Trade-Off Economics for Plant Turnarounds

TINC 2007 – “The Continuum of TA Excellence”1

2008

TURNAROUND INDUSTRY NETWORK CONFERENCEAn Owners Only Forum for Industry Best Practices

TINC 2008

June 16-19, 2008

Trade-Off Economics in Plant and Refinery TurnaroundsJan A. Jackson

Senior Consultant – AP-Networks


2008

In case you did not know…

“Smoking is one of the leading causes for

…..statistics.”


2008

BackgroundPurpose of Presentation

1. Describe various types of economic trade-off scenarios in the turnaround environment

2. Present some on-going high-level turnaround data research and emerging trends.

3. Provide a conceptual framework for your turnaround decision-making and trade-off considerations


2008

BackgroundProposed Methodology

Constraints Trade-Offs Optimization Opportunity Costs

I. ESSENTIAL CONCEPTS

TA Duration TA Size (hrs, $) Labor Productivity Work Intensity

II. DATA PRESENTATION

Shift Pattern Refining Margin

III. CASE STUDY

Conclusion

IV. SUMMARY


2008

BackgroundIncreasing volatility in refinery margins

0

50

100

150

200

250

300

350

JAN-86 JUN-95 APR-08

Cen

ts/G

allo

n o

f G

aso

line

JAN-02

Price of Gasoline1 (left axis)

Crude Oil2

Refinery Margins3

1 Spot Price EIA New York Harbor Conventional Gasoline Regular FOB, 2Cushing OK WTI Spot, 3NWE Brent Cracking

ECONOMY


2008

BackgroundUS Refiners approach 1980’s capacity with ½ the plants

70

120

170

220

270

320

50.0

55.0

60.0

65.0

70.0

75.0

80.0

85.0

90.0

95.0

100.0

1949 20061980

Nu

mb

er o

f R

efin

erie

sUtilization3

Input

Capacity2

INDUSTRY

1 Information provided by www.eia.doe.gov, 2 Capacity and Input are displayed w/o axis. 3 Right axis is for Utilization

ARAB-ISRAELI WAR 1973

IRAN / IRAQ WAR

IRANIAN REVOLUTION

PERSIAN GULF WAR 1991

SUEZ CRISIS

http://www.eia.doe.gov/


2008

-

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

2.00

2.20

2.40

2.60

2.80

3.00

3.20

3.40

3.60

3.80

BackgroundRefinery portion of Gasoline Prices in ‘07 varied greatly

2007

Cost of Crude

Refinery

Misc. Taxes~$0.34

US

$/g

allo

n f

or

gas

olin

e p

rod

uct

ion

REFINERY

~$1.26

1 Information provided by www.eia.doe.gov, FRS

Crude Oil

Gasoline



2008

BackgroundThe Refinery Cost Structure1 is dominated by crude

REFINERY

Re

fin

ed P

rod

uc

t C

ost

s

2.9%

4.5%

91.0%

1.6%Refinery Net Income

Other Refining Expenses

9.0%

36.0%

55.0%

Other2

Product Purchases

Processed Raw Material

100.0%

1 Information provided by www.eia.doe.gov



2008

BackgroundContext – Summary

Increasing volatility in refinery margins U.S. has reached almost same capacity in 2007 with

149 refineries as in 1980 with 320 Major extraneous constraints are present on all levels:

Economy: Oil Prices set by World Market and events

Industry: Increasing regulatory requirements (safety, environmental, fuels, etc.)

Refinery: Limited options for capacity expansion, resource attrition

Turnaround: Contracting and labor, skill level

Turnarounds are being executed in an increasingly difficult context


2008

I. Essential ConceptsWhat are “Constraints”? What are “Trade-Offs”?

The “Triple Constraint1“ of (Turnaround) Management Constraints exist due to (inter-) dependencies Constraints are an artifact of scarcity They force us to consider trade-offs

performance

cost

time


2008

I. Essential ConceptsConstraints in the “real” world are not just ‘triple’ but manifold

scope

cost

schedule

reliability

company objectives

refinery objectives

personnel skills

personnel availability


2008

I. Essential ConceptsOptimization of the ‘Cost Curve’

cost (crash)

cost (opt.1)

t(crash) t(opt.1)time

cost

t(normal)

• Decreased labor productivity• More complex field management• Higher number of safety incidents• Expediting charges• Inefficiencies in coordination

• Increased general conditions

• Indirects• Rental Equipment

TRADETRADE

MINIMUMTIME 1

2

3

Cost Curve


2008

I. Essential ConceptsOpportunity Costs and the ‘Cost Curve’

cost (crash)

cost (opt.1)

t(crash) t(opt.1)time

cost

t(normal)

Opportunity Costs

t(opt.2)

cost (opt.2)1

2

4MINIMUMTIME

3

Cost Curve

Cost Curve-revised-


2008


“There are three kinds of lies:

lies, damn lies, and statistics.”- Benjamin Disraeli -


2008

II. Data PresentationLabor Performance1 deteriorates with increasing TA size

0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,0000.70

0.90

1.10

1.30

1.50

1.70

TOTAL TA HOURSLA

BO

R P

ER

FO

RM

AN

CE

IN

DE

X

1.0

(+)100,000 hrs = (+)0.10

1 Labor Performance Index (LPI) is calculated by dividing Actual Hours Incurred and Planned Hours


2008

0 5,000 10,000 15,000 20,000 25,000 0.75

0.85

0.95

1.05

1.15

1.25

1.35

1.45

1.55

LA

BO

R P

ER

FO

RM

AN

CE

IN

DE

X

~270 personnel / shift


1.0

II. Data PresentationHigher Work Intensity1 adversely impacts Labor Performance2

HRS WORKED / DAY (Work Intensity)

2 See previous slide

1 Work Intensity is defined as ‘Hours Worked per Day’


2008

II. Data PresentationHigher Work Intensity increases potential for Safety Incidents1

0 2,000 4,000 6,000 8,000 10,000 12,000 14,0000

5

10

15

20

25

30

35

40

45

50

WORK INTENSITY (HOURS WORKED / DAY)

SA

FE

TY

IN

CID

EN

TS


1 Safety Incidents here are defined as the sum of (a.) First Aids and (b.) OSHA Recordable Incidents


2008

0 200,000 400,000 600,000 800,000 1,000,000 1,200,0000.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

ACTUAL TOTAL TA HOURS

PO

RT

ION

OF

INC

L. S

UP

PO

RT

HO

UR

SIndirect manhour portion increases by 1% per each additional 20,000 hours in size for turnarounds up to 400,000 hours in size. 30% in support hours appears to be the upper limit.

27.5%

II. Data PresentationLarger TAs have increasing portion of ‘support hours’


2008

II. Data PresentationTurnaround Durations by Shift Pattern

0.80

1.00

1.20

1.40

1.60

1.80

2.00

6-10s 7-10s

SHIFT TYPE

LA

BO

R P

ER

FO

RM

AN

CE

7-12s

MEANMEAN

7-10s and 7-12s show wide range of outcomes and strong potential for labor hour overruns of 40-60%. 6-10s are very predictable with few ‘catastrophic’ outcomes.


2008

$0

$10,000,000

$20,000,000

$30,000,000

$40,000,000

$50,000,000

$60,000,000

$70,000,000

$80,000,000

$90,000,000

$100,000,000

$50.00

$60.00

$70.00

$80.00

$90.00

$100.00

$110.00

$120.00

$130.00

$140.00

$150.00 1. Total TA Costs and Labor Hours strongly correlated2. Up to 300,000 hrs data have very tight fit to trend-line3. “All-In Rate” level is elevated between 300-500,000 hrs

II. Data PresentationTurnaround Costs by Man-hours (left axis) and All-In Rate

TA SIZE IN MANHOURS

1

All-In Rate2

3

TO

TAL

TU

RN

AR

OU

ND

CO

ST

S


2008

II. Data PresentationMan-hours and Turnaround Duration

0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 900,000 1,000,00010

20

30

40

50

60

70

0

2,500

5,000

7,500

10,000

12,500

15,000

17,500

20,000 TA

DU

RA

TIO

N I

N C

Ds

TA SIZE IN MANHOURS

HRS/CD

1

2

3


2008


"The bigger the real-life problems, the greater the tendency for consultants to retreat into a

reassuring fantasy-land of abstract theory and technical manipulation.“ (revised)

- Tom Naylor -


2008

III. Case StudyCreating the Base Case

28211470 35 42 49 56

Baseline Shift: 5-8sEstimated Dur.: 49 CDsNo. avail. Men: 1,428Scope Hours: 400,000

DIRECT

DIRECT LABOR

INDIRECT LABOR

23.0%

68.0%

09.0%

INDIRECT

MATERIAL

EQUIPMENT

GENERAL COND.

$

hrs10% - 30%

70% - 90%


2008

0.400

0.500

0.600

0.700

0.800

0.900

1.000

1.100

CALENDAR DAYS

EX

PE

CT

ED

DA

ILY

PR

OD

UC

TIV

ITY

RA

TE

6-12s

6-10s6-10s

5-10s

Baseline Case 5-8s 1.0

P1 P2 P3 P4

0 7 21 28 80

7-10s

7-12s

III. Case StudyProductivity Profiles1

1 In


2008

III. Case StudyMajor Observations

Total Scope is base-lined as 400,000 Earned Hours on 49 CDs (5-8s). Each shift pattern meets final scope target on a different day due to

productivity differentials.


2008

III. Case StudyCreating the Base Case

DIRECT LABOR5-8s

$80.0MM

$40.0MM

$20.0MM

$60.0MM

MATERIAL

PER DIEM

IND. LABOR

EQUIP. / GC

DIRECT LABOR6-10s

IND. LABOR

MATERIAL

PER DIEM

EQUIP. / GC

PREMIUM 15%

+ $10MM

49 Days 39 Days 37 Days 33 Days- 10 Days - 2 Days - 4 Days

DIRECT LABOR7-10s

IND. LABOR

MATERIAL

PER DIEM

EQUIP. / GC

PREMIUM 23%

+ $7MM

DIRECT LABOR7-12s

IND. LABOR

MATERIAL

PER DIEM

EQUIP. / GC

PREMIUM 32%

+ $7MM

DIRECT LABOR7-14s

IND. LABOR

MATERIAL

PER DIEM

EQUIP. / GC

PREMIUM 32%

+ $6MM

30 Days- 3 Days


2008

III. Case StudyTurnaround Durations by Shift Pattern

BASE (5-8s)

A- (7-14s)

B-(6-10s)

C-(6-10s)

D-(6-12s)

E-(7-10s)

F-(7-12s)

20 25 30 35 40 45 50

CALCULATED TA DURATION

PR

OD

UC

TIV

ITY

ST

UD

Y A

ND

SH

IFT

PA

TT

ER

N4 CDs

2

19 CDs

10 CDs

33 CDs

37 CDs

39 CDs

30 CDs

49 CDs


2008

III. Case StudyTrade-Offs (e.g. capacity 200,000 bbl/d)

20 25 35 45 50 554030

$50.0MM

$60.0MM

$70.0MM

$80.0MM

$40.0MM

$6.00 margin bbl

$12.00 margin bbl

$2.00 margin bbl

7-12s 7-10s 6-10s 5-8s

+ $10MM

+ $7MM

+ $7MM

33 37 39 49

$4.00 margin bbl

30

7-14s

+ $6MM

1

2


2008

III. Case StudyCompression v. Acceleration

28211470 35 42 49 56

2

3

1

4

FEASIBLE RANGE

Compression increases degree of concurrency (t(conc.)/total duration) => increasing demand on coordination/supervision skills


2008

IV. Summary

Larger TAs tend to have worse Labor Performance Index (LPI). The complexity of these events is not fully valued.

LPI development changes significantly at ~270 and ~500 personnel/shift

Portion of support hours increases by 1% for every 20,000 hrs up to 400,000 hrs, and then log to lim. 28%

All-In Rate is highest for TAs between 300-500,000 hrs. Higher work intensity accelerates safety incidents. Larger TAs have higher work intensity Impact of 7-day shift schedules on LPI often

underestimated


2008

IV. SummaryThe Need For Post-Turnaround Reviews of Data

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 3721-JUL 27-AUG

STEAM LEAK STRIKE

LESS IMPACTED PERIOD IMPACTED PERIOD LEARNING

ERROR ?

ADDED CO HRS

7,200 HRS LOSS

Cumulative Productivity

Incremental Productivity

Documents

Trade-Off Economics for Plant Turnarounds