DECISION SUPPORT SYSTEM

FOR INFRASTRUCTURE MAINTENANCE USING COMBINED GRAPH THEORY AND HOUSE OF QUALITY

1

Dr. Moustafa Kassab

Infrastructure Asset /Challenges

Decision Making: Maintenance/ Rehabilitation/ Replacement

Graph Theory

House of Quality Deployment Function

Proposed Decision Support System for Infrastructure Maintenance

Case Study

Conclusion and Future work

2

Agenda

3

Objective

- Develop flexible MCDM Based DSS for by utilizing the graph theory

and House of Quality for infrastructure related decisions in

maintenance projects that meet customer’ requirements.

- Validate the decision support tools by applying to case studies in

infrastructure contracts (i.e. Transportation/ water systems )

Ageing infrastructure

Importance to Economy and social Developments

Increasing population

Budget Cuts: for Health / Education Priorities

Sustainability

Government Investment and relaxing Regulations

Infrastructure Asset /Challenges

Build New facilities

Maintain & Expand Existing

Rehabilitate Old facilities

5

House of Quality (HoQ)

It Is a set of matrices which contains

the maintenance requirements "

what's" and the detailed information to

achieve these requirements (How's)

Stakeholders groups (based on project

goal, previous data-base, and

experiences) fill in the matrices based

on their project goal and its priorities

A key to the HoQ is making sure each

group answer the same question about

the same relationship (What vs. How)

Projects Delay and Failure

Projects delay & Failure: HoQ Advantages

MCDM Process for Infrastructure Projects

Identify the Problem

Identify the Alternatives

Evaluate the decision

Establish Evaluation Criteria

Evaluate Alternatives

Make a decision

Sensitivity Analysis

User

(Municipality)

Interface

- Past Experience

- Survey

Technical Req’d

Criteria

VOC

Customers Req’d

- On-line survey

- Expert

- Graph Theory

a)

b)

c)

OptimumDecision

Proposed DSS Framework

DSS

Components

Characteristics of

Infrastructure'|

Maintenance Project

House of Quality

Proposed DSS Framework

Point Scores

Pre-Qualification Score for “What”s

Pre-qualification Score for “How”s

Pre-qualification Score for each contractor

Pre-qualification Index for Each contractor

Mathematical background

Proposed DSS Framework

- Infrastructure Maintenance Project ( Transportation / Water network)

- The Municipally want to call contractors for bidding

- Municipality revised the contractors list and considered short list of 6 contractors with close bidding price

- In selecting the suitable contractor : the owner ( municipality listed its requirements (what's) as follow:

Delivery on Time and schedule

Deliver with planned expenditures

Follow Code and technical specifications

Accountability and warrantees

Honesty and professional Management

Adopting safety and sustainability

- In addition, the Municipality review the contactors ability based on the following attributes (How's):

WE= Work Experience

M = Management

FS= Financial stability

R = Reputation

Q = Quality

TE = Technology and equipment

CI = Creativity and innovation

S = Sustainability

- The Municipality (Decision makers) will rank the contractors and make its awarding decision accordingly

Example Case Study

Proposed DSS Framework Case Study

ص

ص

ص

ص

ص

ص

WE

ص

ص

ص

ص

ص

ص

M

ص

ص

ص

ص

ص

ص

FS

ص

ص

ص

ص

ص

ص

R

ص

ص

ص

ص

ص

ص

Q

ص

ص

ص

ص

ص

ص

TE

ص

ص

ص

ص

ص

ص

CI

ص

ص

ص

ص

ص

ص

S

Step:1

Using the convenience of Graph theory and its nodes (Hows) and interrelations ( arrows)

among the required atributes

Proposed DSS Framework

For each contractor and based on the characteristics of the project , owner (DM) assigns weight of

importance for each “How” and weight of importance for each “What “

Case StudyStep: 2 Data Matrix

status of each “What”

Proposed DSS Framework

Owner ( Municipality) assign weighting scores for interrelation between the

various criteria (How) of the in the hose of quality ( Roof -matrix)

Case StudyStep:3 Roof Matrix

Work

Experience

(WE)

Management

(M)

Creavity

Innovation

(CI)

– 0.665 0.665

0.59 0.745 0.745

0.335 – 0.5

0.5 0.665 0.665

0.5 0.745 0.745

0.335 0.5

0.335 0.5 0.5

0.335 0.5

Relative Important of Attributes

Reputation

(R)

M

Attributes

Technology &

Equipments

(TE)

Sustainability

(S)

Financial

stability

(FS)

Quality

(Q)

R 0.225 0.335 0.225 0.5

0.225 0.335 0.255 0.5 0.5

0.665

TE – 0.59 0.5 0.745 0.745

WE 0.41 0.5 0.5 0.665

0.5

S 0.41 – 0.41 0.665 0.665

0.255 0.335 0.255 0.5

–

–

0.745

Q 0.225 0.335 0.255 – 0.5

FS 0.5 0.59 – 0.745

–

CR

Relative importance of attributes scale

Class descriptionRelative

Importance

One attribute is exceptionally

less important over the

other

0.045

One attribute is extremely less

important over the other

0.135

One attribute is very less

important over the other

0.255

One attribute is less important

over the other

0.335

One attribute is slightly less

important over the other

0.410

Two attributes are equally

important over the other

0.500

One attribute is slightly more

important over the other

0.590

One attribute is more important

over the other

0.665

One attribute is very more

important over the other

0.745

One attribute is extremely more

important over the other

0.865

One attribute is exceptionally

more important over the other

0.955

Proposed DSS Framework

For each contractor and based on the

characteristics of the project , owner

assign weight of importance for each

“How” and weight of importance for

each “what “

Case StudyStep:4

weight of important for each How

Strength of interrelation between

each “what” and “How”

Proposed DSS Framework

For each contractor: calculate PSWi and then Max_PSW

Step: 5 Process Matrix

Case Study

PSW of each requirement (what) with respect to the contactor ability (How) = 20x0.45x0.6x1=5.4

status of each How

PS

Pre

qu

ali

fic

ati

on

sc

ore

fo

r s

pe

cif

ic H

ow

Prequalification score for specific How

Proposed DSS Framework

For each contractor Pre-qualification Index : calculate CPI = PSWi / Max_PSW

Contractor # 1: 1008.8/ 176.8 = 57 %

Step: 6 Ranking contractors and Making Decision

Case Study

First

Last

Ageing infrastructure/ Increasing population

Infrastructure maintenance projects: Municipalities challenges

Complicated maintenance projects => Need for effective DSS

DSS : Combined Graph theory and House of Quality is an effective system

Reduce changes in Design, planning and procedure

Good for communication decision making and planning

Allow for a lot of information in small time and space

Future work Integrating AI : Computerized Neural-networks, and Expert system

Conclusion and Future work

Thank You