140414 Process Control IEEE Eml r

QUALITY CONTROL AND ITS IMPACT ON PLANT PROCESS CONTROL By Anis HAIDER President of ITECA

PROCESS CONTROL IN A CEMENT PLANT

1

PROCESS CONTROL

 It should never be underestimated that the cement manufacturing process, is essentially a mineral transformation process, that needs to be monitored by directly controlling the product at each transformation stage

PROCESS CONTROL

TRADITIONALLY THE SAMPLES ARE COLLECTED MANUALLY AND BROUGHT BACK TO THE PLANT LABORATORY TO BE ANALYSED MANUALLY FROM ONCE AN HOUR TO ONCE A SHIFT THE RESULTS ARE THE GIVEN TO THE PLANT OPERATORS, SO THAT THEY CAN ADJUST THE PRODUCTION PROCESS

2

PROCESS CONTROL WHAT ARE THE DRAWBACKS OF THE TRADITIONAL METHOD : • LOW FREQUENCY • LARGE LAG TIME • HUMAN ERRORS

PROCESS CONTROL

CENTRALIZED AUTOMATIC LABORATORIES

3

Centralised Automatic Laboratory

Automatic Laboratory Raw meal 1

Raw meal 2

Kiln Feed

Clinker

Hot Meal

Cement 1

Cement 2

Field network Transport  fan

Free Lime Analyser

Carbon Sulphur Analyser To plant system  (LIMS, PLC, etc.)

Gas  Dust  (XRF/XRD) extraction  Technical room system

Instructions to  raw mill weight  feeders

PSD  Workstation

Mill &  Press Central  control  cabinet

Vision  Software PSD Analyser

XRF/XRD  Workstation Raw Mix  Control  Software

Composite  samples XRF

XRD

Laboratory network

Bridge  Workstation

Movable control  console

4

On line Process Control Precalciner Additives

Quarry

Raw Mill

Preblending

Clinker Silo

Crusher

Kiln

Chemical Composition

RAW MIX

Cement Mill

Cooler

Loss on Ignition

Gas Sampling & Analysis

Free Lime

Mineral Structure

Carbon Sulphur

Particle Size

2/h

Continuous

5/h

Continuous

6/h

Continuous

Al - Fe - Ca - Si - S - P - K

7/h

Cement Silo

Additives

Blending Silos

HOT MEAL

CLINKER

CEMENT

On line Process Control

Advantages over centralised automatic laboratory Analysis at a higher frequency  energy savings and more stable quality o

o

Normally cheaper systems o

Simpler to operate

o Independent systems  no risk of having no analysis at all in the whole plant

5

RAW MIX CONTROL

Raw Mix Control WHY CONTROL THE RAW MIX ?  Check the fineness, especially the %>90microns

The large particle typically come from quartz silica that is hard to grind. If the %>90microns goes up, the clinker will be harder to burn, and C2S (Belite) will be present in clusters that will have an impact on cement reactivity and strengths

6

Raw Mix Control WHY CONTROL THE RAW MIX ?  Check the LSF (Lime saturation factor)

A 1% change in LSF (at constant FCaO) corresponds to a 2% change in C3S LSF should never exceed 100, as this will result in increase of FCaO Higher C3S will result in more reactive cement, with higher early strengths Hardening Comparison in Kg/cm² Alite C3S Belite C2S

7 Days

322 24

28 Days

466 42

180 Days

512 194

365 Days

584 325

Changes in Raw Mix LSF should be maintained below 1%

Raw Mix Control WHY CONTROL THE RAW MIX ?  Check the Silica Ratio SR (ratio of Si to Al and Fe)

If the Silica Ratio goes up for a given LSF, the C3S will go up but less molten liquid will be formed (less C3A and C4AF). So a dusty kiln, less coating, and the clinker combination will be more difficult

Changes in SR should be kept below 0.1

7

Raw Mix Control WHY CONTROL THE RAW MIX ?  Check the Alumina Ratio AR (ratio of Al to Fe)

The Alumina Ratio determines the quantity of flux or liquid formed at low temperatures (around 1330°C) and also has an impact on cement (high C3A will have higher heat of hydration)

Chnages in AR should be kept below 0.1

Raw Mix Control TRADITIONAL CONTROL TRADITIONALLY ONE HOUR COMPOSITE RAW MIX SAMPLES ARE COLLECTED MANUALLY AND BROUGHT BACK TO THE PLANT LABORATORY TO BE ANALYSED ONCE AN HOUR THE RESULTS ARE THE GIVEN TO THE PLANT OPERATORS, SO THAT THEY CAN ADJUST THE WEIGH FEEDERS THAT CONTROLS THE FEED TO THE RAW MILL

8

Raw Mix Control What are the major drawbacks with the traditional method ?  Non representative sampling system  Low frequency control  Long lag time  Human error

Raw Mix Control What are the major drawbacks with the traditional method ? Frequency of control 100

LSF 1 HOUR

Change only every hour : large fluctuations 100 LSF 1 HOUR

Increased frequency : smaller fluctuations and target hit more often Higher average LSF values  higher C3S  more reactive cement

9

Raw Mix Control Best location to take a sample Precalciner Kiln Dust

Blending Silos

Additives

Quarry

Preblending

Raw Mill

Crusher

Kiln

At the input of the feed to the blending silo including the kiln dust where applicable, as : • this is the final product including kiln dust • takes into account the raw mill grinding circuit residence time of the different raw material components

Raw Mix Control

Requirements for an efficient raw mix control system  Representative & reliable sampling system  High quality sample preparation  Repeatable & reliable analysis  High frequency control

10

Raw Mix Control Typical layout

Major oxides quantification + raw mix control software

Sampling in a chute

 Automatic control of the weight feeders

Sampling in an airslide Slot Sampler

Screw Sampler

Mixing

Piston Sampler

Mechanical Transport

On site EDXRF analyser Up to 7 analysis per hour Up to 2 sampling points controlled with 1 single analyser

To plant PLC or Raw Mix Control Software: Ca, Si, Al, Fe, etc.

Raw Mix Control Case Study Automatic raw mix control system as installed in a plant in India Analyser

Sampling

Sample Transport

11

Raw Mix Control Case Study Results Raw mix Analyser(FX-3500)

Time

Al2O3 Fe2O3

SiO2

CaO

LSF

SM

AM

00:17:00

13,82

3,25

2,91

42,99

0,966

2,24 1,12

00:37:00

13,60

3,08

2,82

43,05

0,987

2,31 1,09

00:57:00

13,71

3,21

2,83

43,16

0,979

2,27 1,13

01:17:00

13,61

3,11

2,81

43,01

0,985

2,30 1,11

02:05:00

13,94

3,25

2,86

42,94

0,959

2,28 1,14

02:25:00

13,69

3,24

2,86

42,77

0,970

2,24 1,13

02:45:00

13,44

3,06

2,80

42,28

0,980

2,29 1,09

03:05:00

13,67

3,19

2,77

42,99

0,979

2,29 1,15

03:25:00

13,42

3,20

2,76

42,79

0,990

2,25 1,16

03:45:00

13,86

3,27

2,77

42,79

0,961

2,29 1,18

04:05:00

13,49

3,23

2,85

42,42

0,975

2,22 1,13

04:25:00

13,76

3,35

2,91

42,78

0,963

2,20 1,15

04:45:00

13,31

3,30

2,92

42,58

0,987

2,14 1,13

05:05:00

13,80

3,26

3,14

42,36

0,950

2,16 1,04

05:25:00

13,25

3,35

3,07

42,17

0,978

2,06 1,09

05:45:00

13,69

3,39

3,11

42,62

0,959

2,11 1,09

06:05:00

13,46

3,13

3,11

42,62

0,981

2,16 1,01

06:25:00

13,73

3,41

3,17

42,68

0,957

2,09 1,08

06:45:00

13,62

3,35

3,15

42,54

0,962

2,10 1,06

07:05:00

13,76

3,45

3,10

42,81

0,958

2,10 1,11

07:25:00

13,70

3,30

2,97

42,64

0,964

2,19 1,11

07:45:00

13,75

3,27

2,92

42,88

0,967

2,22 1,12

08:22:00

13,71

3,27

2,93

42,80

0,968

2,21 1,12

08:42:00

13,59

3,09

2,85

42,78

0,981

2,29 1,08

09:26:00

13,52

3,22

2,81

42,96

0,987

2,24 1,15

10:09:00

13,59

3,21

2,94

42,34

0,966

2,21 1,09

10:29:00

13,32

3,12

2,96

42,68

0,993

2,19 1,05

10:49:00

13,54

3,23

3,04

42,72

0,976

2,16 1,06

11:09:00

13,50

3,27

2,98

42,69

0,978

2,16 1,10 2,15 1,08

11:29:00

13,69

3,31

3,06

42,59

0,962

12:16:00

13,36

3,06

2,96

42,77

0,995

2,22 1,03

12:30:00

13,85

3,34

3,09

42,54

0,950

2,15 1,08

12:50:00

13,56

3,18

3,05

42,59

0,973

2,18 1,04

13:10:00

13,70

3,26

3,03

42,64

0,964

2,18 1,08

13:30:00

13,76

3,34

3,06

42,48

0,954

2,15 1,09

13:50:00

14,03

3,34

3,11

42,46

0,937

2,18 1,07

14:10:00

13,72

3,31

3,11

42,47

0,956

2,14 1,06 2,21 1,01

14:30:00

13,74

3,13

3,09

42,43

0,959

14:50:00

13,75

3,34

3,03

42,45

0,954

2,16 1,10

15:10:00

13,61

3,23

2,90

42,72

0,974

2,22 1,11

16:06:00

13,45

3,18

2,83

42,76

0,987

2,24 1,12

16:26:00

13,61

3,28

2,81

42,81

0,976

2,23 1,17

16:46:00

13,74

3,10

2,79

42,87

0,974

2,33 1,11

17:06:00

13,73

3,33

2,80

42,80

0,967

2,24 1,19

17:26:00

13,43

3,15

2,75

43,11

0,999

2,28 1,15 2,28 1,16

17:46:00

13,66

3,21

2,77

42,79

0,975

18:06:00

13,54

3,17

2,73

43,08

0,991

2,29 1,16

18:26:00

13,62

3,10

2,81

42,82

0,980

2,30 1,10

18:46:00

13,62

3,18

2,87

42,85

0,978

2,25 1,11

19:06:00

13,56

3,27

2,89

42,63

0,974

2,20 1,13

23:03:00

13,45

3,18

2,85

42,98

0,992

2,23 1,12

23:23:00

13,62

3,24

2,92

42,84

0,975

2,21 1,11

23:43:00

13,63

3,09

2,89

42,98

0,982

2,28 1,07

Min

13,25

3,06

2,73

42,17

0,94

2,06 1,01

Max

14,03

3,45

3,17

43,16

1,00

2,33 1,19

Ave

13,63

3,23

2,93

42,72

0,97

2,21 1,10

Std dev

0,16

0,09

0,13

0,22

0,01

0,06

0,04

Raw Mix Control Case Study Results

Raw Meal LSF value over 24 hours sampled every 20 mn, with 0.97 Target LSF Standard deviation < 0.01

12

Raw Mix Control Case Study Results

Raw mix Analyser(FX-3500)

24 Hour Min

LSF 0,94

SM

AM

2,06 1,01

Raw mill Lab XRF (Bruker-S4)

24 Hour

LSF 0,96

SM

AM

2,07 1,05

Kiln feed Lab XRF (Bruker-S4)

24 Hour

LSF

SM

AM

CLINKER ANALYSIS in Lab XRF (Bruker-S4)

24 Hour

0,96 2,16 1,06

LSF

AM

SM

0,92

1,20

2,09

Max

1,00

2,33 1,19

1,00

2,34 1,20

0,93

1,24

2,17

Ave

0,97

2,21 1,10

0,97

2,24 1,12

0,97

2,18 1,08

0,92

1,22

2,13

Std dev

0,01

0,06 0,04

0,01

0,07 0,04

0,01

0,02 0,02

0,00

0,01

0,03

0,99 2,21 1,12

The plant maintains a low raw mix standard deviation despite having diverse raw material sources

HOT MEAL CONTROL

13

Hot Meal Control WHY CONTROL THE HOT MEAL ?  Check the actual calcination value at the outlet of the precalciner In modern kilns 50 to 60% of the total fuel consumption is burnt in the precalciner. The temperature value that is traditionally used to control fuel usage only gives partial information on precalciner performance. Knowing the actual calcination value, it is possible to optimize the fuel input to obtain a consistent and stable process

Hot Meal Control WHY CONTROL THE HOT MEAL ?  Check the actual Volatile Cycle in the kiln/precalciner Control volatile cycle of : Sulphur, Chlorine, Alkalis To either : • Adjust their content ratio in the fuel or raw meal mix to avoid build up problems in the precalciner, and optimize the Sulphur/Alkali ratio • Adjust the kiln by pass gas flow, when such systems exist, so as to avoid wasting material and loosing energy

14

Hot Meal Control TRADITIONAL CONTROL TRADITIONALLY A SPOT SAMPLE IS COLLECTED MANUALLY AND BROUGHT BACK TO THE PLANT LABORATORY TO BE ANALYSED ONCE A SHIFT THE RESULTS ARE THE GIVEN TO THE PLANT OPERATORS, WHO TYPICALLY NEVER USE THE INFORMATION TO CONTROL THE CALCINER ..

Hot Meal Control

What are the major drawbacks with the traditional method ?  Non representative sampling system  VERY Low frequency control  Long lag time  Human error  Data never actually used to control the process

15

Hot Meal Control

Requirements for an efficient hot meal control system  Representative & reliable sampling system  Repeatable & reliable analysis  High frequency control (should be done at least once an hour)

Hot Meal Control Typical layout Piston Sampler PC303

Quenching system Sample short distance Transport

To plant PLC : Calcination value

Up to 2 analysis per hour

Loss on ignition analysis

16

Hot Meal Control Typical layout Piston Sampler PC303

Quenching system Sample short distance Transport

To plant PLC : Calcination value Sulphur Content

Up to 4 analysis per hour

Carbon Sulphur Determination

Hot Meal Control Case Study Automatic hot meal control system as installed in a cement plant in India

LOI Analyser

CCR to control calciner

Hot meal Sampler + Quencher

17

Hot Meal Control Case Study Automatic hot meal control system as installed in a cement plant in India

Results Date 23.01.2013

Time 15.26 PM 15.56 PM 16.26 PM 16.56 PM

Average

LOI Analyser Result 97,32 97,90 98,28 97,74

Lab Result 97,51 97,89 97,98 97,72

Variance ‐0,19 0,01 0,30 0,02

97,81

97,77

0,04

Data comparison between on line analyser and plant laboratory

Hot Meal Control Case Study Results

LOI value is monitored every 30 mn Fuel input to calciner is adjusted based on the actual LOI data STABLE and OPTIMUM calcination value

18

CLINKER CONTROL

Clinker Control WHY CONTROL CLINKER ?  Check the Free Lime Value (FCaO%) -High free lime will have a negative impact on 28 day strengths. Small hard burned free lime particles hydrate very slowly. They will hydrate many days after being in contact with water, and double in size, causing cracks in the concrete

- If the LSF is correctly dosed, low free lime indicates that the clinker has been hard burnt. This results in large Alite crystals, that are hard to grind, and the cement has a lower reactivity.

19

Clinker Control WHY CONTROL CLINKER ?  Check clinker mineralogy Increased usage of alternative fuels, with high ash content, heavy metal content, Chlorine and Sulphur content, etc, will have a direct impact on clinker mineralogy and therefore on cement quality.

Clinker Control WHY CONTROL CLINKER ?  Use the data to optimize the kiln burner operation

HOURS

20

Clinker Control Free Lime and Kiln Data







A high frequency free lime measurement is required (< 20 mn)

Free Lime / Burning Zone T°/ Kiln Amps and NOx are closely correlated over the short term

Over the long term the relation between Free Lime / BZT/ Kiln Amps and NOx changes

Clinker Control Free Lime and Kiln Data

o

o

Incremental instantaneous control based on NOx, BZT, Kiln Amps or a weighted average of the 3

o

Clinker is sampled as close as possible to the clinkering zone and analysed with a high frequency

Free Lime results are used to update the set points for each of the control factors

21

Clinker Control TRADITIONAL CONTROL TRADITIONALLY A SPOT SAMPLE IS COLLECTED MANUALLY FROM THE COOLER DISCHARGE OR FROM THE PAN CONVEYOR AND BROUGHT BACK TO THE PLANT LABORATORY TO BE ANALYSED ONCE AN HOUR THE RESULTS ARE THE GIVEN TO THE PLANT OPERATORS, WHO TYPICALLY ONLY USE THE INFORMATION TO DECIDE TO BYPASS OFF SPEC CLINKER

Clinker Control

What are the major drawbacks with the traditional method ?  Non representative sampling system  Low frequency control  Long lag time  Human error  Information is only a POST MORTEM

22

Clinker Control Best location to take a sample Precalciner

Clinker Silo Kiln

Cooler

At the discharge of the kiln before the cooler as : • there is no lag time between clinker production and sample collection • Coating being larger and not crushed at this point can be removed selectively from the actual clinker

Clinker Control Clinker sampling systems

Cooler Kiln

Under grate Sampler Cooler

Kiln discharge

Cooler discharge Sampler

23

Clinker Control Sample Transport system

Bend

Receiving cyclone Sending station Diverter (several lines)

Clinker Control Sample Transport system

24

Clinker Control Analyser using glycol extraction and conductivity

Analysis cell

Preparation cell

Heating Mixing of clinker + glycol Conductivity measurement

CaO + (CH2OH)2  H2O + (CH2O)22- + Ca 2+

Clinker Control At Line XRD Analyser

Solid state detector

Clinker is ground to fine powder The sample is moving on a turntable On line complete mineralogical composition of the clinker is given About 100g/min are analysed

25

Clinker Control At Line XRD Analyser

Typical installation

It is possible with this analyser to determine all the phases of clinker  determine the real clinker quality, not the one calculated by Bogue  increase the use of alternative fuels, and determine their effects on clinker on a real time basis

Clinker Control Case Study Automatic free lime control system as installed in a cement plant in India

CCR to control kiln pyroprocessing

Kiln discharge Sampler Free Lime Analyser

Free Lime data

26

Clinker Control Case Study Results

The plant managed to optimize the free lime value and maintain a low standard deviation Average = 1% Std dev = 0.1%

In case of upset conditions, the plant can catch the off spec clinker immediately before it goes into the clinker silo

Clinker Control Case Study 2 Free Lime and Kiln Data

% Free lime

US Plant With 2 wet kilns % free lime 1 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0

K-1 K-2 1

2

3

Date

1 : Analysis not used to control the kiln (over burnt clinker) 2 : Manual control of kiln using free lime (higher free lime rate but unstable) 3 : Kiln Expert System connected to the analyser (stable and higher free lime rate)

27

Clinker Control Savings Direct Savings A 0,5 % increase in free lime results in :  15 Kcal / Kg CK of fuel savings  1 KWh / Ton CK of electricity savings

Indirect Savings  Manual analysis labour cost  Cost of handling production rejects  Post production incident costs

CEMENT CONTROL

28

Cement Control WHY CONTROL CEMENT ?  Check the Gypsum Content (CaSO4·2H2O) Gypsum is the set retarder for Ordinary Portland Cement (OPC). Without gypsum, ground clinker exhibits flash setting in a few minutes, due to the rapid hydration of calcium aluminates SO3 percent

Setting time, min Initial Final

1 day

Compressive strength, Mpa 3 day 7 day 28 day

12 hour

Heat of hydration, Kcal/kg 1 day 3 day 7 day

28 day

1.80

115

150

17.7

37.4

53.8

61.6

22.5

33.2

45.4

59.3

67.2

2.10

130

165

20.9

40.2

59.0

65.4

28.2

33.2

44.5

63.0

65.7

2.40

135

180

20.9

32.1

47.8

62.0

46.0

54.2

63.2

80.3

88.5

But gypsum also has an impact on strength and heat of hydration. If gypsum content is too high the heat of hydration will increase and strengths will decrease It should therefore be maintained within a narrow tolerance

Cement Control WHY CONTROL CEMENT ?  Check the Limestone Content (CaCO3)

Optimize limestone content, as per regulatory norms

It should therefore be maintained within a narrow tolerance. Limestone being much cheaper then clinker, limestone usage when allowed should be maximized…

29

Cement Control WHY CONTROL CEMENT ?  Check Cement Fineness

Cement fineness has a direct relation with concrete performance: • Early strengths • Heat of hydration • Long term strengths

Cement Control WHY CONTROL CEMENT ?  Check Cement Fineness - Electrical energy used in the grinding process accounts for 1% of the world’s energy supply - Milling is very inefficient: < 5% of energy goes into size reduction, the rest is wasted as heat A balance has to be struck between : Over grinding results in high milling costs and creates an excess of particles < 2 mm This leads to the cement curing exothermically, setting too fast (cracking) and increases water demand And Under grinding where particles > 32 mm are not being fully hydrated even after long curing periods thus reducing the final strength

30

Cement Control TRADITIONAL CONTROL TRADITIONALLY A COMPOSITE SAMPLE IS COLLECTED MANUALLY FROM FEED TO THE TRANSPORT SYSTEM TO THE CEMENT SILOS AND BROUGHT BACK TO THE PLANT LABORATORY TO BE ANALYSED ONCE AN HOUR THE RESULTS ARE THE GIVEN TO THE PLANT OPERATORS, WHO USE THE INFORMATION TO ADJUST THE SEPERATOR AND THE CEMENT MILL WEIGH FEEDERS

Cement Control

What are the major drawbacks with the traditional method ?  Non representative sampling system  Low frequency control  Long lag time  Human error  Blaine values are used for fineness control

31

Cement Control Blaine Values

2 samples each with same area but a different particle size distribution

Cement Control Blaine Values

Blaine number is not a reliable parameter (especially for blended cements)!!

 Identical Blaine number but very different behaviour regarding curing and thus final mechanical properties

32

Cement Control PSD Values High heat of hydration Contribution to early strength Contribution to late strengths < 32 microns Zero contribution to strengths > 32 microns

 Using PSD values it is possible to optimize and stabilize the required cement properties

Cement Control Best location to take a sample

At the outlet of the cement grinding circuit before the transport system to the cement silos as : • this is the final product, including cement dust

33

Cement Control C/S Analyser Sampling in an airslide

Sampling in a chute

Slot Sampler Screw Sampler

Piston Sampler P11

Screw sampler

Mechanical Transport

To plant PLC : Limestone & gypsum rates Analyser CO2/SO3

Variable pitch = sampling on the whole cross section of the chute  better representativity

Cement Control C/S Analyser

- Analyser dedicated to cement process control 200 crucible storage system

- 1 analysis / 10 min

34

Cement Control C/S Analyser

Quantification of limestone & gypsum additives  Optimisation of cement composition

Cement Control PSD Analyser

Laser diffraction

35

Cement Control PSD Analyser Vertical chute at classifier outlet

Sampling in a vertical chute

Sampling system

On line PSD

Cement Control PSD Analyser

Scheme

Vertical chute at separator outlet

On Line PSD Sampling system

36

Cement Control PSD Analyser

Continuous measurement:  results on a real time basis: %>X µm, Dv(X), Blaine number, particle size distribution…  ± 15 kg/h of cement are analyzed: representative sample

Cement Control PSD Analyser

Classifier can then be monitored close to the specification limits  Energy savings on grinding operation

37

Cement Control Case Study PSD Analyser Cement plant in the UK Product specification change with off line analysis

PSD data not available to the operator during the change from OPC (Ordinary Portland Cement) to RHPC (Rapid Hardening Portland Cement)  Blaine manual analysis 3 hours required to reach the required specifications  Loss of ± 100 T of cement!!

Cement Control Case Study PSD Analyser Cement plant in the UK Product specification change with on line analysis Product change 360  500 m2/kg

In spec material

PSD data available to the operator during the change from OPC (Ordinary Portland Cement) to RHPC (Rapid Hardening Portland Cement)  Less than 30 min required to reach the required specifications  Savings on purging time

38

Cement Control Case Study PSD Analyser Cement Plant in USA Summary of the impact of automated control and real time particle size measurement on production parameters Before high level control

After high level control, without on line PSD

With high level control and on line PSD

Bucket elevator pwer (kW) Average

48

60

69

Std. Dev.

3,81

2,35

3,33

Seperator speed rpm

•

Implementation of a High Level Process Control System with an online PSD : • 20.3% Reduction in specific energy consumption • 15% throughput increased • 15% increase in 1 day strength • 10% reduction in Blaine • C3S Concentration decreased Water demand of cement is stable and low

Average

1414

1536

1476

Std. Dev.

40

45

22

Total feed rate (tph) Average

118

127

136

Std. Dev.

4,2

5,7

3,8

4468

Mill power (kW) Average

4884

4902

Std. Dev.

21

13

19

kWh/t

41,8

39,1

33,3

2125,49

2176;54

2454,35

60,22

61,21

59,69

One day strengths (psi) Average C3S (%) Average

PROCESS CONTROL Conclusions Quality control data should be used to actually optimize the cement manufacturing process and not only be used for post portem reporting

o

o

More accurate & higher frequency results, means that it is possible to better control the process, and therefore improve quality AND save energy costs o

Most of these solutions have a fast payback < 1 YEAR

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THANK YOU FOR YOUR ATTENTION

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