DETERMINING PERFORMANCE IN FORMULATIONS FOR OIL-CONTAINING PRODUCTS FOR COSMETICS

Abstract

A computer implemented method for determining performance properties of an oil-containing product for cosmetics, the oil-containing product for cosmetics comprising different oils forming a mixture, the method comprising the steps of: providing to a processing device via an input channel o performance properties for each of the different oils o a measure for the ratio of the different oils in the mixture, o a data driven model and/or a rigorous model determining with a processing device determined performance properties of the oil-containing product for cosmetics comprising the mixture, based on o the data driven model o the performance properties for each of the different oils o the measure for the ratio of the different oils in the mixture, providing via an output channel o the determined performance properties of the oil-containing product for personal care and/or o the measure for the ratio of the different oils in the mixture and/or o a formulation of the mixture, and or o a formulation of the oil-containing product for personal care.

Claims

1. A computer implemented method for determining performance properties of an oil-containing and/or surfactant-containing product for cosmetics, the oil-containing product for cosmetics comprising different oils forming a mixture and/or the surfactant-containing product for cosmetics comprises at least one surfactant and further component forming the mixture, the method comprising: providing via a communication interface, composition parameters to a processing device providing via the communication interface a data driven model and/or a rigorous model to the processing device determining with a processing device determined performance properties of the oil-containing and/or the surfactant-containing product for cosmetics comprising the mixture, based on the data driven model and/or the rigorous model and the composition parameters, providing via an output communication interface the determined performance properties of the oil-containing and/or the surfactant-containing product for cosmetics and/or the composition parameters and/or a formulation of the mixture, and or a formulation of the oil-containing and/or the surfactant-containing product for cosmetics.

2. The method of claim 1, wherein the composition parameters comprise a measure for the ratio of the different oils and/or surfactant and the further component in the mixture.

3. The method of claim 1, wherein the composition parameters comprise performance properties for each of the different oils.

4. The method of claim 1, wherein the composition parameters comprise an identifier for each of the oils and/or surfactant and the further component and the method further comprises a step of deriving performance properties for each of the oils and/or surfactant and the further component from the identifier.

5. The method of claim 1, wherein the performance properties of each of the different oils and/or surfactant and the further component relate to physico-chemical properties of each of the different oils and/or surfactant and the further component.

6. The method of claim 1, wherein the performance properties of each of the different oils and/or surfactant and the further component relate to sensory properties of each of the different oils and/or surfactant and the further component.

7. The method according to claim 1, wherein oil-containing product for cosmetics comprises at least two different oils, at least three different oils, or at least four different oils.

8. The method of claim 1 further comprising the step of providing to the processing device via the communication interface target performance properties of a specific oil or a mixture of oils and/or surfactant and the further component or a mixture of surfactant and the further component for cosmetics.

9. The method of claim 8, wherein the method step of providing target performance properties is preceded by the steps providing an identifier of a specific oil or a specific mixture of oils and/or a specific surfactant or a specific further component or a specific mixture of surfactant and the further component, deriving the target performance of the specific oil or the specific mixture of oils properties and/or of the specific surfactant or the specific further component or the specific mixture of surfactant and the further component from the identifier of the specific oil or the specific mixture of oils and/or of the specific surfactant or the specific further component or the specific mixture of surfactant and the further component.

10. The method according to claim 8, wherein the method further comprises the step of comparing by the processing device the target performance properties of a specific oil or a mixture of oils and/or a specific surfactant or a specific further component or a specific mixture of surfactant and the further component for cosmetics with the determined performance properties of the oil-containing and/or the surfactant-containing product for cosmetics and deriving a result of the comparing step, wherein the step of comparing comprises comparing if the target performance requirements are met, wherein providing via the output channel further comprises providing the result of the comparing step.

11. The method of claim 10, further comprising the step of varying the composition parameters, further comprising the step of providing the varied composition parameters as composition parameters.

12. The method of claim 11, further comprising the step of repeating the method, until the target performance properties are met.

13. The method of claim 11, wherein the step of varying the composition parameter comprises varying the measure for the ratio of the different oils and/or the surfactant or the further component and/or, wherein step of varying the composition parameter comprises changing at least one identifier of the different oils and/or the surfactant or the further component and or comprises adding an additional identifier of an oil and/or of a surfactant or of a further component.

14. The method of claim 8, wherein the target performance properties of a specific oil or a mixture of oils for cosmetics relate to a silicone-based oil or a mineral/paraffin oil.

15. The method of claim 8, wherein the target performance properties of a specific surfactant or a specific further component or a mixture of surfactant and further component relate to alkoxylate and sulfate based surfactants.

16. A system (12) for determining performance properties of an oil-containing and/or surfactant-containing product for cosmetics, the oil-containing product for cosmetics comprising different oils forming a mixture and/or the surfactant-containing product for cosmetics comprises at least one surfactant and further component forming the mixture, the system (12) comprising: a communication interface (18), and a processing device (16) configured to perform the method according to claim 1.

17. A computer program product that, when run on a processing device performs the method according to claim 1.

18. A method for determining performance properties of an oil-containing and/or a surfactant-containing product for cosmetics comprising the use of a system according to claim 16 for production of an oil containing product and/or of a surfactant-containing product for cosmetics.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0222] As example, embodiments of the present invention are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only particular aspects of the present invention and are therefore not to be considered limiting of its scope. The present invention may encompass other equally effective embodiments.

[0223] FIG. 1 illustrates an example method/flow-chart for determining the performance properties of an oil-containing product.

[0224] FIG. 2 shows an example of a conceptual device for determining performance property of an oil-containing product.

[0225] FIG. 3 illustrates how an example performance property, Surface Tension (SFT), for a binary oil mixture, varies with mixing ratio. SFT for the mixture is predicted using a data-driven model.

[0226] FIG. 4: illustrates that for several oil mixtures and for four different performance properties, the estimates obtained by the corresponding data driven (linear) models agrees excellently with their corresponding experimental values.

[0227] FIG. 5: a) depicts the sub-linear, behavior of a binary mixture of oils in terms of its viscosity. b) illustrates that a data driven model (log-log) is able to predict accurately the viscosities of several oil mixtures.

[0228] FIG. 6: Illustrates the detailed workflow of the present invention giving the performance of the optimized oil mixture, names of the mixture constituents, and mixing ratio that matches best to a target oil or an oil mixture or any performance profile.

[0229] FIG. 7: Shows the comparison between the performance profiles of Cyclomethicone and an optimized oil mixture derived from the method outlined in this invention.

[0230] FIG. 8: Shows an embodiment of a system or determining performance properties of an oil-containing and/or surfactant-containing product for cosmetics.

DETAILED DESCRIPTION

[0231] The present disclosure provides a method for determining performance properties of an oil-containing product for cosmetics, the oil-containing product for cosmetics comprising different oils forming a mixture.

[0232] FIG. 1 shows an example the disclosed method in form of a simplified flow chart. In this example determining performance properties of a mixture of two different oils is described. The first of the different oils is dicaprylyl ether (Cetiol® OE) The second of the different oils is coco-caprylate/caprate (Cetiol® LC).

[0233] At step 100 composition parameters are provided via a communication interface to a processing device. In this example the composition parameters comprise an identifier for each of the different oils and a step of deriving performance properties for each of the oils from the identifier is performed. In cases where the performance parameters are derived from the identifier, the derived performance parameters are also provided as composition parameters. The identifier in this example are the brand names of each of the oils. In this example the brand names of are entered via a keyboard.

[0234] Other means for providing the identifier of each of the oils are also possible, for example providing the identifier of each of the oils from a database.

[0235] In this embodiment the performance properties for each of the oils are derived from a database.

[0236] Additionally, or alternatively, the method may comprise a step of selecting one or more of the performance properties of each of the different oils. This allows reducing the number of performance properties of each of the oils to the performance properties that are relevant for the task. This reduces computational power.

[0237] In this example, the performance properties for each oil is a single physico-chemical performance property. More specifically, the performance properties for each oil is the surface tension (SFT), see table below.

TABLE-US-00001 TABLE 1 mixture Mixture perfor- perfor- Perfor- Oil.sub.1 Oil.sub.2 mance mance mance (Cetiol (Cetiol x.sub.1 x.sub.2 property property property OE) LC) [%] [%] (determined) (measured) SFT 27.26 29.80 25 75 29.16 29.00 (mN/m)

[0238] The composition parameters in this example further comprise, a measure for the ratio of the different oils. In this is example, the measure for the mixing ratio of the first of the different oils is entered by a keyboard.

[0239] In other examples the measure for the mixing ratio of the oils may be derived from an identifier of a mixture of oils containing these oils.

[0240] In this example the measure for the mixing ratio of the second oil is derived from the measure for the mixing ratio of the first of the different oils. In other cases, the measure for mixing ratio for each of the different oils may be provided for each oil separately.

[0241] In this example at step 200 a data driven model is provided via the communication interface to the processing device. In this example, the data driven model is a linear mixing model. On other examples data driven model may be a log-log model. In other examples other data driven models e.g. as mentioned above may be provided.

[0242] At step 300 with a processing device determined performance properties of the oil-containing product for cosmetics comprising the mixture are determined with the processing device, based on the data driven model and/or the rigorous model and the composition parameters.

[0243] The linear model in this example can be described by SFT(mixture.sub.2)=Σ.sub.1.sup.2SFT(oil.sub.i).Math.x.sub.1. The data driven model in this example was derived by linear regression on measurements of different ratios. Index 2 indicates that the mixture comprises two different oils. The term x.sub.i. relates to the relative portion of oil; in the mixture in percent.

[0244] When the performance properties comprise more than one performance property for each of the different oils the performance of each oil may be provided as a vector {right arrow over (prop)}(oil.sub.i) for oil i. For the example given in table 2, the properties are SFT, RI, spreading value and density. And the mixing ratio x.sub.1 is 25% and x.sub.2=100−25=75%.

TABLE-US-00002 TABLE 2 Oil.sub.1 Oil.sub.2 Performance Performance Performance (Cetiol (Cetiol properties properties property OE) LC) x.sub.1 determined measured SFT (mN/m) 27.26 29.80 25 29.16 RI 1.433 1.445 25 1.442 1.442 Spreading value 1607 557 25 819 729 (mm.sup.2/10 min) Density (gm/cm.sup.3) 0.805 0.856 25 0.8432 0.8427

[0245] The performance property vector for the example in table 2 would therefore look like

[00001]$\stackrel{.Math.}{\mathrm{prop}}=\left(\begin{array}{c}\mathrm{SFT}\\ \mathrm{RI}\\ \mathrm{spreading}\mathrm{value}\\ \mathrm{density}\end{array}\right)$

[0246] For a mixture of two oils the step of determination of the determined properties of the mixture could be described in a general way as:

{right arrow over (prop)}(mixture.sub.ij)=ƒ{{right arrow over (prop)}(oil.sub.i),{right arrow over (prop)}(oil.sub.j),x.sub.ij}

[0247] with x.sub.ij: mixing ratio of the two different oils and {right arrow over (prop)}(oil.sub.i): the vector with performance properties of oil/and {right arrow over (prop)}(mixture.sub.ij): the vector with performance properties of the oil mixture. The function f is the mathematical description of the data driven model.

[0248] An example of a linear data driven model for a multitude of n oils is described by the formula below.

[00002]$\stackrel{.Math.}{\mathrm{prop}}\left({\mathrm{mixture}}_{\mathrm{ij.Math.}n}\right)=\underset{i}{\overset{n}{.Math.}}\stackrel{.Math.}{\mathrm{prop}}\left({\mathrm{oil}}_i\right).Math.x_i$

[0249] At step 400 providing via a communication interface, the determined performance properties of the oil-containing product for cosmetics is performed. In this example the performance properties of the oil-containing product for cosmetics are provided to a display.

[0250] Providing to the display has the advantage that the information is readily available for a user.

[0251] In other examples the communication interface may provide the determined performance properties of the oil-containing product for cosmetics to a database. Providing to a database has the advantage, that the information can later be retrieved and may be available for later use.

[0252] In a further example, the communication interface may provide the determined performance properties of the oil-containing product for cosmetics to a database and a display simultaneously.

[0253] Providing to the database and the display simultaneously has the advantage, that the information can later be retrieved and may be available for later use and is also readily available to the user.

[0254] The method may within the scope of the invention be extended to three, four, or more than four different oils.

[0255] In an alternative, the performance property may be any of the physico-chemical properties, or any of the sensory properties. In a further alternative the performance property may comprise more than one performance property for each of the different oils.

[0256] In FIG. 2 an example of a system 1000 for determining the performance properties of an oil-containing product, in particular for personal care, more particular for cosmetics is shown.

[0257] The system is configured for performing the method steps 100 to 400 described above in context with FIG. 1. FIG. 2 focuses on illustrating the conceptual device in this invention.

[0258] In this embodiment the system comprises a communication interface 1100 for providing composition parameters to a processing device 1200, and for providing a data driven model and/or a rigorous model to the processing device.

[0259] The system further comprises a physical input device 1300 connected to the communication channel. In this example the physical input device is a keyboard.

[0260] In other embodiments the performance properties for each of the different oils may be provided by the physical input device. This allows the use of the system for determination of performance properties of the oil-containing product for cosmetics even when the performance properties for each of the different oils are not available for all of the different oils. This can increase flexibility of the system.

[0261] The system further comprises a logical input device 1400. The logical input device in this case is a database in which performance properties for different oils and/or mixtures of oil are stored.

[0262] In this example, the measure for the ratio of the different oils in the mixture is provided as a composition parameter to the communication interface 1100 via database 1400.

[0263] In other examples the measure for the ratio of the different oils in the mixture may be provided as composition parameters to the communication interface by entering into keyboard 1300.

[0264] In this example, the data driven model and/or a rigorous model is provided to the communication interface 1100 via database 1400.

[0265] The system further comprises an output device 1500. The communication interface provides the determined performance properties of the oil-containing product for personal care and/or the measure for the ratio of the different oils in the mixture and/or a formulation of the mixture, and or a formulation of the oil-containing product for cosmetics to the output device. In this example the output device is a display. A formulation of the oil containing product may contain additives such as e.g. water, preservatives, emulsifiers.

[0266] In a further example the output device may be a database. In yet another example, the output device may be a combination of a display and a database.

[0267] The processing device 1200 is configured to perform the steps outlined in context with the method described in FIG. 1.

[0268] FIG. 3 shows a plot of the determined performance properties of an oil-containing product, in particular for personal care, more particular for cosmetics, the oil-containing product for personal care comprising different oils forming a mixture, for various measures for the ratio of the different oils in the mixture. The X-axis refers to the ratio of oil, in the mixture. Oil in this example is Cetiol OE, the second oil in this example is Cetiol LC. The determined performance property is SFT. It can be seen, that there is a is a linear relationship between the measure for the ratio of the different oils in the mixture and the determined performance property. Some measured performance properties are also shown provided at selected mixing ratios. Examples of determined and measured values for different mixing ratios are shown in table 3.

TABLE-US-00003 TABLE 3 x.sub.1 Oil.sub.1 x.sub.2 Oil.sub.2 SFT determined SFT measured (Cetiol OE) in % (Cetiol LC) (mN/m) (mN/m) 100 0 27.26 27.26 90 10 27.514 75 25 27.90 27.23 60 40 28.276 50 50 28.53 28.28 40 60 28.784 25 75 29.16 29.00 10 90 29.546 0 100 29.8

[0269] FIGS. 4 a-d show examples of physico-chemical properties where the determined performance property can be determined based on a data driven model. In these cases, the data driven model is a simple linear model. Each data point relates to a ratio of different oil mixtures with varying chemistries. The data driven model accurately captures the performance for several mixtures.

[0270] FIGS. 5 a)-b) show that non-linear data driven models may also occur. In this example the viscosity of dicaprylyl ether (Cetiol® OE) and caprylic/capric triglyceride (Myritol® 318) have been provided as the performance property. FIG. 5 a) shows the plot of a measured viscosity of the mixture of dicaprylyl ether (Cetiol® OE) and caprylic/capric triglyceride (Myritol® 318) at various ratios. It can be clearly seen that the viscosity of the mixture does not change linear with the ratio between the two oils, but rather follows a sublinear log-log behavior. Also shown is a fit to the derived data-driven model, which is a log-log model. FIG. 5b) shows the behavior of the log-log model in comparison to the experimentally measured viscosity of several oil mixtures with different chemistries. The model fitting viscosities of oil mixture is of the following form:

loglog[{right arrow over (prop)}(mix.sub.ij . . . n)]=loglog[{right arrow over (prop)}(oil.sub.i)].Math.x.sub.i

[0271] FIG. 6 shows a flowchart of a further aspect. In this example an alternative use of the method for determining performance properties of an oil-containing product for cosmetics is disclosed the oil-containing product for cosmetics comprising different oils forming a mixture.

[0272] At step 750 target performance properties of an oil or a mixture of oils for cosmetic are provided to the processing device via the communication channel. In this example the step of providing to the processing device via the communication channel target performance properties of an oil or a mixture of oils for cosmetics is preceded by the step 770 of providing an identifier of the specific oil or the specific mixture of oils, and step 800 deriving target performance properties from the identifier of the specific oil or the specific mixture of oils. In this example the method is applied to only one specific oil. The identifier of the specific oil in this example is cyclopentasiloxane/cyclomethicone. The task which this flowchart is describing is to identify new oil mixtures and their ratios that matches the properties of the specific/target oil, cyclomethicone.

[0273] The target performance properties used in this example include: viscosity, spreadability, density, RI, IFT, SFT as physical properties and include: thickness, gloss, powdery feel, silicone feel, wetness, distribution, thickness, rubs to absorbency, oil, grease amount of residue, dryness, gloss, slipperiness, smoothness, thickness of residue, greasy feel %, oily feel %, powdery feel %, silicone feel, slipperiness, and stickiness as sensory properties. In other examples the target performance properties may only be one physical property or one sensory property or any combination of physical and/or sensory properties. The target performance properties are derived from the database.

[0274] In this example at step 2200 a data driven model is provided via a communication interface to a processing device. In this example, providing a data driven model comprises providing a data driven model for each performance property.

[0275] At step 2100 composition parameters are provided via the communication interface to the processing device. In this example the composition parameters comprise an identifier for each of the different oils and a step of deriving performance properties for each of the oils from the identifier is performed.

[0276] In cases where the performance parameters are derived from the identifier, the derived performance parameters are also provided as composition parameters. The identifier in this example are the brand names of each of the oils. In this example the brand names were selected from a list of oils in a database. Other means of providing the identifiers are also possible, for example providing the identifier of each of the oils via a keyboard.

[0277] Providing the identifiers via a database is in particular useful, if the method is automized.

[0278] The identifiers in this example were based on a binary system of oils. In other examples tertiary and quarterly systems are also possible. In principle, there is no upper limit for the number of different oils. The binary system of oils in this example comprises Cetiol C5 and Cetiol Ultimate, both of which are trademarks of BASF.

[0279] In this example the performance parameters for each of the different oils are derived from the identifier. In this embodiment the performance properties for each of the oils are derived from a database. The derived performance parameters are also provided as composition parameters.

[0280] Consequently, the performance properties of Cetiol C5 and Cetiol Ultimate are also provided as composition parameters. In this example, the performance properties that are provided comprise viscosity, spreadability, density, RI, IFT, SFT as physical properties and include: thickness, gloss, powdery feel, silicone feel, wetness, distribution, thickness, rubs to absorbency, oil, grease amount of residue, dryness, gloss, slipperiness, smoothness, thickness of residue, greasy feel %, oily feel %, powdery feel %, silicone feel, slipperiness, and stickiness as sensory properties. In this case the provided performance properties are identical to the target performance properties. This allows to best meet the target performance properties. In other examples only a subset of target performance properties may be provided as performance properties of each of the oils.

[0281] Additionally, or alternatively, the method may comprise a step of selecting one or more of the performance properties of each of the oils. This allows reducing the number of performance properties of each of the oils to the performance properties that are relevant for the task. This reduces computational power.

[0282] In this example the composition parameters also comprise a measure for the ratio of the different oils in the mixture. In this is example, the mixing ratio is fixed and reflects an initialization value.

[0283] In other examples, the measure for the mixing ratio of the first of the different oils may be entered by a keyboard and the measure for the mixing ratio of the second oil is derived from the measure for the mixing ratio of the first of the different oils.

[0284] In other cases, the measure for mixing ratio for each of the different oils may be provided for each of the oils separately.

[0285] In this example, the measure for the mixing ratio of the first of the different oils is x.sub.1=1.

[0286] At step 2300 the performance properties of the oil containing product for cosmetics comprising the mixture are determined with the processing device, determining with a processing device determined performance properties of the oil-containing product for cosmetics, based on the data driven model, the performance properties for each of the different oils, the measure for the ratio of the different oils in the mixture.

[0287] At step 2400 the target performance properties of a specific oil or a mixture of oils for cosmetics are compared with the determined performance properties of the oil-containing product for cosmetics. A result of the comparing step is generated.

[0288] In this example, comparing the target performance properties of a specific oil or a mixture of oils for cosmetics with the determined performance properties of the oil-containing product for cosmetics includes calculating a value of an error function, according to

[00003]$\mathrm{erf}\left(\mathrm{ij},{\mathrm{oil}}_R\right)=\underset{\mathrm{prop}}{.Math.}{.Math.\stackrel{.Math.}{\mathrm{prop}}\left({\mathrm{oil}}_R\right)-\stackrel{.Math.}{\mathrm{prop}}\left({\mathrm{oil}}_{{\mathrm{mixture}}_{\mathrm{ij}}}\right).Math.}^2,$

[0289] wherein i, j are indices related to different oils, {right arrow over (prop)}(oil.sub.R) relates to the target properties of the selected oil or mixture of oils and {right arrow over (prop)}(oil.sub.mixture.sub.ij) relates to the determined performance properties of the mixture of oils. The result of the comparing step in this example is the value of the error function. In other cases, the result may be a binary value reflecting, whether the target performance properties are matched.

[0290] At step 2500 the composition parameters of the mixture of oils are varied. This composition parameter may be the measure for the ratio of the different oils in the mixture. In this example, the step of varying the composition parameter comprises varying the measure for the ratio of the different oils. In this example the varying step is repeated until the performance requirements are met. In this example meeting the performance requirements relates to minimizing the error function described above.

[0291] The result of the comparison step may be provided via the communication interface. This may result in providing a table shown below.

TABLE-US-00004 Oil.sub.i Oil.sub.j X.sub.opt (oil.sub.i ratio) Erf * Cetiol C5 Cetiol Ultimate 0.75 0.58

[0292] In this example, the step varying the composition parameters further comprises changing at least one identifier of the different oils.

[0293] In this example, the at least one identifier of the different oils that is changed is the brand name of Cetiol Ultimate. In this example the identifier is changed to Cetiol RLF.

[0294] The varied composition parameters are then provided as composition parameters.

[0295] By this an iterative optimization process is enabled.

[0296] Finally, in the table below, for the target silicone oil, Cyclomethicone, the corresponding mixing ratios for four example binary mixtures and the values of the optimized error function computed through the routine outlined in FIG. 6 are shown. This table was derived by iteratively changing the identifier of oil.sub.j, and providing a result of the comparison step together with the minimum of the error function.

TABLE-US-00005 Oil.sub.i Oil.sub.j X.sub.opt (oil.sub.i ratio) Erf * Cetiol C5 Cetiol Ultimate 0.75 0.58 Cetiol C5 Cetiol RLF 0.45 0.66 Cetiol C5 Cetiol A 0.50 0.71 Cetiol C5 Cetiol Sensoft 0.15 0.71

[0297] FIG. 7 illustrates an example match between the performance profile of a mixture {right arrow over (prop)}(mixture.sub.ij) and that of a example target silicone-oil, {right arrow over (prop)}(Cyclomethicone), using the method outlined in FIG. 6.

[0298] At step 500, the final determined performance properties of the oil-containing product for personal care may be provided via the communication interface.

[0299] In this example, along with the performance properties of the oil-containing product for personal care, the constituent oils (names) and mixing ratio are provided to a display.

[0300] FIG. 8 shows an embodiment of a system 12, in particular an internet-based system 12, for determining performance properties of an oil-containing and/or surfactant-containing product for cosmetics. The Internet-based system 12 may comprise a server 14, e.g. comprising a processing device 16, which can be accessed via the communication interface 18 such as a network 20, such as the Internet, by one or more client devices 10. The client devices 10 may be computer terminals accessible by a user and may be customized devices, such as data entry kiosks, or general purpose devices, such as a personal computer. Preferably, the server 14 is an HTTP server and is accessed via conventional Internet web-based technology. The server 14 may be connected to a further client device 10 and, either directly or indirectly through the network, to a manufacturing facility 22. The server 14 may be configured to trigger a request of initiating the method for determining performance properties of an oil-containing and/or surfactant-containing product for cosmetics. The manufacturing facility 22 can be located proximate to the server 14 and be part of an overall customized ordering and manufacturing system. Alternatively, manufacturing facility 22 may be remotely located from both the server 14 and the client devices 10. For example, the performance properties of an oil-containing and/or surfactant-containing product for cosmetics can be forwarded directly, such as via e-mail, to the manufacturing facility 22. In yet a further embodiment the manufacturing facility 22 can be located proximate a client device 10. This arrangement is particularly well suited for a kiosk-based on-demand manufacturing system, e.g., such as may be located in a point-of-sale establishment. These three potential connections to the manufacturing facility 22 are illustrated in FIG. 8. Multiple manufacturing facilities 22 located at different places may be provided or only one connection may be implemented.