Presented By

Dr. Mohsen Alardhi

College of Technological Studies , Kuwait

April 19th,2009

Presentation Agenda

•Research Objectives

•Research Motivation

•Plant Description

•Preventive Maintenance Scheduling Definition

•Preventive Maintenance Scheduling Model

•Simulation Model Results

•Conclusions

2

• To develop, test and validate an integrated decision-making model, for maintenance scheduling in cogeneration plants in order to effectively enhance maintenance scheduling in cogeneration plants using a mathematical model and simulation model

• The proposed models and tools should achieve the following:

Provide Overall system performance

Provide alternative maintenance schedules

Test different maintenance scheduling policies

Provide decision making with a tool for maintenance scheduling

Research Objectives

3

0

100

200

300

400

500

600

700

800

900

1000

CA

PA

CIT

Y M

IGD

SAUDIARAB

KUWAIT UAE USA LIBYA IRAN BAHRAIN QATAR ITALY USSR

DESALINATION CAPACITY FOR TOP 10 COUNTRIES IN ORDER OF CAPACITIES

Research Motivation

4

Plant Description

5

Zurn and Quintana define the maintenance scheduling (MS) problem as:

"one in which the maintenance outages of each unit have to be scheduled in some optimal way while satisfying a number of constraints, over a planning interval of m periods."

PM - Scheduling definition

6

1- Maintenance Constraints:

Crew constraints

Resource constraints

Allowable maintenance window

Priority or sequence constraints

Maintenance duration bounds

Maintenance completion periods

2- System Constraints:

Unit capacity constraints

Supply/demand constraints

System Modeling- Constraints

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Preventive maintenance scheduling of cogeneration unit using integer programming method

Decision Variables

1 if the equipment in the unit in plant during period in operational status

0 otherwise rijk

j i r kx

1 if the equipment in the unit in plant is not in maintenance during period

0 otherwise rijk

j i r ky

represent the plant number. 1, 2,3,.......,

represent the unit number. 1, 2,3,.........,

represent the equipment type. 1,...., 3

represents the number of planning horiz

r r R

i i m

j j n n

k

on period . 1, 2,3,....k L

System Modeling- Decision Variables

8

Maintenance Window

1 if or

0 if rijk rij

rijkrij rij

k E k By

E k B

earliest time equipment in the unit in plant can be taken for maintenace

latest time equipment in the unit in plant can be taken for maintenance

rij

rij

E j i r

B j i r

System Modeling- Maintenance Window

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Maintenance Completion

0 if equipment in the unit in plant starts its maintenance on period

1 otherwise rijk

j i r ks

1

1

1 for 1

1 for rij

k

rijq rij rij rijq

rijk k

rij ijq rij rij rijq k D

k s E k E D

y

D s E D k B

1

1

rij rijB D

rijk rij rijk

s B D

1

rijB

rijk rij rijk

s B E

System Modeling- Maintenance Completion

10

Logical Constraints

1

1,....,

m

rijki

x m u

j n

2 1 ; 1, 2,3,....., , 1, 2,3,...., ri k ri kx y r R i m

2 1 ; 1, 2,3,....., , 1, 2,3,....., ri k ri ky y r R i n

System Modeling- Logical Constraints

11

Resource Constraints

1

(1 ) m

rjk rjkp rjkpi

y M MA

1,2,3,...........,

1, 2,3,..........,

1, 2,3,..........,

1, 2, ,..........., , 3

r R

k L

p p

j n n

System Modeling- Resource Constraints

12

Maintenance Crew

1

(1 ) m

rijk rjk rjki

y C CA

1,2,3,.........,

1, 2,3,.........,

1, 2,3,..........,

r R

k L

j n

System Modeling- Maintenance Crew

13

Efficiency Constraints

1

0 ritk r rijk

rijkritk r rijk

pw MW ff

pw MW DMW f

2ritk ridk ritkx x f

System Modeling- Efficiency Constraints

14

Demand Constraints

ritk ritk ritkpw A x

ridk ridk ridkw B x

1

m

ritk ki

pw DV

11

1 min1

1 max1

m

k ridk k ki

m

k ridk ki

m

k ridk ki

w w DW w

w w DW w

w w DW w

System Modeling- Demand Constraints

15

mR

r 1 i 1 1 1

Max. rijk

n L

j k

x

Objective Function

System Modeling- Objective Function

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0200400600800

10001200140016001800200022002400

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52

WEEKS

MW

generator capacity on maintenance Available MW Electricity Demand

Unit system output summary (weekly loads of electricity and gross reserves for 14 units)

System Modeling- Output

17

0102030405060708090

100110120130140150

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52

WEEKS

MW

distiller capacity on maintenace Available MGID Water Demand

Unit system output summary (weekly loads of water and gross reserves for 14 units)

System Modeling- Output

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Start

Formulate a hypothesis

Develop a simulation

model

Run simulation experiment

Hypothesis correct

End

Yes

No

SIMULATION Model- FLOW CHART

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Determine number of unitsAssign unite to Preventive maintenance scheduling

Determine units to be available

Generate demand for water and electricity

Assign demand to plants

Assign to units

Performance measure

SIMULATION Model- FLOW CHART

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SIMULATION Model- FLOW CHART

21

SIMULATION Model- RESULTS

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SIMULATION Model- RESULTS

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SIMULATION Model- RESULTS

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Averaged simulation model output under random demand and equipment breakdown for weekly demand and production of

electricity and gross reserve for 4 units input data from the linear integer programming model

SIMULATION Model- RESULTS

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Averaged simulation model output under random demand and equipment breakdown for weekly demand and production of water and gross reserve for 4 units input data from the linear

integer programming model

SIMULATION Model- RESULTS

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Averaged simulation model output for state of each equipment for linear integer

programming model

SIMULATION Model- RESULTS

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•A single objective integer programming model has been developed which aims to maximize the availability of units

•Discrete event simulation model has been developed

•Link between the integer programming and simulation model illustrate

Conclusions

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Any Questions

Thanks

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