirety
• This rigorous and time consuming cycle is typically
repeated for every new construction simulation
model to be built
• The effort and technical expertise needed to build a
simulation model and then run experiments
compared with the uniqueness and relatively short
life cycle of a construction project contribute to the
slow adoption of simulation by the industry
5. INTRODUCTION
• When faced with a problem, end users have to make a choice:
– If time permits and required resources are available: Simulation
– Otherwise: traditional tools (even though they understand these tools are
less adequate than simulation)
• For end users to adopt the simulation path, simulation has to be
more accessible
– Require less time to build a model and arrive at answers
– Should not require simulation practitioners every time a question needs to
be answered
– Allow end users to focus on solving their business problem and not on
modeling
• Today we will briefly go over a DES model built for asphalt paving
and then describe the first steps being taken to develop a
framework to make simulation more accessible to end users
6. Asphalt Paving Simulation Model
Background
• Asphalting operations
–a main constituent of road construction
projects
–involve numerous interactions between the
many participants in the process (i.e. paving
equipment, trucks, loaders, rollers, asphalt
plants, material sources, etc…)
7. • Many factors affect the operations and
the interactions between the different
resources:
–number and asphalt laying rate of the
asphalt paving machines
–asphalt plant production rate
–number of trucks
Asphalt Paving Simulation Model
Background
8. Asphalt Paving Simulation Model
Simulator Design and Development
• Abstraction of the real world situation into a
simulation model representing asphalt paving
operations:
– Product definitions
• Sub-base
• Base course
• Wearing course
– Process definitions
• Activities and their flow
• Resources
9. • The three product layers were defined including all
required parameters
Asphalt Paving Simulation Model
Product Definitions
Subbase Course (x layers each with m thickness)
Base Course (y layers each with n thickness)
Wearing Course (z layers each with p thickness)
10. Asphalt Paving Simulation Model
Resources
• Equipment selection & availability through user
interface
• Team (crew) building for each of the layers
12. Alternative Method
• Model was very successful on large road
project
• However, the development process of the
model was quite rigorous and required a great
deal of effort and time
• On a typical project there is not usually
enough time available to develop such a
model to answer important ad-hoc questions
as they arise
13. Alternative Method
• An alternative is to have a generic simulation environment
allowing the user, for specific construction simulation
situations, and instead of building a simulation model from
scratch using a simulation modeling environment, to
– populate specific modular data structures with process
information, product information and environment
information
– process the data using an algorithm which will compile the
provided product, process, and environmental information
into a DES model on the fly
– run the DES model and produce results
14. • The process definition structure component would carry
– definitions of activities to be simulated including all their
relevant properties
– resource definitions and timelines
• The product definition structure component would carry
– definitions of the objects to be constructed including all their
relevant properties
– the object hierarchy to enable level of detail shifting during
simulation execution when needed
• The environment definition component would carry the
definitions of environment aspects affecting productivity
(i.e. calendar, season, shifts, etc.)
Alternative Method
15. Activities Template - Type 1
Task 1 Task 2 Task N...
...
Task Replication and Processing Engine Component
Taski(f(PPEi))
Resource(s)
The process definition structure component:
the definitions of the activities to be simulated
including all their relevant properties
the inter-activity relationships
resource definitions and timelines
The product definition structure component:
the definitions of the objects to be constructed
including all their relevant properties
the object hierarchy to enable level of detail
shifting during simulation execution when needed
The environment definition component:
the definitions of environment aspects affecting
productivity (i.e. calendar, season, etc.)
SuitableDatabaseEnvironment
Suitable Discrete Event Simulation Environment
Algorithmto
manage“process”-
“product”feed
Activities Template - Type M
Task 1 Task 2 Task N...
Alternative Method
16. Potential Benefits
• The proposed methodology describes a new
approach for creating construction simulation
models with potential benefits to target user
groups, including:
– Enabling target users to build special purpose
simulation models quickly and with little
simulation model development skills
– May allow integration with other construction
management systems by allowing simulation flows
to be dynamically constructed from data
17. Future Work
• The proposed alternative methodology is still a very
theoretical approach, in its early stages, and which needs to
be developed, implemented and evaluated.
• Immediate future work will include:
– Examining diverse construction simulation model building
efforts to gather more information and data
– Further development of the conceptual model
– Further classification of the appropriate target user
group(s)
– Developing the modular input data structure components
– Identifying the appropriate simulation environment in
which to apply it
– Verification and validation using real world test cases
18. Acknowledgements
• The asphalting model described in this paper was developed
and implemented at Consolidated Contractors Group (CCC) to
aid in estimating, planning and managing asphalting
operations on major road construction projects.
• I would like to thank:
– Dr. Simon Abourizk – University of Alberta
– Mr. Zuhair Haddad and Dr. Amr Elsersy - CCC
extended visits to multiple mega industrial projects were conducted to observe and document pipe spool fabrication activitiesBenchmarking for every activity was conducted via numerous observations of the activity being performed on different spools of varying characteristics. Both crew composition information and productivity figures were collected. In this paper we will not deal with the analysis of the observed productivity data; this matter will be dealt with at a different time. Instead, for this paper, we will assume the resulting productivity norms deduced from the observations as our activity productivity norms for the tasks. The simulator was developed as a discrete event simulation model with spools as the main entity. For the welding tasks, welds are the entities - where spools are split into their constituent welds - in order to process welds individually and collect their artificial history.
Spool data required: spool ID, current spool status, line class, material type, paint code, surface area, spool specific priority information Joint data required: weld type, inch-dia, post weld heat treatment (PWHT) requirement and non-destructive testing (NDT) requirements
These are just the main flows without the constraints.