• 专利附录
  • 专利说明
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    • 专利摘要:
    The process may include mixing ingredients into a cocoa mass, conching the cocoa mass and, after conching, measuring the viscosity of the conched cocoa mass, depending on whether said viscosity is greater than a value of target viscosity, the calculation, on the basis of the measured viscosity and the reference data representing a reference model of viscosity with respect to the content of the viscosity reducing substance for the chocolate to be produced, from an amount of cocoa butter to add to the cocoa mass, and adding the amount of cocoa butter to add to the cocoa mass.
    公开号:CH716749A2
    申请号:CH01335/20
    申请日:2020-10-16
    公开日:2021-04-30
    发明作者:Leclerc Jean-Philippe
    申请人:Jean Philippe Leclerc；
    IPC主号:
    专利说明:

    Context
    Chocolate is an increasingly popular product and production in America and Europe alone was estimated to be over 5 million tonnes in 2016. Most industrial chocolate production processes involve a sequence of steps include mixing, grinding, conching and generally tempering and molding or shaping, but some chocolate products are sold or transported in liquid form. While there are different types of chocolates and specific recipes depend on the type of chocolate, conching is known to significantly affect the quality of chocolate and helps improve the taste and smoothness of the finished product. Conching involves the creation of sustained mechanical stresses and heat in the cocoa mass, which helps to disaggregate the cocoa mass and eliminate unwanted aromas. Higher quality products generally involve longer conching times than lower quality products. At the end of conching, emulsifiers can be added, depending on the recipe. Even if the existing chocolate production processes were satisfactory to a certain extent, there is still room for improvement. In particular, there is always a motivation to cut costs while continuing to meet or exceed specifications.
    summary
    [0002] It is relatively common for chocolate production specifications to include a maximum viscosity specification for chocolate. The maximum viscosity specification may depend on the usage of the chocolate, since, for example, chocolates which are intended to be used for chocolate coatings may require a relatively low viscosity to properly perform the coating function. However, even where there are no specific external viscosity requirements, as in the case of the production of chocolate chips for example, the chocolate mass typically still has to be processable by the equipment available, which may become difficult above a certain viscosity level, and the viscosity level above which processing is deemed difficult may be set as a maximum viscosity specification, for example.
    [0003] The percentage of fat in the recipe affects the viscosity of the chocolate mass, and the percentage of fat depends on the total amount of fat contained in the raw ingredients which are initially added together and mixed. Substances other than fatty substances can also have an effect on viscosity, such as emulsifiers (eg lecithin, PGPR), for example. For greater clarity in the following description, all of these ingredients, or the mixture of these ingredients, the content of which has an effect on the viscosity, will be referred to herein as “viscosity reducing substance”. In addition, conching in particular, and certain other process variables, can also affect the viscosity of the chocolate mass. For this reason, it may be desirable to add a little more fat (for example one or more ingredients containing fat such as cocoa butter, cocoa liquor, butter oil or even powdered milk. ), an emulsifier and / or other viscosity reducing substance, in the mixing step to ensure that the maximum viscosity specification will be met later in the process. However, using this approach, and due to process variations, the final viscosity sometimes ends up being significantly below the maximum cut-off value, by an amount that could fluctuate at the lot level. Now, even if this method systematically achieves the objective, it can repeatedly lead to exceeding the required minimum quantity of viscosity reducing substance. Cocoa butter, a typical example of a viscosity reducing substance, is a relatively expensive ingredient in the production of chocolate, and the amount of cocoa butter contained in the cocoa mass corresponds to the extent to which the viscosity specification has been. exceeded (reaching a viscosity lower than required) can be a waste of valuable resources. It will be understood that a viscosity reducing substance can also include ingredients which do not reduce viscosity, as long as it exhibits some degree of viscosity reduction.
    [0004] To avoid exceeding the viscosity specification (that is to say, wasting the viscosity reducing substance), it may on the contrary be preferable to limit the amount of viscosity reducing substance included in the starting ingredients, while keeping open the possibility of adding a quantity of viscosity reducing substance as the final stages of the process approach, such as during the conching stage. For example, one can concher until the chocolate mass has stabilized, measure the viscosity, and, if the viscosity threshold has not been reached, add a quantity of substance containing fat and carry out an additional step of conching. The latter approach can avoid or reduce the amount of fat used, while still respecting the minimum viscosity threshold, at the cost of additional conching time.
    [0005] According to one aspect, there is provided a process for the production of chocolate comprising the mixing of ingredients in a cocoa mass, the refining of the cocoa mass and the conching of the cocoa mass and, after conching, the conching. measuring the viscosity of the conched cocoa mass, depending on whether said viscosity is greater than a target viscosity value, the calculation, on the basis of the measured viscosity and the reference data representing a reference model of viscosity with respect to the content of viscosity reducing substance for the chocolate to be produced, of an amount of viscosity reducing substance to be added to the cocoa mass, and adding the amount of viscosity reducing substance to be added to the cocoa mass.
    [0006] According to another aspect, there is provided a chocolate production line in which a computer determines an amount of viscosity reducing substance to be added to the cocoa mass between conching and shaping, on the basis of the measured viscosity and reference data representing a reference model of viscosity versus viscosity reducing substance content. Viscosity can be measured by sucking the cocoa mass from and to the conch, along a recirculation loop where a viscometer is present, for example.
    [0007] During the additional conching time, the equipment is not free to receive the next batch, and the next batch can therefore be considered as delayed. The same question can be raised when choosing the amount of viscosity reducing substance to add after the first conching phase, or after a subsequent conching phase: if the amount is less than what is required, yet another addition of viscosity reducing substance and further conching phase will be required before reaching the minimum viscosity threshold, which will also cause additional production time and further delay the next batch. Such a longer production time can also be equated with additional costs, and the operator must then choose between saving the viscosity reducing substance, speeding up the production time and finding a balance between the two, given the specifics of the production. exact implementation.
    [0008] From now on, according to one aspect, there is provided a method of adding a quantity of viscosity reducing substance after a given conching phase, the method including measuring the viscosity of the chocolate mass after the phase of given conching, determining an amount of viscosity reducing substance to be added, adding the determined amount of viscosity reducing substance, and performing a subsequent conching step, wherein said determining the amount of substance viscosity reducing agent includes determining a difference between the measured viscosity and a target viscosity value, associating the difference with a base amount of viscosity reducing substance to be added based on a reference model, associated quantity having a margin of error, and selecting, for the quantity of viscosity reducing substance to be added, a value different from the base value, but within the margin of error.
    [0009] Regardless of the operator's preference for a given implementation (i.e. whether it is preferable to save the viscosity reducing substance, to speed up production time or to achieve a balance between the first two considerations), it may be preferable to obtain an estimate, or forecast, of the fat content required to reach the viscosity threshold that is as precise as possible, as this will reduce or reduce avoiding either or both of i) an undesirable excessive amount of viscosity reducing substance and ii) additional production time. The subject of improving the accuracy of the forecast is quite broad, and will be explored in more detail below, as various methods can produce reference models relating an amount of fat to a viscosity or to a change in viscosity. . Such a reference model will generally have a certain margin of error. However, in some cases the margin of error may be known in absolute terms or with some degree of confidence. The reference model can be specific to a given recipe, or more general, such as for example the use of the same reference model for different recipes of the same type of chocolate. As noted above, one will likely be prompted to use a reference model which is most likely to be accurate in the light of the circumstances, and therefore for which the margin of error is the smallest, if more than one reference model is available.
    [0010] It was found that many reference models had margins of error which could be improved / reduced according to the actual measured values resulting from previous iterations of the same recipe on the same equipment. Accordingly, according to another aspect, there is provided a process for producing a plurality of batches of a given chocolate recipe, wherein for each batch an initial amount of viscosity reducing substance and / or an amount added subsequently. of viscosity reducing substance are determined on the basis of a reference model associated with the recipe, and in which the reference model is modified or updated between a previous batch and a following batch on the basis of one or more viscosity measurements made during the preparation of the previous batch.
    According to another embodiment, there is provided a method for producing chocolate comprising: producing a first batch of chocolate including mixing an initial recipe of ingredients in a cocoa mass, conching of the cocoa mass and, after at least one phase of said conching, measuring the viscosity of the conched cocoa mass, depending on whether said viscosity value is less than a target viscosity value, reducing an amount of reducing substance of viscosity specified in the recipe for starting ingredients, and producing a second batch of chocolate including mixing the recipe with starting ingredients having a reduced amount of viscosity reducing substance in a cocoa mass and conching cocoa mass.
    It will be understood that the expression "computer", a generic example of which is presented in FIG. 8, as used here, should not be interpreted in a limiting manner. Rather, it is used in a broad sense to generally refer to the combination of some form of one or more processing units and some form of memory system accessible by the one or more processing units. The memory system can be of the non-transient type. The use of the term “computer” in the singular as used herein includes within its scope the combination of two or more computers working together to perform a given function. In addition, the term "computer" as used herein includes within its scope the use of partial capacities of a given processing unit.
    A processing unit can be in the form of a microprocessor or a general-purpose microcontroller, a digital signal processing processor (DSP), an integrated circuit, a network of programmable doors on site (FPGA), a reconfigurable processor, a programmable read-only memory (PROM), programmable logic controller (PLC) to name but a few examples.
    The memory system may include an appropriate combination of any suitable type of computer readable memory located either internally or externally, and accessible by the processor wired or wirelessly, either directly or over a network such than the Internet. Computer readable memory can take the form of random access memory (RAM), read only memory (ROM), compact disc read only memory (CDROM), electro-optical memory, Magneto-optical memory, erasable programmable read-only memory (EPROM) and electrically erasable programmable read-only memory (EEPROM), ferroelectric RAM (FRAM) to name but a few examples.
    [0015] A computer can have one or more input / output (I / O) interfaces to allow communication with a human user and / or with another computer via an input, output or input / device. associated output such as keyboard, mouse, touch screen, antenna, port, etc. Each I / O interface can allow the computer to communicate and / or exchange data with other components, to access and connect to network resources, to serve applications and / or to run other computer applications by connecting to a network (or multiple networks) capable of carrying data, including the Internet, Ethernet, Classic Telephone Service Line (POTS), Public Switched Telephone Network (PSTN), integrated services digital network (ISDN), digital subscriber line (DSL), coaxial cable, fiber optic, satellite, mobile, wireless (e.g. Wi-Fi, Bluetooth, WiMAX), SS7 signaling network, landline, local network, wide area network, to name a few examples.
    It will be understood that a computer can perform functions or processes through hardware or a combination of hardware and software. For example, the hardware can include logic gates embedded in a silicon chip of a processor. The software (eg application, process) may be in the form of data such as computer readable instructions stored in non-transient computer readable memory accessible by one or more processing units. With respect to a computer or processing unit, the term “configured for” refers to the presence of hardware or a combination of hardware and software that is usable to perform associated functions. The processor, the controller, the memory can all be local, or one or more of these can be partly or entirely remote, distributed or virtual.
    Many other characteristics and combinations thereof relating to the present improvements will become apparent to those skilled in the art after reading the present disclosure.
    Description of figures
    In the figures,
    Figure 1 is a schematic view of a chocolate production line; Fig. 2 is a graph illustrating a reference model specifying a margin of error; Fig. 3A is a graph illustrating a first example of a diagram for calculating an amount of viscosity reducing substance to be added; Fig. 3B is a graph illustrating a second example diagram for calculating an amount of viscosity reducing substance to be added; Fig. 4 is a flowchart showing a viscosity correction process between conching and shaping; Fig. 5 is a graph illustrating how an amount of cocoa butter to be added can be calculated using reference data; Figure 6 is a flowchart showing a process similar to Figure 4, but in which one or both of the amount of fat containing ingredient to be added and benchmark data itself can be adjusted. depending on the presence of a difference between the measured viscosity and the known fat content, and the corresponding reference values in the reference data; Figure 7 shows three examples of curve fitting based on three points of actual batch data; and Figure 8 is a schematic view of a generic computer.
    detailed description
    Figure 1 shows an example of a chocolate production line 2. In this production line, a mixer 4 is provided which receives the starting ingredients of a specific chocolate recipe, these ingredients may include quantities specific chocolate liquor, cocoa butter, powdered milk and / or sugar for example, as is known in the art. Due to the variability inherent in the later stages of the process, and in conching step 6 in particular, there is inherent variability in the fat content which will lead to a specific viscosity value (usually provided as a minimum viscosity threshold). The relationship between viscosity and fat content is typically at least globally of the inversely proportional type, as shown schematically in Figure 2, and a relationship established for a given recipe may be referred to as Reference Model 8. For example, as shown in Figure 2. FIG. 2, the reference model 8 can associate a base fat content Q1 with the target viscosity Vt, but this base fat content Q1 can be known to typically lead to a certain variability of the viscosity values, to typically between V1 and V2, due to the margin of error 10. If the final result is V1, the target viscosity Vt will not have been reached during the first conching phase. If the final result is V2, the target viscosity Vt will have been exceeded and the fat-containing substance will therefore have been wasted. In light of this process variability, the fat content (i.e. the amount of fat-containing substance) in the ingredients initially added to Mixer 4 can be intentionally chosen to be lower, or higher. , to the basic fat content Q1. Indeed, one may prefer to select a minimum quantity Q2, which will certainly avoid wasting fat; a maximum quantity Q3, which will certainly avoid a subsequent conching phase, or a balance between these two extreme considerations.
    Returning to Figure 1, after mixing the ingredients initially supplied in the mixer 4, the mixer 4 feeds a pre-refiner 12 where a level of grinding is performed, and from there, the chocolate mass is conveyed to a refiner 14, where a finer level of grinding is carried out. The chocolate mass is then conveyed from the refiner 14 to the conch 16, where the conching step 6 is carried out. As will be seen later, in this example, a viscometer 18 is placed in a recirculation loop 20 associated with the conch 16 and comprising a pump 22, and can be used to measure the viscosity of the cocoa mass as soon as a or several phases of the conching step 6 are carried out. The viscosity can then be adjusted by adding an amount of viscosity reducing substance to the conch 16. The addition of a viscosity reducing substance supplied to the conch 16 from a viscosity reducing substance reservoir 24 can be metered. with a dosing system 26, for example. The amount of fat to be added can be calculated using a computer 28, based on the measured viscosity value, the target viscosity value, the amount of fat already present in the cocoa mass , and on a reference model, and be translated by the computer 28 into an amount of fat / substance containing fat to be added.
    This last sequence of steps is perhaps best illustrated in Figures 3A and 3B, both of which show an example scenario in which it is known that an initial fat content Q1 was initially included in the ingredients. starting mixed and directed to the first phase of conching, and in which the viscosity was measured after the first phase of conching, and determined to correspond to the measured viscosity Vm. The process can be automated, so that a computer 28 (Figure 1) can automatically perform a comparison between the measured viscosity Vm and the target viscosity specification Vt. After determining that the target viscosity specification Vt has not been reached, computer 28 can conclude and indicate that an addition of fat is necessary. The question becomes: how much added fat is needed Again, a reference model can be used to relate a fat-containing substance addition amount to a viscosity reduction value. Again, due to the variability inherent in the conching process, a margin of error may exist. The margin of error may be significantly less than the initial margin of error (eg, margin of error 10 in Figure 2), but still be significant.
    FIG. 3A perhaps represents a relatively simple diagram. After the first conching phase based on a known quantity of fat Q1, the viscosity measurement Vm indicates that the viscosity is always greater than the target viscosity Vt (or viscosity threshold). In an "aggressive" scheme, an amount of fat Q4 determined to ensure that the target viscosity Vt is reached using the initial reference model 8 can be determined, and an amount of viscosity reducing substance corresponding to the difference between Q4 and Q1 fat content can be added. This may lead to wastage of the viscosity reducing substance, but the amount of viscosity reducing substance wasted would probably have been less than that found if a larger amount Q1 had been initially introduced into the mixture based on an aggressive pattern. “Similar.
    In practice, the margin of error may, for example, be somewhat proportional to the difference between the measured viscosity Vm and the target viscosity Vt. As a result, a new reference model having a lower margin of error can be established by updating the initial reference model with the additional information of the measured viscosity Vm, and focusing on the remaining unknowns, such a diagram is shown in Figure 3B. Here, the updated Reference Model 30 can provide a base value of the fat content Q5, the difference of which, with the current value of the fat content Q1, can be determined to correspond to a decrease in viscosity. making it possible to precisely reach the target viscosity value Vt. However, taking into account the margin of error 32, adding the base value of the added fat content (Q5 minus Q1) may lead to an actual measured viscosity value, which may be higher or lower than the target viscosity value Vt, after the second conching phase. The margin of error 32 can extend, with a certain degree of confidence, between a maximum quantity Q6 and a minimum quantity Q7, to reach a given target viscosity Vt. Here too, an operator may prefer to concentrate on a minimum amount of added fat, introducing an amount corresponding to the Q7-Q1 value to achieve a total fat content lower than the base value of Q5 fat content. , and corresponding to a minimum fat content Q7, ensuring that no substance containing fat is wasted. Alternatively, the operator may prefer to introduce a maximum amount of added fat content value of Q6-Q1 to ensure that the added fat content will achieve the target viscosity value Vt, and to avoid a subsequent addition and the associated conching phase. It will be understood that the operator may also prefer to balance the exact amount added to a value different from Q5-Q1, but somewhere between Q7-Q1 and Q6-Q1, for example by adding an amount of fat greater than the minimum value d 'a specified amount, depending on whether said added amount avoids going through another conching phase. Regardless of the preference for a specific recipe, the associated instructions can be provided to the computer which can control the addition of the fat content, and possibly also the rest of the process, such as the cooking phase. next conching, and the possible next viscosity measurement, automatically.
    A process which is generally identical to that shown in FIG. 3A or 3B can also be applied after a second conching phase, for example when the amount of fat added between the previous conching phase (s) has led to not yet reach the target viscosity Vt according to the corresponding viscosity measurement Vm, where yet another addition of fat is made, followed by yet another conching phase, and optionally another viscosity measurement, another addition fat, etc., until the target viscosity is reached.
    As will be discussed in more detail below, various ways of forming a reference model can be used. Interestingly, in some embodiments, the reference model can be refined based on data points from viscosity measurements taken from previous real batches, for the same chocolate recipe. For example, if a given recipe leads to an initially measured viscosity (after the first conching phase), which is always significantly higher than the target viscosity, the recipe can be adjusted so that the initial amount of substance containing fat is higher by a certain amount, and the reference model used to determine the amount of fat to add based on a difference between the measured viscosity and the target viscosity can be adjusted. The same can be true even when preparing a given batch, where, for example, if it is determined that the difference between the measured viscosity and the target viscosity exceeds a given amount, the reference model can be adjusted. before calculating the amount of the fat-containing substance to be added, and any amount of the fat-containing substance to be added can be calculated based on a reference model that has been updated based on the measured points either a) earlier during the preparation of the same batch, b) during the preparation of the previous batches or c) both. To a certain extent, using somewhat advanced techniques, adjustments to a given reference model associated with a given recipe can be made based on measurements made during the preparation of one or more other recipes. Indeed, such a technique can be used, for example, if a given conch is identified as always producing a viscosity bias that other conches do not, the reference model used in that given conch can be adjusted accordingly.
    In one embodiment, for example, if a given recipe leads to exceeding the viscosity specification after a first conching phase of a previous batch, the initial amount of viscosity reducing substance specified that this recipe can be reduced, and the thus reduced amount of viscosity reducing substance can be used in place of the previous amount of viscosity reducing substance in a subsequent batch.
    Let us now pass to the question of the construction of a reference model, in a context where the expression "reference model" can also include the definition of the mixture of starting ingredients. Temperature affects the viscosity of chocolate, but does so in a highly predictable way via equations available in the literature. To avoid scenarios where different viscosity readings are taken at different temperatures and therefore biased by the temperature variable, all viscosity readings can be normalized against a reference temperature, and commercially available viscometers can do this. do it automatically. Accordingly, it will be assumed in the following text that when compared to each other, such as when constructing a reference curve or when comparing a viscosity reading with a reference curve, the viscosity readings are either taken at the same temperature or have been corrected to compensate for the effect of temperature on individual readings, mainly allowing 'compare what is comparable'. Accordingly, no further reference to temperature correction will be made in this text, temperature correction, if necessary, being implied at the viscosity values referred to.
    It was found that at the outlet of the conching system 16, the viscosity was related more reliably to the percentage of fat content than at the inlet of the mixer 4. In fact, the percentage of the content of Fat after conching is adjustable by adding liquid ingredients containing fat, such as cocoa butter, cocoa liquor, butter oil for example, and can thus be modified to cause a change in viscosity corresponding. This means that the typical statistical deviation in estimating the amount of fat required to achieve a target viscosity was significantly smaller after conching than during an initial determination of the respective amounts of ingredients to be introduced before mixing. Indeed, since no more significant physical modification is made to the cocoa mass after conching, it may be convenient to take the viscosity reading at this point, at which point the fat content may be the lowest. the only significant variable affecting viscosity. This can make it interesting to select the reference model, or adjust the reference model, depending on the actual viscosity measured after a first (or more) conching phase.
    [0029] Accordingly, according to one aspect, there is provided a process for producing chocolate, in which the amount of fat included in the ingredients added in mixing step 4 is intentionally reduced from the amount of base of fat that should be needed to reach the target viscosity value. It can be reduced to a minimum value of the margin of error, for example. Viscosity is measured after conching step 6, the difference between the measured viscosity and a target viscosity value is determined, reference data in the form of a reference curve or table can be used to calculate an amount of liquid ingredient (s) containing fat to be added so that the viscosity reaches the target viscosity value, and an amount of liquid ingredient (s) containing fat can then be added to the chocolate mass on the basis of the calculation, after conching.
    In fact, the viscosity can be linked to the fat content at least globally by a negative exponential equation, which can correspond to a curve as illustrated in FIG. 2. In one example, the reference model can be based on an equation in the form: Corrected viscosity (at corrected temperature) = A * e ^ (- B * Fat content + C) + D, where A, B, C and D are variables which depend on the specific recipe, and as such, a reference model for a specific recipe can use the corresponding values of variables A, B, C and D in the context of this equation, where the fat content can be known depending on the amount of fat contained in the crude ingredients added to the mixer, and subsequently taking into account the amount of liquid ingredients containing fat added after conching, and the viscosity can be measured at conch 16, after conching. The margin of error can be established independently, for example, and can be selected as a specified percentage of the value of the fat content to be added after the first stage of conching, for example. Alternatively, the margin of error can be established on the basis of actual data collected from one or more previous batches of the same recipe prepared by identical or similar equipment, for example. In some alternative methods of producing a suitable reference model, an appropriate algorithm, or neural network, can be used to construct a reference model that automatically suggests a single proposed value of fat content to be added based on of measurements obtained from previous batches and on certain specified parameters, such as "avoid wasting fat" or "avoid a third phase of conching" or "avoid an additional phase of conching when the cost to avoid a phase of conching extra fat is less than X amount of extra fat ”. In still other embodiments, the margin of error and / or the baseline values of the reference model can be determined using techniques of statistical analysis, curve fitting, regression, classification, measurement. grouping, dimension reduction, deep learning, neural networks, transfer learning and / or reinforcement learning techniques, to name a few examples. Different ways of carrying out the evaluation of the margin of error can be used, and such a method may involve taking into consideration how far the measured value or the viscosity values deviate from the reference model. The more a measured value deviates from the reference model, the more likely it is that the required amount of ingredient containing added fat determined on the basis of that model is outside the target to some extent, and therefore therefore, a higher margin of error can be established. The determined margin of error can be used in different ways. In certain embodiments, the statistical distribution of the margin of error can be taken into account in determining the quantity of fat to be added, this can in particular be the case when a value other than the minimum or maximum values of the additional fat content indicated by the reference model should be added. For example, it may be desirable to limit the amount of fat to be added to the extent that such limitation is deemed sufficiently improbable to lead to a subsequently measured viscosity value which does not meet the target (e.g. lower probability at 5% based on the model - in which case a subsequent conching phase would only be necessary once every 20 batches on average, which can be considered an appropriate compromise given the expected decrease in the amount of reducing substance viscosity used on 20 batches according to the technique).
    In one example, one may wish to add an amount of ingredient containing fat corresponding to the sum of the estimated base value and the determined positive branch of the margin of error, to ensure that the Adding a fat-containing ingredient will achieve the target viscosity on the first try. Such an approach may be motivated by the fact that iterations of adding a fat-containing ingredient to the cocoa mass in the conch take time, and therefore affect the ability of the production line to switch to another. lot. However, if in this particular case the estimated value minus the determined error would have been sufficient to achieve the target viscosity value, an amount of fat containing ingredient corresponding to 2 times the determined error would have been wasted.
    [0032] Alternatively, it may be preferable, in some embodiments, to proceed iteratively by adding the base estimated value minus the negative branch of the determined error margin, and once this is done, to measure the viscosity again, compare it to the target value, and if it has not yet reached the target value, determine how much fat-containing ingredient to add to achieve it. This can help ensure that the amount of fat-containing ingredient needed to achieve the viscosity target is not exceeded (exceeded) and that no fat-containing ingredient is wasted.
    In all cases, as more viscosity values are obtained from measurements carried out on batches, these experimental data can be used to finely adjust the reference model. In a specific example, a curve fitting technique can be used to adjust the curve of the initial reference model so that it best fits the new actual viscosity measurements. This can be done taking into account that the relationship between viscosity (temperature corrected) and fat content will have a negatively exponential relationship such as: Corrected viscosity (at standard temperature) = A * e ^ ( -B * Fat content + C) + D, where A, B, C and D are the model variables that need to be adjusted to get the best fit, which can be automated by a computer using a commonly available software. Partial adjustments can be made even based on a single measured viscosity and a known fat content point, but more comprehensive adjustments can be made when two or more points are determined. For example, the solution for A, B, C and / or D that best matches the viscosity values measured at the two viscosity / fat content values (the initial fat content is known, and a known amount of material fat has been added, which makes it possible to know the second value of the fat content) can be retained, and the amount of viscosity reducing substance to be added can be calculated from the equation using the refined values of A , B, C and D obtained by fitting the curve. The deviation of the measured points from the updated model can also be used to determine the likely degree of error in the calculated amount of viscosity reducing substance to be added, and if desired this degree of error can be subtracted from the determined amount of fat to give the actual amount of viscosity reducing substance to be added to avoid overcompensation, and if desired further iterations can be performed, with other measurement points used to further refine the model if that is is practical, until the actual measured viscosity matches the target value within acceptable tolerances.
    [0034] The same production line can be used to produce different chocolate recipes, each having its own reference model, and as a result, the same line can be used to produce chocolate according to several other recipes before having to produce. the same chocolate recipe another time. However, when the same recipe comes up, the “learning” of the algorithm that took place the first time the process was executed can be exploited to reduce the amount of error, or the amount of iterations, needed to. reach the target viscosity value in the next batch. Indeed, the initial quantity of ingredient containing fat added in the mixer can be determined using the refined model, that is to say the model previously corrected according to the actual fat content by relative to viscosity behavior as measured, and / or the first amount of fat-containing ingredient added in the next batch can be calculated using the refined model.
    [0035] It may be preferable to limit the ease with which the model can be modified according to the actual measurements. Indeed, some measured effects of fat content versus viscosity behavior may be batch specific or even problematic, and in such scenarios, fully base calculations of the amount of ingredient containing fat. fat to be added to reach the target viscosity of the next batch on the behavior of the previous batch may lead to a higher degree of error than if these calculations were based on a single generic reference model representing the average behavior of a large number of lots. Likewise, it may even be preferable to limit the importance that is given to one or more measurements in the correction of the reference model used to correct that specific batch, and reference models modified in an intermediate or complete manner can be repeated for the next batch so that the next batch has access either to the reference model used as a last resort in the previous batch, or to a reference model partially modified on the basis of the lessons received by the measurements carried out in the previous batch. Accordingly, in some cases it may be preferable to limit the effect that individual batches may have on the reference model which is carried over for the next batch, which can be obtained by weighting in each measurement equally against to all previous measurements that have taken place, for example, or in some cases, corrections from more recent measurements may be assigned greater importance than previous measurements, so as to allow the reference model to adapt gradual changes that may occur in batches due to changes in the source product and / or the environment. Ultimately, it may be desirable to use artificial intelligence to determine the importance placed on a given measurement, either to determine how much of the fat-containing ingredient to add to the specific batch, or to correct the reference model for future batches.
    FIG. 4 shows an example of a flowchart illustrating the steps which can be carried out using a computer. Indeed, the viscosity can be measured 34, or rather the equivalent of the viscosity for a given reference temperature can be determined, using a viscometer 18. The measured viscosity value can be communicated to a computer 28 , which can be done by cable or wireless for example. Computer 28 may have access to reference data 36 which may include both a target viscosity value specification 38 for the recipe and a reference model 40 representing an expected relationship between fat content and viscosity for the recipe. recipe. Reference model 40 can take into account the initial amount of fat that was introduced into mixer 4 or otherwise earlier in the process. In Reference Model 40, the expected relationship may be presented in tabular form, but it may be more convenient with computers available today to present the relationship directly as a mathematical equation. For example, the reference data 36 may take the form of a negative exponential mathematical equation of the following type:Corrected viscosity (at standard temperature) = A * e ^ (- B * Fat content + C) + D (1)where A, B, C and D are variables which depend on the specific recipe. Such a relationship, when presented graphically, produces curves such as the example curves shown in Figure 5. On exiting conch 16, this reference model 40 for viscosity behavior as a function of the fat content may be more reliable, and may provide better accuracy than estimating viscosity based on the amount of fat added at the time of mixing and at the start of the conching process.
    The computer 28 can have access to reference data 36 including equations or tables, and associate the fat content introduced at the start (recipes) and the viscosity targets for each of a plurality of recipes, and can select the correct reference data 36 based on user input indicating the recipe corresponding to the current batch, for example. For example, milk chocolate and dark chocolate may have different recipes and reference data 36, and milk chocolate with different fineness, for example 25 µm, 35 µm and 50 µm, may have different recipes and data. Reference 36. Different computers can control different parts of the process, and any processor, controller, memory, etc. used can be either local, in part or in whole, or remote and / or distributed and / or virtual.
    [0038] The expression reference data 36 can also be used to encompass the target viscosity value 38 required for the specific recipe upon leaving the conch, for example.
    The reference data 36 for each recipe can be established by taking experimentally, for each recipe, and for a plurality of fat content values, a number of viscosity values at the outlet of the conching, and this process can be repeated until the obtained reference curves are satisfactory representative of the behavior of the given recipe. Indeed, with reference to figure 5, each time the viscosity is measured at a different fat content, a point can be added to the original reference point, and any other previous reference point, and the adjustment of the curve can be used to adjust the model accordingly, potentially weighting the amount of previous reference points and the magnitude of the deviation between a single reference point and the model.
    Once the baseline data for the specific recipe has been established, and by measuring the viscosity 34 after conching step 6, the computer 28 can determine, as shown in Figure 5, how far away we are. sums of the desired viscosity along the curve, and computer 28 can thus determine the amount of fat that must be added 44 to achieve the desired viscosity. The corresponding amount of fat can then be added 46, in the form of specific amounts of one or more liquid fat-containing ingredients, to the cocoa mass to achieve the desired viscosity. In many modern production lines, the addition of fat-containing liquid ingredients such as cocoa butter and cocoa liquor can be automated and therefore can be driven directly by a computer 28 acting as a controller to a controller. Appropriate metering system 26, based on the calculated value 44. The metering system 26 may be a pump associated with a flow meter and controlled by a computer 28 so as to deliver a specified amount of viscosity reducing substance based on the reading of the flow meter , to cite just one example.
    In theory, this will lead to the exact target viscosity which is desired for the specific recipe using the minimum amount of fat containing ingredients, and can target a minimum amount of cocoa butter in particular. In practice, when the viscosity is measured after stabilization after the addition, the exact value of the viscosity will typically be at least slightly different from the target value. The same process can be repeated at this point to add more fat if viscosity still needs to be added, but it may be desirable to limit the amount of fat addition cycles on a single batch as the additional cycles require more. production time. However, on the other hand, if the viscosity is lower than the target, then fat containing ingredients such as cocoa butter have been wasted. To avoid wasting cocoa butter, one may wish to add a little less cocoa butter than the amount indicated by the curve, but this is tricky, because if too little cocoa butter is added, additional production time will be required. necessary for the subsequent iteration of adding cocoa butter.
    It will be understood that the steps of determining 44 and adding an amount of viscosity reducing substance 46 need not be completed if the measured viscosity 34 reaches the target viscosity value 38 within a certain range, which can be determined by the user. The computer 28 can check whether the viscosity is within the target viscosity 42 after each viscosity measurement 34, for example, and indicate to the production line that the product is ready to be tempered 48 if it meets the viscosity requirements. .
    The flowchart shown in Figure 6 shows a more elaborate embodiment in which one or two additional characteristics may be present. The first potential additional feature is to determine how much the reference data deviates from the measurements 50, to calculate the potential error on this basis 52, and to adjust the amount of added fat based on this error. For example, the amount of cocoa butter added may correspond to the amount of cocoa butter indicated by the curve minus the% error expected based on the deviations detected. The second potential additional feature is that the benchmark data itself can be adjusted based on the detected deviation 54, and this can be done either for subsequent additions of cocoa butter to take place on the current batch or for a benchmark use on subsequent lots, or both.
    Indeed, with each measurement of a particular recipe, more and more experimental points can be added to the specific reference curve of the product, and an exponential regression can be recalculated, taking all the points into consideration, Everytime. When adding cocoa butter, the amount of cocoa butter added can be adapted as a function of the correlation coefficient between the measured viscosity value (s) and the recalculated exponential regression. The closer the coefficient is to 1, the more aggressive the system can be in determining the amount of cocoa butter (i.e. determining an amount closer to the value of the reference curve), while avoiding overdosing . As the amount of experimental points increases over time, the average correlation factor may improve.
    For example, a coefficient of 0.97 means that the reference curve very closely represents the viscosity values which have been measured for the corresponding values of fat content. In such a case, the system can use the value indicated by the curve to determine the exact amount of butter to add with a very low risk of overshooting.
    Figure 7 shows three examples. Each example includes three measured viscosity values for a corresponding product / recipe. For each recipe, a curve fitting algorithm was used to determine the value of the coefficients A and B that best match the three experimental points, and the distance between the point and the corresponding curve is used to determine the coefficient. In the case of product 1, the coefficient of its curve 56 is 0.98, and in products 2 and 3, the coefficients of their curves 58, 60 are 0.97. In all of these cases the measured values are quite close to the fitted curves and the value of the added cocoa butter curve can be used directly if the process otherwise allows, as it will likely lead to a viscosity within the specification tolerances of viscosity.
    [0047] In order to have a curve which adapts to changes in raw material, environmental conditions and / or other gradual changes, a weighting factor can be applied to the most recent points. This weighting factor can be selected as being 1 / number of days since the last measurement, for example, which leads for example to a scenario where a point which was taken over a year ago will be 1/360 of the importance of 'a point taken today. Such an approach would ensure that fresh data takes precedence over older data, without completely neglecting the entire history. Depending on the software application used, all weighting factors may be updated every day at midnight, for example. Further development of the algorithm or the use of machine learning, for example, could allow time varying factors such as seasonal fluctuations to be taken into account, potentially allowing even more accurate forecasting.
    In order to be able to follow the evolution of the viscosity over time, each distance from point to the curve can be recorded and plotted as a function of time. This can help to have a time base variation curve by product that will show problems with the process or with the raw materials.
    In one example, the adjustment of the viscosity can be carried out by following the following steps: 1- Conching ends, leading to the viscosity control step. 2- Recirculation through the viscometer begins. 3- Viscosity is monitored until the reading stabilizes (when recirculation starts, the system may need a few minutes to give an accurate reading). 4- An average value of the time compensated in temperature is extracted from the viscometer (the viscometer performs the temperature correction). 5- The actual dose of fat is calculated on the basis of the actual dosage of the mixer and the conche and not on the basis of the theoretical recipe. This gives the actual fat content. 6- If the lecithin actually dosed does not match, the optimal value system adjusts. If an adjustment is necessary, go back to step 3. 7- This new point (% fat, viscosity) is placed on the reference curve of the product. 8- The theoretical fat content required is calculated from the reference curve. The target viscosity is the average between the nominal viscosity and the positive tolerance. This gives the amount of butter to add to meet the specification limit and put in as little butter as possible to meet the specification.Difference in% fat = (theoretical% fat necessary to reach the target viscosity -% real fat) 9- This quantity is reduced according to the correlation coefficient to avoid any overshoot.Addition of butter [kg] = Actual weight in the conch * (Difference in% fat) * Correlation coefficient 10- The adjustment is complete. 11- If the viscosity is not in the range, go back to step 3; if it is within the range, go to 12. 12- Wait for the discharge temperature to be reached. 13- Take a sample. 14- Start emptying.
    In practice, the data associated with each recipe may further include reference data for the algorithm, and this additional reference data may include the following parameters: nominal viscosity in CPS; position tolerance in%: (default value, maybe 10%), negative tolerance in%: (default value, maybe 10%), optimum value of lecithin: (default value, maybe 0 , 5%); amount of fat to be removed from the conch: (default value, maybe 5%), initial reference curve: recalculated reference curve equation with addition of viscosity measurement points; correlation coefficient of the reference curve; table with the value of the reference curve to allow manual adjustment. In addition, the following data can be recorded in association with each recipe for reference: (time,% fat, viscosity, grain size): to obtain the regression rule; (time, distance from the regression curve): to get an idea of the accuracy of the model; (time, final% fat): to know when to update the official recipe. The basic calculated data of the recipe can be the following: parameter of the equation: viscosity = A * e ^ (Bx + C) + D; - correlation coefficient R ^ 2; - target viscosity. The basic recorded data of the job can be as follows: 25 (time,% fat, viscosity, particle size): to get an idea of how the viscosity fluctuated during the job. The basic calculated data of the work can be the following: addition of butter to be carried out.
    As can be understood, the examples described above and illustrated are given by way of example only. The scope is indicated by the appended claims.
    权利要求:
    Claims (21)
    [1]
    1. Process for producing chocolate comprising:the mixture of ingredients in a cocoa mass, the conching of the cocoa mass and, after at least one phase of said conching, the measurement of the viscosity of the conched cocoa mass,according to whether said measured viscosity value is greater than a target viscosity value, the determination, on the basis of the measured viscosity and the reference data representing a reference model of viscosity relative to the content of the viscosity reducing substance for the chocolate to be produced, of an amount of viscosity reducing substance to be added to the cocoa mass to achieve the target viscosity value, and adding, to the conched cocoa mass, of the amount of viscosity reducing substance to be added .
    [2]
    The method of claim 1, wherein said determining the amount of viscosity reducing substance includes determining a difference between the measured viscosity value and a target viscosity value, associating the difference with an amount of. base of viscosity reducing substance to be added on the basis of a reference model, the amount of base having a margin of error extending to a maximum amount and to a minimum amount from the amount of base, and selecting, for the amount of viscosity reducing substance to be added, a value different from the amount of base, but within the margin of error.
    [3]
    The method of claim 2, wherein said selecting includes selecting, for the amount of viscosity reducing substance to be added, the minimum amount.
    [4]
    The method of claim 2, wherein said selecting includes selecting, for the amount of viscosity reducing substance to be added, the maximum amount.
    [5]
    The method of claim 2, wherein the margin of error is determined on the basis of the difference between the measured viscosity value and the target viscosity value.
    [6]
    6. The method of claim 5, wherein the margin of error is proportional to the difference.
    [7]
    The method of claim 1, leading to the preparation of a first batch of chocolate, further comprising repeating said steps to prepare a second batch of chocolate, after preparation of the first batch, further comprising adjusting the pattern. viscosity reference according to the viscosity reducing substance based on the measured viscosity value of the first batch.
    [8]
    The method of claim 1, leading to the preparation of a first batch of chocolate, further comprising repeating said steps for a second iteration to prepare a second batch of chocolate, wherein an initial amount of fat forming part of the ingredients mixed into the cocoa mass during the second iteration is determined based on the measured viscosity value of the first iteration.
    [9]
    9. The method of claim 8, wherein the initial amount of fat during the first iteration is based on the reference model, wherein the initial amount of fat in the second iteration is based on the reference model, the model. reference being adjusted between the first iteration and the second iteration based on a measured deviation between the measured viscosity value and the reference model during the first iteration.
    [10]
    10. The method of claim 1, further comprising performing a subsequent conching phase, after said addition of the viscosity reducing substance.
    [11]
    11. The method of claim 10, further comprising measuring the viscosity of the conched cocoa mass after the subsequent conching phase and, depending on whether said subsequently measured viscosity value is greater than a target viscosity value after the conching phase. subsequent conching, determining, on the basis of the subsequently measured viscosity and the reference data, an additional amount of viscosity reducing substance to be added to the cocoa mass to achieve the target viscosity value, and adding, to the conched cocoa mass, a viscosity reducing substance containing the additional amount of viscosity reducing substance to be added.
    [12]
    The method of claim 1, further comprising after adding the viscosity reducing substance, stabilizing the cocoa mass and measuring the viscosity of the stabilized cocoa mass.
    [13]
    The method of claim 12, further comprising: wherein said measured viscosity of the stabilized cocoa mass is greater than a target viscosity value, calculating, based on the benchmark data, an additional amount of substance. viscosity reducing substance to be added, and adding the additional amount of viscosity reducing substance.
    [14]
    The method of claim 1, further comprising determining a difference between the content of viscosity reducing substance and the measured viscosity of a corresponding reference viscosity reducing substance content and a reference viscosity being part of the data of. reference.
    [15]
    15. The method of claim 14, further comprising adjusting the amount of viscosity reducing substance to be added based on the difference.
    [16]
    16. The method of claim 14, further comprising adjusting the benchmark data based on the difference.
    [17]
    17. The method of claim 1, wherein the viscosity reducing substance is a substance containing fat.
    [18]
    18. The method of claim 17, wherein the fat-containing substance is cocoa butter.
    [19]
    19. The method of claim 1, wherein measuring the viscosity includes recirculating the cocoa mass from and to the conch through a viscometer.
    [20]
    20. A method of adding an amount of viscosity reducing substance after a given conching phase, the method including measuring the viscosity of the chocolate mass after the given conching phase, determining an amount of substance. viscosity reducing substance to be added, adding the determined amount of viscosity reducing substance, and performing a subsequent conching step, wherein said determining the amount of viscosity reducing substance includes determining a difference between the measured viscosity and a target viscosity value, associating the difference with a base amount of viscosity reducing substance to be added based on a reference model, the associated amount having a margin of error, and the selection, for the quantity of viscosity reducing substance to be added, of a value different from the basic value, but within the margin of error.
    [21]
    21. A process of producing a plurality of batches of a given chocolate recipe, wherein for each batch an initial amount of viscosity reducing substance and / or a subsequently added amount of viscosity reducing substance is determined based on a reference model associated with the recipe, and in which the reference model is modified or updated between a previous batch and a following batch on the basis of one or more viscosity measurements taken during the preparation of the batch previous.
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    同族专利:
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    US20210112824A1|2021-04-22|
    CA3096369A1|2021-04-16|
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