Presentation Lube Oil Blending Plant Performance Evaluation

Vikram Razdan ([email protected])

Lube Blending plantsGlobal market study and Performance evaluation

Feb 2016

Vikram RazdanBusiness Consultant

Plax Ltd, UK


Objectives

• Present an overview of the global lubricants industry

• Lube blending, product formulations and growth markets

• Propose a methodology for developing a Lube Blending plant Performance Index, based on Plant Index and Operating efficiency

• MonteCarlo simulation for sensitivity analysis of Performance Index


Global lubricants market overview

China (6 million tonnes) and India (1.7 million tonnes) are the fastest growing markets.

Global lubricants growth @0.6-0.7% for next 10 years as per Total, France (2015)

Lubricants market dominated by International Oil companies (IOCs) and National Oil companies (NOCs), with Shell as the market leader.

World’s largest Independent lube blender: Fuchs

World’s largest blending plant commissioned by Total in Singapore in 2015 (310,000 metric tonnes per annum) with a workforce of 100

Global,35 mil-

lion tonnes

China 6 million tonnes India,

1.7 million tonnes

2012


Top 20 countries in 2012 by lubricants consumption

Global consumption: 35 million tonnes


Global lubricants demand snapshot

Fastest growing market is Asia Pacific (mainly China and India)North America and Western Europe are mature markets


Finished lubricants segment wise (2012)

Automotive oils segment dominated by major oil companies (IOCs and NOCs)

Industrial oils and MWF/CP/Greases dominated by independent manufacturers

Automotive oils Engine oils, gear oils, transmission fluids (ATF), brake fluids, coolants/anti freeze

Industrial oils Hydraulic fluids, turbine oils, industrial gear oils, spindle oils, open gear compounds, rolling oils, etc.

Process oils For manufacturing of textiles, optical-cables, tyres, polymers, cosmetics, fertilizers, explosives and crop sprays.

MWF/CP/Greases Metalworking fluids, Corrosion preventives and Greases


Key players in the global lubricants market

Manufacturers130 major oil companies (IOCs and NOCs)590 independent manufacturers

Volume mix Top 10 manufacturers ~ 50% Rest 710 manufacturers ~50%

Top 15 (2012)

1. Shell2. ExxonMobil3. BP4. Chevron5. Total6. PetroChina7. Sinopec8. Idemitsu9. Fuchs 10. Lukoil (1.3 MMTPA)11. JX Nippon Oil12. Petronas13. Petramina14. Gulf/Houghton15. Valvoline (Ashland)

(source: Fuchs)

• IOCs and NOCs have market domination• Rest of the market highly fragmented• IOCs benefitting the most in shift from mineral (SN)

to semi-synthetic/ synthetic base oils (PAO/Esters)• Independents play a pivotal role in the industrial

lubricants market• More focus on high gross margins speciality

lubricants (automotive and industrial), especially in mature markets

Strategic drivers


Lube manufacturing/blending

ABB: Automatic Batch BlenderSMB: Simultaneous Metering BlenderILB: Inline BlenderDDU: Drum Decanting Unit

Plant complexity depends upon

type and number of formulations /

grades


Lubricants formulations are technically complex

Engine OilsBase oil Group I, II (Low S), III (Low S, High VI), IV (Synthetic) : 80 to 90%

Additives (10 to 20%)ZDDP or TCP• Anti-wear• Corrosion inhibitor• Anti-oxidantPolymethacrylate or Olefin Copolymer• VII (Viscosity Index Improver)

Other additives• Friction Modifiers• Dispersants• Detergents• Pour point depressants• Anti-foam agents

GreaseBase oil Group I (90-95%) or IV (Synthetic) : 75 to 90%

Thickeners (5 to 20%) • Lithium• Lithium complex• Aluminium complex• Clay

Additives (0 to 10%)ZDP• Extreme Pressure• Anti-wearMolydisulphide or Graphite• Solid lubricants

Other additives• Oxidation inhibitors• Friction Modifiers• Tackifiers• Corrosion and Rust preventives• Metal deactivators

Gear OilsBase oil Group I or IV (Synthetic) : 85 to 90%

Additives (5 to 15%)Sulphur-Phosphorus• Extreme Pressure• Anti-wear• Corrosion inhibitor

Other additives• Friction Modifiers• Dispersants• Pour point depressants• Anti-foam agents• Metal deactivators

Mono-grade (SAE 10, 20 ,30, 40, 50)Multi-grade (SAE 5W30, 10W30, 20W40, 20W50)API SJ, SL, SM, SN (Petrol)API CF-H, CG-J, CF-I (Diesel)

NLGI grade (6 softest to 000 hardest)

API GL 4 (moderate duty, low speed)GL 5 ( heavy duty, high speed)Mono-grade (SAE 80, 90)Multi-grade (SAE 80W90, 75W90, 85W140)


Lube blending plants – some figures

Fuchs: 33 blending plants worldwide. Largest independent manufacturer in the world. Gross margin: 37%, Net profit margin: 11.4% (2012)

77 Lubricants, Holland: Largest independent blender in Europe (130,000 MTPA)

Other key independent blenders: Motul, Pentosin, Liqui Moly, Unil-Opal, Carlube, Royal Purple, Amsoil, Red Line, Torco, Exol (largest in UK)

•50 blending plants worldwide•8 blending and 3

grease plants in China with largest in Tainjin (280,000 MTPA)• Indonesia (120,000

MTPA)• India (55,000 MTPA)

•30 blending plants worldwide•Operates the 2nd

largest plant in the world. •2 blending plants in

China.• India (70,000 MTPA)

•20+ blending plants worldwide.•2 blending plants in

China (Taicang and Shenzen)•5 blending plants in

India (BP/Castrol)

Shell

ExxonMobilBP

Top

3In

depe

nden

ts


Lube blending in China and India – Growth markets

India

Industrial lubricants have 54% market share

IOCL is the largest blender (6 plants in India 505,000 MTPA)

Chennai: 140,000 MTPA Mumbai: 135,000 MTPAKolkata: 90,000 MTPASilvassa: 30,000 MTPATaloja: 20,000 MTPAAsaoti: 60,000 MTPA

7th blending plant in Sri Lanka (18,000 MTPA)

Other local key players: BPCL. 3 blending plants, 4 filling plantsHPCL. 7 blending plantsTideWater: 5 blending plants

1.7 million tonnes (2012)

China

Industrial lubricants have 46% market share.

PetroChina is the largest blender. 10 blending plants. Total capacity: 1700,000 MTPA

Sinopec is the second largest blender. 11 blending plants. Total capacity: 1146,000 MTPA

Other local key players:• CNOOC.• Feoso Group. 5 blending

plants. Total capacity: 227,000 MTPA• Longcheng Shiye. 3 blending

plants (150,000 MTPA)

6 million tonnes (2012)


Lube blending plant – Benchmarking possibilities

Performance Compare vis-à-vis the best practices of the leading Lube blending plant

Strategic Critical success factors (compare with other industries like FMCG and Paints)

Operational Evaluate running cost, staffing and productivity

Process Process mapping and technology

Product Product design/packaging (compare with market leader / paints industry for best practices)

Financial Financial ratios and return on investment

Performance level = Strategic positioning x Operational effectiveness


Proposed methodology for creating Lube blending plant Performance Index

Plant Index Based on Strategic parameters• Plant location• Capital Investment• Blending complexity• Feedstock availability• R&D capability• Power and Utilities• Quality and Environmental compliance

Operating efficiency Based on Operational parameters• Quality• Cost• Time

Performance Index (Plant Index) x (Operating Efficiency)

Net Performance Index (Performance Index) x (Capacity Utilisation)


Lube blending plant – Strategic parameters

Parameter Weightage (%) Yardstick Level Multiplier(0.5 to 1.0)

Plant location (low freight cost, market proximity, duties and taxes, labour costs) 30 Labour costs

> $10ph 0.5< $10ph 1

Capital investment • Plant size/Economies of scale (high production capacity, low cost per tonne) • Blending/Filling systems for product quality and quantity (high accuracy, low variance) • Storage and Warehousing

25Plant capacity in tonnes per annum

> 200,000 1100,000 to 200,000 0.75

< 100,000

0.5

Blending complexity (formulations/batch size/changeovers/cycle-time) 15 Level of

automation

Fully automated 1Semi-automated 0.75No automation 0.5

Feedstock availability

15

Base oil manufacturing

Manufacturer 1Non-Manufacturer 0.5

R&D capability

5

Product formulations

> 250 1100 to 250 0.75< 100 0.5

Power and Utilities

5

Captive or Procure

Captive generation 1Procure 0.5

Quality and Environmental compliance (ISO standards)

5

Level of compliance

ISO9000 0.5ISO14000 0.5Scores to be allocated for each parameter to generate a Plant index


Plant Index example

Two hypothetical Lubricants blending plants Plant A

• In an OECD developed country• 100,000 MTPA• Fully automated• Base oil manufacturer• 200 product formulations• Procure power• ISO9001/TS16949 and 14001

compliant

Plant B• In a developing country• 150,000 MTPA• Semi automated• Base oil manufacturer• 300 product formulations• Captive power generation• ISO9001 /TS16949 compliant

Plant location 0.5 x 30 = 15.00 1.0 x 30 = 30.00

Capital investment 0.75 x 25 = 18.75 0.75 x 25 = 18.75

Blending complexity 1.0 x 15 = 15.00 0.75 x 15 = 11.25

Feedstock availability 1.0 x 15 = 15.00 1.0 x 15 = 15.00

R&D capability 0.75 x 5 = 3.75 1.0 x 5 = 5.00

Power and Utilities 0.5 x 5 = 2.50 1.0 x 5 = 5.00

Quality and Environmental Standards

0.5 x 5 + 0.5 x 5 = 5.00 0.5 x 5 = 2.50

Plant Index (max 100) 75 87.5

(Detailed worksheet in Annex 1)


Lube blending plant – Operational parameters

Cost

Quality

Time

Impact on plant performance

Valu

e

Tendency is to focus on costs only

60%

25%

15%


Operational parameters in detail

Parameter Fixed Variable

Quality Additives Base oilBlending process• Level of automation• Batch sizeProduct downgradesProduct testing

Cost MaintenanceProduct testingStaff/Labour

Base oilAdditivesInventoryContainersPackagingProduct lossEnergy consumption

Time Cycle time• Blending• FillingProduct testing

Customer ordering to deliveryProcurement lead time


Operational metricsParameter Operational metrics Measurement

unitGross weightage

(%) Standalone Weightage (%)

Quality

Base oil quality (VI, stability, fluidity, evaporation) % variation

25

10Additive dosing accuracy % variation 2.5Bulk product downgraded % of total 5Number of filled product containers downgraded % of total 5Product tests done per year number 2.5

Cost

Base oil cost per tonne

60

20Additive cost per tonne 5Raw material inventory cost per tonne 5Work in process inventory cost per tonne 10Maintenance cost per tonne 5R&D cost per tonne 2.5Product loss per tonne 2.5Employee cost per tonne 10

Time

Blending cycle time for ABB per tonne

15

2.5Blending cycle time for SMB/ILB per tonne 2.5Decanting cycle time for DDU per tonne 1.25Filling cycle time for cans per tonne 2.5Filling cycle time for drums per tonne 1.25Procurement lead time per tonne 2.5Customer ordering to delivery time per tonne 2.5

Total 100

Scores to be allocated for each metric with reference to best-in-class blending plant to generate Operating efficiency (%)

Vikram Razdan ([email protected]))

Operating Efficiency example

Two hypothetical Lube blending plants Plant A

• High quality base oil• Low process variation• Low product downgrades• Medium base oil cost• High maintenance cost• High R&D cost• High employee cost• Optimum cycle time• Median procurement lead

time

Plant B• Medium quality base oil• Some process variation• Medium product downgrades• Optimum base oil cost• Low maintenance cost• Medium R&D cost• Low employee cost• Median cycle time• High procurement lead time

Quality 10 x 1.0 = 102.5 x 1.0 = 2.55 x 1.0 = 55 x 1.0 = 52.5 x 1.0 = 2.5

10 x 0.75 = 7.52.5 x 0.9 = 2.255 x 0.8 = 45 x 0.9 = 4.52.5 x 1.0 = 2.5

Cost

Time

Operating Efficiency (max 100%) 83.5 85.31

20.38

44 53.8814.5 11.06

Setting the benchmark best-in-class as reference

would be the main issue in generating blending plant

operating efficiency.

25



Performance Index example

Two hypothetical Lube blending plants

PlantPlant Index

Operating Efficiency (%)

Performance Index

Capacity Utilisation (%)

Net Performance Index

a d c = a x b d c x d

A 75 83.5 62.63 95 59.49

B 87.5 85.31 74.64 85 63.45

Key observations

Plant A, based in an OECD developed country, achieves a good Net Performance Index as compared to Plant B (located in a developing country), in spite of higher operating costs

Plant Index should have minimal variation, and thus scope for improvement lies mainly in increasing Operating Efficiency and Capacity Utilisation


Performance Index sensitivity (MonteCarlo simulation)

Two hypothetical Lube blending plants

PlantPlant Index

Operating Efficiency (%)

Performance Index

Capacity Utilisation

(%)

Net Performance

Index

a d c = a x b d c x d

MinimumA 74.54 82.86 61.76 95 58.67

B 87.12 84.63 73.73 85 62.67

AverageA 74.95 83.50 62.58 95 59.45

B 87.57 85.31 74.71 85 63.50

MaximumA 75.41 84.20 63.49 95 60.32

B 87.91 85.98 75.58 85 64.25

Standard deviation (SD) of 5% has been assumed for all scores in the example. However, SD should depend on historical data which should give more realistic results



End of presentation


Annex 1

PLANT INDEX SCORE

ParameterWeightage

(%) Yardstick Level Multiplier Plant A Plant BPlant location (low freight cost, market proximity, duties and taxes, labour costs) 30 Labour costs >$10ph 0.5 0.5 15 1 30

<$10ph 1

Capital investment • Plant size/Economies of scale (high production capacity, low cost per tonne) • Blending/Filling systems for product quality and quantity (high accuracy, low variance) • Storage and Warehousing

25Plant capacity tonnes per annum

>200000 1

0.75 18.75 0.75 18.75100000 to 200000 0.75

<100000 0.5

Blending complexity (formulations/batch size/changeovers/cycle-time) 15 Level of automation

Fully automated 11 15 0.75 11.25Semi-automated 0.75

Manual 0.5

Feedstock availability 15 Base oil manufacturing

Base oil producer 11 15 1 15Non-base oil

producer 0.5

R&D capability 5 Product formulations

>250 10.75 3.75 1 5100 to 250 0.75

<100 0.5

Power and Utilities 5 Captive or Procure

Captive generation 1 0.5 2.5 1 5Procure 0.5

Quality, Safety and Environmental compliance (ISO standards) 5 Level of compliance

ISO9000 0.5 0.5 2.5 0.5 2.5ISO14000 0.5 0.5 2.5

75 87.5


Annex 2

OPERATING EFFICIENCY SCORE

Parameter Performance metricMeasurement

unit

Gross weightage

(%)

Standalone Weightage

(%) Plant A Plant B

Quality

Base oil quality (VI, stability, fluidity, evaporation) % variation

25

10 1 10

25

0.75 7.5

20.38Additive dosing accuracy % variation 2.5 1 2.5 0.75 1.875Bulk product downgraded % of total 5 1 5 0.8 4Number of filled product containers downgraded % of total 5 1 5 0.9 4.5Product tests done per year number 2.5 1 2.5 1 2.5

Cost

Base oil cost per tonne

60

20 0.75 15

44

1 20

53.88

Additive cost per tonne 5 0.9 4.5 0.9 4.5Raw material inventory cost per tonne 5 0.9 4.5 0.7 3.5Work in process inventory cost per tonne 10 0.9 9 0.7 7Maintenance cost per tonne 5 0.5 2.5 1 5R&D cost per tonne 2.5 0.5 1.25 0.75 1.875Product loss per tonne 2.5 0.9 2.25 0.8 2Employee cost per tonne 10 0.5 5 1 10

Time

Blending cycle time for ABB per tonne

15

2.5 1 2.5

14.5

0.75 1.88

11.06

Blending cycle time for SMB/ILB per tonne 2.5 1 2.5 0.75 1.88Decanting cycle time time for DDU per tonne 1.25 1 1.25 0.75 0.94Filling cycle time for cans per tonne 2.5 1 2.5 0.9 2.25Filling cycle time for drums per tonne 1.25 1 1.25 0.9 1.13Procurement lead time per tonne 2.5 0.8 2 0.5 1.25Customer ordering to delivery time per tonne 2.5 1 2.5 0.7 1.75

83.5 85.31


Annex 3

NET PERFORMANCE INDEX

PlantPlant Index Operating Efficiency

(%) Performance Index Capacity Utilisation (%)

Net Performance Index

a d c = a x b d c x dA 75 83.5 62.63 95 59.49B 87.5 85.3125 74.65 85 63.45

MonteCarlo simulation (minimum, 5% standard deviation)A 74.54 82.86 61.76 95 58.67B 87.12 84.63 73.73 85 62.67

MonteCarlo simulation (average, 5% standard deviation)A 74.95 83.50 62.58 95 59.45B 87.57 85.31 74.71 85 63.50

MonteCarlo simulation (maximum, 5% standard deviation)A 75.41 84.20 63.49 95 60.32B 87.91 85.98 75.58 85 64.25

Presentation Lube Oil Blending Plant Performance Evaluation

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Transcript of Presentation Lube Oil Blending Plant Performance Evaluation