Presentation Lube Oil Blending Plant Performance Evaluation

Lube Blending plants
Global market study and Performance evaluation
Feb 2016
Vikram Razdan (vrazdan@plaxgroup.co.uk)
Vikram Razdan
Business 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 million
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
Manufacturers
130 major oil companies (IOCs and NOCs)
590 independent manufacturers
Volume mix
Top 10 manufacturers ~ 50%
Rest 710 manufacturers ~50%
Top 15 (2012)
1. Shell
2. ExxonMobil
3. BP
4. Chevron
5. Total
6. PetroChina
7. Sinopec
8. Idemitsu
9. Fuchs
10. Lukoil (1.3 MMTPA)
11. JX Nippon Oil
12. Petronas
13. Petramina
14. Gulf/Houghton
15. 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 Blender
SMB: Simultaneous Metering Blender
ILB: Inline Blender
DDU: Drum Decanting Unit
Plant complexity
depends upon
type and number
of formulations /
grades

Lubricants formulations are technically complex
Engine Oils
Base 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-oxidant
Polymethacrylate or Olefin
Copolymer
• VII (Viscosity Index Improver)
Other additives
• Friction Modifiers
• Dispersants
• Detergents
• Pour point depressants
• Anti-foam agents
Grease
Base oil Group I (90-95%) or IV
(Synthetic) : 75 to 90%
Thickeners (5 to 20%)
• Lithium
• Lithium complex
• Aluminium complex
• Clay
ZDP
• Extreme Pressure
• Anti-wear
Molydisulphide or Graphite
• Solid lubricants
Other additives
• Oxidation inhibitors
• Tackifiers
• Corrosion and Rust preventives
• Metal deactivators
Gear Oils
Base oil Group I or IV
(Synthetic) : 85 to 90%
Sulphur-Phosphorus
• Extreme Pressure
• Anti-wear
• Corrosion inhibitor
Other additives
• 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
ExxonMobil
BP
Top3Independents

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 MTPA
Kolkata: 90,000 MTPA
Silvassa: 30,000 MTPA
Taloja: 20,000 MTPA
Asaoti: 60,000 MTPA
7th blending plant in Sri Lanka
(18,000 MTPA)
Other local key players:
BPCL. 3 blending plants, 4 filling
plants
HPCL. 7 blending plants
TideWater: 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
25
Plant capacity
in tonnes per
annum
> 200,000
1
100,000 to 200,000 0.75
< 100,000
0.5
Blending complexity (formulations/batch
size/changeovers/cycle-time)
15
Level of
automation
Fully automated 1
Semi-automated 0.75
No automation 0.5
Feedstock availability 15 Base oil
manufacturing
Manufacturer 1
Non-Manufacturer 0.5
R&D capability 5
Product
formulations
> 250 1
100 to 250 0.75
< 100 0.5
Power and Utilities 5 Captive or
Procure
Captive generation 1
Procure 0.5
Quality and Environmental compliance (ISO
standards)
5 Level of
compliance
ISO9000 0.5
ISO14000 0.5
Scores 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
Value
Tendency is to focus
on costs only
60%
25%
15%

Operational parameters in detail
Parameter Fixed Variable
Quality Additives Base oil
Blending process
• Level of automation
• Batch size
Product downgrades
Product testing
Cost Maintenance
Product testing
Staff/Labour
Base oil
Additives
Inventory
Containers
Packaging
Product loss
Energy consumption
Time Cycle time
• Blending
• Filling
Product testing
Customer ordering to
delivery
Procurement lead time

Operational metrics
Parameter Operational metrics
Measurement
unit
Gross weightage
(%)
Standalone Weightage
(%)
Quality
Base oil quality (VI, stability, fluidity, evaporation) % variation
25
10
Additive dosing accuracy % variation 2.5
Bulk product downgraded % of total 5
Number of filled product containers downgraded % of total 5
Product tests done per year number 2.5
Cost
Base oil cost per tonne
60
20
Additive cost per tonne 5
Raw material inventory cost per tonne 5
Work in process inventory cost per tonne 10
Maintenance cost per tonne 5
R&D cost per tonne 2.5
Product loss per tonne 2.5
Employee cost per tonne 10
Time
Blending cycle time for ABB per tonne
15
2.5
Blending cycle time for SMB/ILB per tonne 2.5
Decanting cycle time for DDU per tonne 1.25
Filling cycle time for cans per tonne 2.5
Filling cycle time for drums per tonne 1.25
Procurement lead time per tonne 2.5
Customer 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 (vrazdan@plaxgroup.co.uk))
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 = 10
2.5 x 1.0 = 2.5
5 x 1.0 = 5
5 x 1.0 = 5
2.5 x 1.0 = 2.5
10 x 0.75 = 7.5
2.5 x 0.9 = 2.25
5 x 0.8 = 4
5 x 0.9 = 4.5
2.5 x 1.0 = 2.5
Cost
Time
Operating Efficiency (max 100%) 83.5 85.31
20.38
44 53.88
14.5 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
Plant
Plant
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)
Plant
Plant
Index
Operating
Efficiency (%)
Performance
Index
Capacity
Utilisation
(%)
Net
Performance
Index
Minimum
A 74.54 82.86 61.76 95 58.67
B 87.12 84.63 73.73 85 62.67
Average
A 74.95 83.50 62.58 95 59.45
B 87.57 85.31 74.71 85 63.50
Maximum
A 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
Parameter
Weightage
(%) Yardstick Level Multiplier Plant A Plant B
Plant 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
25
Plant capacity
tonnes per
annum
>200000 1
0.75 18.75 0.75 18.75
100000 to 200000 0.75
<100000 0.5
Blending complexity (formulations/batch size/changeovers/cycle-time) 15
Level of
automation
Fully automated 1
1 15 0.75 11.25Semi-automated 0.75
Manual 0.5
Feedstock availability
15
Base oil
manufacturing
Base oil producer 1
1 15 1 15Non-base oil
producer 0.5
R&D capability 5
Product
formulations
>250 1
0.75 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 5
Procure 0.5
Quality, Safety and Environmental compliance (ISO standards)
5
Level of
compliance
ISO9000 0.5 0.5 2.5 0.5 2.5
ISO14000 0.5 0.5 2.5
75 87.5

Annex 2
OPERATING EFFICIENCY SCORE
Parameter Performance metric
Measurement
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
20.38
Additive dosing accuracy % variation 2.5 1 2.5 0.75 1.875
Bulk product downgraded % of total 5 1 5 0.8 4
Number of filled product containers
downgraded % of total 5 1 5 0.9 4.5
Product 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 4.5
Raw material inventory cost per tonne 5 0.9 4.5 0.7 3.5
Work in process inventory cost per tonne 10 0.9 9 0.7 7
Maintenance cost per tonne 5 0.5 2.5 1 5
R&D cost per tonne 2.5 0.5 1.25 0.75 1.875
Product loss per tonne 2.5 0.9 2.25 0.8 2
Employee 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 1.88
Decanting cycle time time for DDU per tonne 1.25 1 1.25 0.75 0.94
Filling cycle time for cans per tonne 2.5 1 2.5 0.9 2.25
Filling cycle time for drums per tonne 1.25 1 1.25 0.9 1.13
Procurement lead time per tonne 2.5 0.8 2 0.5 1.25
Customer ordering to delivery time per tonne 2.5 1 2.5 0.7 1.75
83.5 85.31

Annex 3
NET PERFORMANCE INDEX
Plant
Plant Index
Operating Efficiency
(%)
Performance Index
Capacity Utilisation
(%)
Net Performance
Index
A 75 83.5 62.63 95 59.49
B 87.5 85.3125 74.65 85 63.45
MonteCarlo simulation (minimum, 5% standard deviation)
A 74.54 82.86 61.76 95 58.67
B 87.12 84.63 73.73 85 62.67
MonteCarlo simulation (average, 5% standard deviation)
A 74.95 83.50 62.58 95 59.45
B 87.57 85.31 74.71 85 63.50
MonteCarlo simulation (maximum, 5% standard deviation)
A 75.41 84.20 63.49 95 60.32
B 87.91 85.98 75.58 85 64.25

Presentation Lube Oil Blending Plant Performance Evaluation

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