Understanding the Attributes for Modeling & Optimizing

Neos Aware organize the information in different level to facilitate the navigation and data record.

The Data is organized in three parts:

  • Process Group
  • Phases
  • Attributes

Process Group and Phase is used to segment the process for better navigation and data introduction.

The attributes is divided in two types:

  • Attributes to Process Control  – these attributes register the process condition for one project
  • Attributes for Modeling and Optimizing

The Attributes Management allows making hundreds of objectives, constrains, maximization, minimization, etc…

The attributes are the following:

Neos Aware organize the information in different level to facilitate the navigation and data record.

Data is organized in:  Process Group – Phases – Attributes.

In this lesson, the Attributes management will be explained for better understand to increase the ability to develop accurate modeling & optimizing.

1- Process Phase: Initial Conditions

The objective of this group is record the data of your raw materials used in the project.
Is important these data to manage the product and establish the raw material parameters for the future.
In this group you found the following:

Group Attribute Usage – Examples
Liquid Conditions Density Record the liquid raw material like Dispersing Agents, Binder, etc.
Liquid Conditions pH Record the liquid raw material like Dispersing Agents, Binder, etc.
Liquid Conditions Solid content Record the liquid raw material like Dispersing Agents, Binder, etc.
Liquid Conditions Viscosity Record the liquid raw material like Dispersing Agents, Binder, etc.
Initial Moisture Moisture Record the Moisture of Raw material used in the project
Initial Particle Size Initial Particle Size Record the Size of Raw material used in the project

This attributes is only recorded, and not applied in the modeling & optimization, the importance of them is for the project management, for the future projects, quality control, maintenance of master standard of each raw materials.

2 – Process Phase: Milling

This group is divided in two sub-groups:

  • Record the quality of the water used in the milling process
  • Milling parameters to modelling and optimizing

Record the water used in the milling process is very important, in particular when is used recycled water.

This record is used to create the acceptable parameter of the water, develop quality process control, and for master standard for the projects. 

Record the quality of the water used in the milling process

Group Attribute Usage – Examples
Milling water conditions Conductivity Parameter associate with the soluble salts content
Milling water conditions Density Solid Contain
Milling water conditions Hardness Ca,Mg correction or sequestrants usage
Milling water conditions pH Interference in the Rheology
Milling water conditions Solid content Percentage of slip into the water

This attributes is only recorded, and not applied in the modeling & optimization, the importance of them is for the project management, for the future projects, quality control, maintenance of master standard of the water.

Milling parameters to modelling and optimizing

Group Attribute Usage – Examples
Milling process Milling time The time to achieve the residue of one formula is used to optimize the electricity cost in the milling department or productivity increase
Rheology Dispersing agent Useful only to optimize when is used a fixed viscosity/density and variable dispersing agent
Rheology Solid content Advantageous to reduce the gas consumption of spray drier
Rheology Density Valuable to optimize the gas consumption of spray drier
Rheology Viscosity Important parameter for process control and is dependent of the other milling parameter
Thixotropy Thixotropy 1 Important parameter for control of process
Thixotropy Thixotropy 2 Important parameter for control of process when the slip has aging more time
Thixotropy Thixotropy 3 Important parameter for control of process when the slip has aging long time

When these attributes is recorded, and applied in the modeling & optimization, the importance of them is to reduce water consumption, milling cost, electricity consumption and gas consumption in the spray drier.

3 – Process Phase: Powder

This group is divided in four sub-groups:

  • Parameter for characterization and process
  • Chemical Analysis to modeling & optimizing
  • Mineralogical Analysis to modeling & optimizing
  • Other parameter to modeling & optimizing

The parameter for characterization and process is recorded to manage one specific process data and special characterization to deepen into the knowledge of one raw material or formula.

Parameter for characterization and process

Group Attribute Usage – Examples
Moisture Moisture The moisture of the powder is to verify if is inside the acceptable range of moisture to press the sample
Granulate distribution size Granulate distribution size This field is to validate the grain size distribution when the study use spray dried product
DTA DTA Is useful to predict the behavior of the formula during the firing process and selection of glaze
SEM SEM This attribute is used to know contaminants and components of one powder
Heating Microscope Heating Microscope This measurement is applied to understand the behavior of feldspar, flux and formulas

This attributes is only recorded, and not applied in the modeling & optimization, the importance of them is for the project management, for the future projects, quality control, maintenance of master standard and improvement of the knowledge. 

Chemical Analysis to modeling & optimizing

The chemical analysis of unfired powder are defined for each single raw material and calculated for each formula.

The oxides being introduced are configurable by the user, is open to add or eliminate oxides from the master table of oxide parameters.

The oxides and others chemicals already load in the software are:

Group Attribute Usage – Examples
Oxide analysis Al2O3 Normally is defined the relation against SiO2
Oxide analysis B2O3 Flux, Contaminant
Oxide analysis BaO Flux, Contaminant
Oxide analysis CaO Flux or compound for monoporosa
Oxide analysis Cr2O3 Contaminant , Coloring agent
Oxide analysis Fe2O3 Contaminant , Coloring agent, Flux
Oxide analysis K2O Flux
Oxide analysis MgO Flux or compound for monoporosa
Oxide analysis MnO Contaminant , Coloring agent, Flux
Oxide analysis Na2O Flux
Oxide analysis P2O5 Amphoteric
Oxide analysis PPC in Ox.An Loss of ignition from the chemical analysis
Oxide analysis SiO2 Normally is defined the relation against Al2O3
Oxide analysis SrO Flux
Oxide analysis TiO2 Contaminant , Coloring agent
Other Chemical analysis Carbonates Carbonates for monoporosa or contaminant
Other Chemical analysis Chlorine Contaminant
Other Chemical analysis Organic carbon Produce black core
Other Chemical analysis Fluoride Contaminant for gases emission
Other Chemical analysis Sulfur Contaminant for gases emission
Other Chemical analysis Ca2+ Contaminant affect the rheology of the slip
Other Chemical analysis Cl- Contaminant affect the rheology of the slip
Other Chemical analysis F- Contaminant for gases emission
Other Chemical analysis K+ Contaminant affect the rheology of the slip
Other Chemical analysis Mg2+ Contaminant affect the rheology of the slip
Other Chemical analysis Na+ Contaminant affect the rheology of the slip
Other Chemical analysis SO42- Contaminant for gases emission and affect rheology
Other Chemical analysis Total soluble salts Contaminant for gases emission and affect rheology

You can add more oxides, or eliminate the oxide not used.

In the modelling & optimization you can define limits, relation against another oxide, maximal summation of one group of oxides and combination of constrains. 

Mineralogical Analysis to Modeling & Optimizing 

The mineralogical analysis of unfired powder are defined for each single raw material and calculated for each formula.

The minerals being introduced are configurable by the user, is open to add or eliminate minerals from the master table of minerals parameters.

The minerals already load in the software are:

Group Attribute Usage – Examples
Mineral analysis Albite Quantity of albite in one sample
Mineral analysis Alunite Contaminant of sulfates
Mineral analysis Anatase Contaminant
Mineral analysis Anorthite Flux, plagioclase feldspar
Mineral analysis Calcite Contaminant or to monoporosa process
Mineral analysis Dolomite Contaminant or to monoporosa process
Mineral analysis Illite Improve the pressing ability
Mineral analysis Kaolinite Whiteness, low pyro-plasticity, high refractory
Mineral analysis Magnesite Contaminant or flux
Mineral analysis Montmorillonite MOR and rheology interference
Mineral analysis Potassium feldspar Quantity of feldspar in one sample
Mineral analysis Quartz Free quartz

You can add more minerals, or eliminate the mineral not used according your raw materials.

In the modelling & optimization you can define limits, relation against another mineral, maximal summation of one group of mineral and combination of constrains. 

Other parameter to Modelling & Optimizing 

Also, in the unfired powders other parameters are load to modelling & optimizing.

Group Attribute Usage – Examples
Plasticity Plasticity Identify the plasticity of one raw material or formula is related with the pressing ability
TGA TGA1 Weight losses in the first range of temperature
TGA TGA2 Weight losses in the second range of temperature
TGA TGA3 Weight losses in the third range of temperature
TGA TGA4 Weight losses in the fourth range of temperature
TGA TGAt Total weight losses in the range of temperature

The TGA data is recorded for each raw material and calculated for the formulas.

The plasticity is measured in the formulation due to the interaction between raw materials, after perform the initial formulas the software predict the plasticity of one composition.

In modeling and optimization, the plasticity range could be one constrain.

The behavior of TGA for one formulation could be useful for the kiln operation, to predict the tendency to create black core and could be used as constrain.

4 – Process Phase: Unfired

 

In the pressing process several attributes must take in consideration to modeling & optimizing.

Take under control this attributes increase productivity and reduce the breakage of pieces during the process.

This group is divided in two sub-groups:

  • Process Control
  • Characteristics of the piece after the press

This attributes for process control of pressing is only recorded, and not applied in the modeling & optimization, the importance of them is for the project management, for the future projects, quality control, maintenance of master standard of project process.

Process control has:

Group Attribute Usage – Examples
Pressing process Pressing pressure The pressing pressure could be variable if you work with fixed apparent density or constant pressing pressure if you work with variable apparent density
Piece moisture Piece moisture To have a comparable results, the moisture must be permanently inside an acceptable range

Characteristics of the piece after the press 

The attributes after pressing process is advantageous to solve problems like breakage and improve the characteristics of the ceramic tile produced.

The attributes are the following:

Group Attribute Usage – Examples
Mechanical strength Dry mechanical strength The pieces must have MOR adjusted for the size, thickness, for the kind of glazing and decoration. Modelling according your process demands and define the acceptable range for the process.
Mechanical strength Glaze mechanical strength According the glazing process the pieces must have a minimal MOR to avoid breakage in the boxes and entrance of the kiln, define the limits and use for the modelling.
Mechanical strength Green mechanical strength The movement of the piece from the press until the drier requires a minimal MOR after the press; define the limits and write adequate constrains in your modelling project.
Apparent density Dry apparent density Apparent Density after the pressing process defines the quality of compaction, interparticle pores and particle surfaces intimacy. This attribute has influence in the fired results and has relationship with other characteristics like water absorption or shrinkage. Define the minimal values or maximize the result in your modelling project gives better results.
Apparent density Green apparent density The measurement of Apparent Density could be after drier or before, select our preferred method between both.
Unfired shrinkage Post-dryer shrinkage The Post-dryer shrinkage gives the information of possible defects after the drier like cracks, fissures, and others. Define the limits for your modelling project.
Unfired shrinkage Post-press expansion The post-press expansion could create tension in the pieces, breakage or problems in the piece extraction from the mold; define the eligible parameter for constrains when you are modelling.
Hydro-plasticity Hydro-plasticity When the piece is glaze, the water penetrates in the capillarity of the piece generating a tension that creates a deformation, convex and later concave, in the piece. This effect could create difficulties to charge and discharge the boxes, and also in the entrance of the kiln. Define the process limits and place in your constrain to modelling.

Basically the ceramic tile is making in the pressing process, if the quality is low after the press, innumerous problems will be faced during the process. 

These attributes is fundamental for the modeling and optimization. Take advantage of it!

5 – Process Phase: Fired Ceramic

After the firing process several attributes are measured and must be used to Modeling & Optimizing.

The Group Fire Ceramic is divided in two parts:

  • Characterization of pieces after firing process not used for Modelling & Optimizing
  • Attributes use for Modelling & Optimizing

The parameter for characterization of pieces after firing process is recorded to deepen into the knowledge of one formulation.

According the methodology applied in the project, variable temperature inside of range of water absorption or fixed temperature and variable water absorption, the identification of fixed temperature is the consonant “T” after the attribute.

The parameters are the following:

Group Attribute Usage – Examples
Mineralogical Phases Anortite Identify the mineralogical phases after the firing process
Mineralogical Phases Mullite Identify the mineralogical phases after the firing process
Mineralogical Phases Kaolinite Identify the mineralogical phases after the firing process
Mineralogical Phases Magnesite Identify the mineralogical phases after the firing process
Mineralogical Phases Quartz Quartz phase
SEM SEM Structural defects

This attributes for characterization of fired ceramic pieces is only recorded, and not applied in the modeling & optimization, the importance of them is for the project management, for the future projects, quality control, maintenance of master standard of project process and improve knowledge.

Attributes use for Modelling & Optimizing 

Important attributes after firing process is used in the Modelling & Optimization.

Get the maximal stability, nonexistence of defects, perfect planarity and dimensions, maintenance of the ceramic body color, whiteness, and water absorption according the normative define the quality of the ceramic tile.

The attributes to be used in the modelling & Optimizing are the following:

Group Attribute Usage – Examples
Colour Colour: a Define the objective of “a” parameter green to red color and define your constrain
Colour Colour: b Define the objective of “b” parameter blue to yellow color and define your constrain
Colour Colour: L Define the objective of “L” parameter of lightness of the color to achieve super withe porcelain tiles, maintain your standard or reduce cost with the same colour
Apparent density Fired apparent density Fired Apparent density means the densification of one material, is fundamental for porcelain tile to achieve the maximal densification in relation of the minimal water absorption. Or take under control for the monoporosa process. Use constrains, maximization or minimization, is very useful for the modelling process to achieve amazing results.
Fired MOR Fired mechanical strength The fired mechanical strength is used in the modelling & optimization to maximize the result of one formula. Define your limits and constrain.
Lineal Shrinkage Lineal Shrinkage Control the Linear Shrinkage is fundamental to control the dimensional variance, use constrains or the object mode “slop the line” to obtain better stability of the shrinkage against a range of water absorption.
Moisture expansion Moisture expansion This measurement predicts future defects after the tile laying, define limit and use this constrain to avoid claims.
Pyro-plasticity Pyro-plasticity Planarity control is key in the tile industry, bigger size demand lower pyro-plasticity, modeling and optimizing with this constrain  to achieve outstanding results, apply the object mode “slope the line” to increase the stability of the composition, define the pyro-plasticity inside your production temperature stability in the kiln.
Water absorption Temperature Water absorption against the temperature is a key parameter to achieve high quality standard, use this attribute to get the water absorption in defined temperature, search higher stability in one range of temperature.

6 – Process Phase: Fired Chemical

After the firing process other important attributes are measured and must be used to Modeling & Optimizing.

The Group Fire Chemical includes the coefficient of expansion, the black core, the loss of ignition, and all chemical analysis after firing.

The parameter for characterization of pieces after firing process is recorded to deepen into the knowledge of one formulation.

The parameters are the following:

Group Attribute Usage – Examples
Coefficient of expansion COE1 COE in the first range of temperature, define the constrains according your selection of engobes and glazes
Coefficient of expansion COE2 COE in the second range of temperature, define the constrains according your selection of engobes and glazes
Coefficient of expansion COE3 COE in the third range of temperature, define the constrains according your selection of engobes and glazes
Loss on ignition Loss on ignition The loss of ignition could be used as constrains according the project requirement
Oxidized layer Black core Establish the acceptable constrain of black core according your process, product typology, glazes used, etc.
Chemical analysis Al2O3 After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis B2O3 After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis BaO After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis CaO After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis Cr2O3 After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis Fe2O3 After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis K2O After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis MgO After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis MnO After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis Na2O After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis P2O5 After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis SiO2 After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis SrO After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project
Chemical analysis  TiO2  After fired the chemical analysis is used like unfired pieces but the LOI is excluded, this parameter could be used as constrain for your modeling & optimizing project

7 – Process Phase: Other

Perhaps the most important attribute today is the cost of the composition.

Usually is used as main objective of one optimization, in other words, minimal cost and maximal ceramic tile performance in the process and fired results.

Group Attribute Usage – Examples
Others Cost Maximize the results of your company minimizing the cost

7 – Properties Management

The tests performed in the laboratory are introduced in the workbench and record the results for each attribute.

Execute the initial formulas composition ( approximate two times of the number of raw materials)  in the laboratory and recorded at the workbench, Neos Aware platform will start the self-awareness processes.

These learning processes are beginning from the proprieties management calculation process.

The software will calculate millions of interactions between the raw materials and formulas based in the test results.

This step is mandatory to the procedure of simulation and optimization.

8 – Optimization Process

Normally the main objet of one optimization is the attribute “Cost”

However, you can select the main objective according your project requires.

You can use the number of attributes that you have selected.

Could be used the objective function:

  • Maximize or
  • Minimize

In the objective mode and after the selection of constrains you have several options to choose.

Attribute – you can select one attribute of your project and define constrain condition and value, also you can define the constrain weight from 0 to 10 (ten is maximal priority in the calculation, the software charge the weight 5).

Attribute Relationship- when you select this object, you define the relationship of one attribute against the other attribute. Is very useful when you want maintain the relationship between Silica/Alumina for example; in this case you select the calculation of “quotient”.

Another alternative is select “summation”, this is useful for example when you want that the sum of Sodium and potassium not exceed 4% for example.

You define the value objective, constrain condition and weight.

Slope of the line– this objet is very useful when you are research a composition with better stability.

Example, lower shrinkage in function of the water absorption reduction, more flat is the slop more stable is the dimensional variance  against the oscillation of the firing process. 

Delta E in a section- this object is to defined the difference of color allowed for the optimization in one range of temperature, of water absorption or other related characteristic. This is very useful for porcelain tile production.

Delta E versus standard value– this is useful when the new formula must have the same color tolerance against your standard.

Raw material percentage – this function allow limited the use of one raw material, sometimes has a volume limitation in the silos or other issues. 

You can pool all of them in one optimization, and select constrains conditions as:

Less than or equal  <=
Greater than >
Equal =
Less than <
Greater than or equal >=
Not allow <>
Between [ , ] 

Now was created your Modelling & Optimizing

  • Run the optimization
  • Realize the laboratory test and introduce the results in the workbench
  • Run the Proprieties Management
  • The software learns more!
  • Modeling and Optimizing again

Approximately after two or three looping of: “Optimization, Test , Proprieties Management”, Neos Aware will process Modelling & Optimizing outstanding.

Now, you are ready to improve the economical results of your company

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