Building Design & Maintenance System Visualised Through Time
1. Travelling Through Time
in aid of Sustainability:
Building Design &
Maintenance System
Professor Farzad Khosrowshahi
27 October 2010
2. • Maintenance on failure
• Preventative planned maintenance
• Time-based maintenance
Building Maintenance
Generations
3. • Too soon: uneconomical
• Too late: Poor service
Promise
. Building Maintenance Scheduling
. IDEAL (2) - Alternative Design Solutions
• Life cycle evaluation
• sustainability
Ideal (1): - Just-in-time maintenance
- live through it twice - virtual
4. Visualisation of Building.
2D, 3D, animation, VR
4D Visualisation.
In time
Visualisation through time.
Visualisation of the degradation of an object like a building:
application in maintenance
Building Visualisation Generations
5. Traditionally
Architect
Produce
building outline
design
Client briefing:
Define functional and strategic
needs
Building
Component
Selection for
lifecycle,
sustainability,
energy.
Define Project
Environment
(climate, usage,
locality)
Long Term &
Periodical
maintenance
scheduling
Construction
Phase
Use to design for lifecycle and generate repair & maintenance program
Lifecycle engine
(knowledge-based
OR visual-based)
Proposed
6. Visual Building
Design
Information
Maintenance
Scheduler
Items Gen Properties
Building Design
Components AnalysisProperties of
Items in Building
Design
Maintenance
Scheduler Analysis
Visual User Interface
Eg. VRML Browser
Cad output
(convert to XML)
contains all building
details
’Items’ attributes
and properties.
Maintenance time period
and type of maintenance..
Default properties of
each standard ‘item’.
Produce a map of building ‘items’
and assign the suitable properties
to each one based on project initials.
Calculate building maintenance
procedure for the given time and
for the given scheduler.
Add building visual data
and calculated data for the given
time and maintenance scheduler
and produce output VUI
8. Development Process
Event-Effect relationship model
Events: list, agents
Component: list, elements, time related variables
Event / Component interaction
Auxiliary events
Maintenance scheduling expert system
Data generation: collect, generate, knowledge conceptualisation, mobilisation
Data Validation: case based , multi-modal
Event-effect modelling / database design
Product Development (software); interface design, web-based
Visualisation; VUI
Automate the maintenance decisions
10. Generalised life span modelGeneralised life span modelGeneralised life span modelGeneralised life span modelGeneralised life span modelGeneralised life span modelGeneralised life span modelGeneralised life span model
Time
Dead
Components
T1T2
A β PDF represent the lifetime
If pi(tj)<=RND(tj) then “Item i is broken at the tj”
12. Generalised status algorithm.Generalised status algorithm.Generalised status algorithm.Generalised status algorithm.Generalised status algorithm.Generalised status algorithm.Generalised status algorithm.Generalised status algorithm.
Color of Component I at the time T
Red =Initial_Red_Colour*PDF_FNr(I,T)
*MaintenanceFactor;
Green=Initial_Green_Colour*PDF_FNg(I,T)
* MaintenanceFactor;
Blue =Initial_Blue_Colour*PDF_FNb(I,T)
* MaintenanceFactor;
End of Colour calculation.
13. Example life span algorithm forExample life span algorithm forExample life span algorithm forExample life span algorithm forExample life span algorithm forExample life span algorithm forExample life span algorithm forExample life span algorithm for
general light source.general light source.general light source.general light source.general light source.general light source.general light source.general light source.
Lumens of lamp I at the time T
Red_Lumens = Initial_Red_Lumen *
PDF_FNr(I,T) * Dust_Factor;
Green_Lumen= Initial_Green_Lumen *
PDF_FNg(I,T) * Dust_Factor;
Blue_Lumen = Initial_Blue_Lumen *
PDF_FNb(I,T) * Dust_Factor;
The_Lamp_Lit_Colour = RGB(Red_Lumens,
Green_Lumens, Blue_Lumens);
End of Lumens calculation.
Death status of lamp I at the time T
Probability_of_Death = PDF_FNd(I,T) *
Environment function based on
Maintenance factor (I);
if Probability_of_Death >= RND(I,T) then
Bulb is in broken state;
Else
Bulb is not in Broken State;
End of lamp death status.
14.
15. Example of a bedroom before lightExample of a bedroom before lightExample of a bedroom before lightExample of a bedroom before lightExample of a bedroom before lightExample of a bedroom before lightExample of a bedroom before lightExample of a bedroom before light
manipulation.manipulation.manipulation.manipulation.manipulation.manipulation.manipulation.manipulation.
16. Example of a bedroom afterExample of a bedroom afterExample of a bedroom afterExample of a bedroom afterExample of a bedroom afterExample of a bedroom afterExample of a bedroom afterExample of a bedroom after
supervised light manipulation.supervised light manipulation.supervised light manipulation.supervised light manipulation.supervised light manipulation.supervised light manipulation.supervised light manipulation.supervised light manipulation.
17.
18. Changes due to
lamps’ death.
General reduction
in lumens due to
dust factor and
lamp’s age.
25. Combined effect of two or more Events
Example: Event-rain plus Event- vandalism-x = Active link to
Component-Cladding-Element-Steel
popu
tionrain cladding
plastic
steel
cladding
ComponentsEvents Auxiliary Events
Rain/vandel
26. Extended model of Events-Effects
water
rain
steel
cladding
Agents
Events
Corrosion
Effects
Elements
Components
auxiliary
auxiliary
29. BEHAVIOURAL PATTERNS
eg. Degradation of Flooring Systems
[Visualisation of Impact of time on internal flooring]
1- Pattern of usage
2- Visualisation of degradation
30. There are two methods for analysing human spatial behaviour:
- Activity system (Chapin, S., 1968); is primarily
concerned with the organisation of the sequence of
activities taking place in a setting.
- Behaviour Settings (Barker, R., 1968); concerned
with the relationship between the setting and a
recurring pattern of behaviour. [anthropology]
Centre
Keep distance
32. 5 0 5 10
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0.2
0.4
0.60.415847
8.64717e-010
g( )x
8-5 x
dy
y
yxf
xg
j
iy
∫=
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),(
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33.
34. The presentation of probability of appearance of
n creatures in a long room (Corridor)
with one entry (Door).
The presentation of appearance of
n creatures in a long room (Corridor)
with two entries (Doors).
40. Clients
s
t
a
n
d
a
r
d
s
Input Data
Output Knowledge
(tailored)
Wider
Dissemination
Wider Exploitation
-Popularize ~music
FINAL PRODUCT: ‘universal’ Web-based Design & Maintenance knowledge Broker
Designers
Maintenance manager
Financiers/Insurers
Public authorities
Community
Pressure Groups
Web – HOLMES
Knowledge Broker
Manufacturers
Researchers
HOLMES
Phase1 : Initial population
Phase 2: Promotion&Publicity
Phase 3: Data volunteers
General Public
Etc.