Method for controlling ice cream hardening tunnel, ice cream hardening tunnel and ice cream production line

Abstract

The invention relates to a method for controlling a hardening tunnel, comprising setting adjustable tunnel parameters for the hardening tunnel, providing a plurality of ice cream products upstream of the hardening tunnel on a transport surface carried by a hardening tunnel conveyor, transporting the ice cream products on the conveyor through the hardening tunnel, and creating adhesion between the ice cream product and the transport surface, continuously measuring the adhesion of the ice cream product within and / or downstream of the hardening tunnel, continuously adjusting the tunnel parameters based on the measured adhesion.

Description

TECHNICAL FIELD

[0001] The present invention relates to a method for controlling an ice cream hardening tunnel, an ice cream hardening tunnel and an ice cream production line. BACKGROUND

[0002] Ice cream product manufacturing on an industrial scale is a well-established technical field, and for decades ice cream production lines have been available. In the past years, ice cream manufacturing production lines have significantly developed in meeting the requirements of the users in terms of design, taste, price, texture, etc.

[0003] An example of such prior art system is disclosed in EP2934168B1, in particular relating to how to control an object which can be referred to as an ice cream hardening tunnel. The ice cream hardening tunnel can be simply referred to as a tunnel which continuously cools ice cream products fed upstream to the hardening tunnel while the ice cream products are transported through the ice cream hardening tunnel. The basic function of the ice cream hardening tunnel is to harden the already produced ice cream products which have a warm enough ice cream temperature to be able to at least partially manufacture and form the products. The hardening is obtained by reducing the temperature of the ice cream enough to harden the ice cream to have a stable form to package and store the produced products in a reliable way and to obtain a robust manufacturing process.

[0004] A challenge of the disclosed hardening tunnel is difficult to control and as a result thereof is for example an unnecessarily high energy consumption which is highly dependent on human control. To help this difficult control of the disclosed hardening tunnel, the system of EP2934168B1 measures the surface temperature of the ice cream products and the lifting torque. A challenge of the proposed control method is that the operation of the hardening tunnel and the whole ice cream production line is difficult and that defective products are likely a result of this type of operation, thereby not only being at risk of low yield, but more importantly leading to challenges and quality problems further downstream of the ice cream production line. SUMMARY

[0005] The present invention relates to a method for controlling a hardening tunnel, comprising: providing adjustable tunnel parameters for a hardening tunnel, providing a plurality of ice cream products on a transportation surface carried by a hardening tunnel conveyor upstream of the hardening tunnel, transporting the ice cream products on the conveyor through the hardening tunnel and creating adhesion between the ice cream products and the transportation surface, continuously measuring the adhesion of the ice cream products within and / or downstream of the hardening tunnel, continuously adjusting the tunnel parameters based on the measured adhesion.

[0006] A hardening tunnel can be understood as a freezing tunnel for the production of ice cream products. A hardening tunnel freezes ice cream products manufactured at a slightly higher temperature to ensure proper hardening and core temperature of the ice cream products. A hardening tunnel can typically comprise a conveyor with a length dimension of 100, 500 or 1000 meters.

[0007] The term "hardening tunnel" can be understood as a tunnel in a production line of, for example, ice cream products. A hardening tunnel can also be understood as a freezing tunnel, a cooling tunnel or an ice cream tunnel. A hardening tunnel can be used to reduce the temperature of ice cream products in a production line, thereby hardening the ice cream products. A hardening tunnel can typically comprise a long conveyor of ice cream products for transporting the ice cream products through the hardening tunnel. In a hardening tunnel, there can also be elements for adjusting the temperature and thereby freezing the ice cream products. A hardening tunnel can also comprise devices and equipment for controlling, regulating and directing the air flow within the hardening tunnel to optimize the hardening process of the ice cream products. A hardening tunnel can typically comprise an air balance system to maintain the freezing inside the hardening tunnel and the warmer air outside the hardening tunnel. The air balance can be a fan or a blower that can create a pressure inside the hardening tunnel to maintain the freezing air inside. Especially at the inlet and outlet of the conveyor, the hardening tunnel can use an air balance system to prevent warmer air from entering the hardening tunnel compared to the freezing air in the hardening tunnel. In the same respect, the air balance system in the hardening tunnel can also prevent freezing air from leaving the hardening tunnel through the air balance system.

[0008] The term "tunnel parameter" is to be understood as a parameter that can be controlled and regulated to adjust the ice cream products output from the hardening tunnel. A tunnel parameter can be the temperature within the hardening tunnel, the tunnel temperature, which can control the degree to which the hardening tunnel should cool the ice cream products passing through the hardening tunnel. Another tunnel parameter can be the air flow, where the speed of the fans can be controlled to better distribute the air within the hardening tunnel. The air flow can also be changed by changing the position of different air guides or deflectors to optimize the air flow in certain volumes inside the hardening tunnel.

[0009] Another tunnel parameter can be the humidity within the hardening tunnel. The humidity can depend on the process of manufacturing the ice cream products, which can result in frost within the hardening tunnel. The frost can for example change the air flow on the ice cream products within the hardening tunnel, thereby causing a change in the cooling of the ice cream products. The humidity can be controlled by a dehumidifier to ensure the correct humidity in the hardening tunnel depending on the type of ice cream products being hardened.

[0010] Another tunnel parameter could be air balance, which involves how to keep chilled air within the hardened tunnel and prevent warmer ambient air from entering. This can be achieved through fans, air deflectors, or blowers, which will blow and direct chilled air within the tunnel to keep it inside, especially around the conveyor inlets and outlets. Therefore, air balance systems often create overpressure within the hardened tunnel.

[0011] The speed of the conveyor within the hardening tunnel can also be considered a tunnel parameter, defining how long a given ice cream product cools within the tunnel. A faster conveyor speed can favor faster processing for a larger output of ice cream products. Conversely, a higher speed will result in less time for the ice cream products to spend in the hardening tunnel, thus reducing freezing time.

[0012] Another tunnel parameter could be the quantity of ice cream products in the hardening tunnel. Since the temperature of the ice cream products entering the hardening tunnel is higher than the temperature inside the tunnel, the quantity of ice cream products can affect the temperature. Ice cream products can also affect the humidity inside the hardening tunnel; therefore, the quantity of ice cream products in the freezing tunnel can influence the humidity within the hardening tunnel.

[0013] Another tunnel parameter can be the timing of evaporator defrosting. Evaporators in a hardened tunnel can be defrosted one at a time, especially when the hardened tunnel includes more than two evaporators. In this case, at least two evaporators can still be cooled while the third evaporator can be defrosted. A tunnel parameter can also be the timing of hardened tunnel defrosting, where the entire hardened tunnel is defrosted.

[0014] In an advantageous embodiment of the invention, the ice cream product is transferred from the hardened tunnel conveyor to another conveyor downstream of the hardened tunnel conveyor via an ice cream transfer system.

[0015] In an advantageous embodiment of the invention, the ice cream product is transferred from the hardened tunnel conveyor to another conveyor downstream of the hardened tunnel conveyor via an ice cream transfer system, wherein the ice cream transfer system includes lifting equipment.

[0016] In an advantageous embodiment of the invention, the ice cream product comprises a respective ice cream stick, and wherein the ice cream product is transferred from the hardened tunnel conveyor to another conveyor downstream of the hardened tunnel conveyor via an ice cream transfer system, and wherein the ice cream transfer system lifts the ice cream product via an ice cream product holder.

[0017] The term "ice cream product holder" can be understood as a mechanism that holds ice cream products with, for example, a mechanical holder around an ice cream product, a mechanical holder around an ice cream product stick, or a vacuum holder.

[0018] The term "adhesion" can be understood as the adhesion between the ice cream product and the transport surface. It can also be understood as the attachment or connection between the ice cream product and the conveyor established or at least altered by the ice cream hardening tunnel as the ice cream is conveyed through it to harden. When ice cream products are produced in large quantities, for example by extrusion, the adhesion between the ice cream product and the conveyor begins upstream of the hardening tunnel. As the ice cream product moves through the hardening tunnel until it is lifted or moved away from the conveyor and transferred to ice cream handling equipment downstream of the ice cream production line, the adhesion typically changes. The temperature of the ice cream product can be, for example, -4 to -8 degrees Celsius as it is formed and positioned on the hardening tunnel conveyor upstream of the ice cream hardening tunnel.

[0019] During the process in the hardening tunnel, the adhesion between the ice cream product and the conveyor can change as described above. This change in adhesion can be slightly unpredictable and may therefore result in the ice cream product being so strongly adhered to the transport surface that it is too sticky when it is to be transferred out of the hardening tunnel conveyor, or the adhesion may be so low that it causes the ice cream product to fall off the conveyor into the ice cream hardening tunnel.

[0020] When producing ice cream products, adhesion is ideally within certain intervals. These intervals typically have two limits, an upper and a lower limit, where one limit can be stronger adhesion. Stronger adhesion can be equal to the limit at which the ice cream product can be just released from the conveyor without damage. Stronger adhesion limits more often manifest as a softer ice cream product. When attempting to lift an ice cream product with excessive adhesion, it may break apart, for example, detach from the ice cream body or tear. The ice cream body may also disintegrate. The ice cream product may be damaged when it is lifted and sticks to the conveyor belt. Avoiding damage when lifting an ice cream product may mean that the ice cream product does not remain adhered to the conveyor after, for example, an attempt to lift it (e.g., by the stick). Another potential damage to the ice cream product can occur when lifting pulls out or breaks the stick or any retaining device. At the point where lifting begins to damage the ice cream product, adhesion can be characterized as strong and will exceed the limit of the adhesion interval. Lifting an ice cream product can be completed with difficulty, as the product may end up in a different position. The new position of the ice cream product may be outside the alignment position of the gripper.

[0021] The lower limit of the adhesiveness interval will be when the ice cream product's adhesiveness is too weak. This lower limit could be when the ice cream product is too hard and the adhesiveness too weak, causing it to change position along the conveyor's curve, thus pulling the product away from the curve. This could typically be a centrifugal force pulling the product out of position, or even causing it to fall off the conveyor. When the ice cream product changes position, for example, due to planned movement, the lifting robot may have difficulty or be unable to lift it from a conveyor downstream of a hardened tunnel conveyor.

[0022] In both cases, when adhesion exceeds one of the two interval limits, it can ultimately lead to the discarding of ice cream products or disruption of the ice cream manufacturing process, and also cause serious damage to downstream coating or packaging processes in the ice cream production line. Therefore, it is highly advantageous to measure adhesion and adjust adjustable tunnel parameters relative to it to control the cooling and operation of the hardened tunnel. Operating at optimal adhesion may mean achieving higher capacity and / or lower energy consumption.

[0023] By continuously (at an appropriate rate) measuring adhesion, the production line can be pushed to its limits relative to adhesion, bringing the system closer to the point where ice cream products might detach from the hardened tunnel (either inside or outside), if adhesion is minimal. In conventional systems tuned purely on when ice cream products will fall, the system offers the possibility of predictable settings close to system limits, but without any ice cream products falling. Similarly, if adhesion is within a safe and acceptable range, conveyor speeds can be increased.

[0024] Adhesion can be measured in a variety of different ways, such as through a lifting mechanism, which is often automated. The lifting mechanism can be placed downstream of the hardened tunnel, for example, downstream of the hardened tunnel, or outside the hardened tunnel, where adhesion can be measured. The lifting mechanism can also be part of a robot that lifts ice cream products from a conveyor to the next part of the production line.

[0025] Adhesion can be measured as the force required to pull an ice cream product away from a conveyor. The measured force required to pull the ice cream product away can be expressed as, for example, lifting force, torque, rotational force, tilting force, displacement of the ice cream product (shear force), or any combination thereof.

[0026] The term "conveyor" can be understood as a conveyor on which ice cream products can be positioned. A conveyor can be a belt or band used to transport ice cream products. A conveyor can also include rollers with space between each roller. A conveyor can also include trays, pallets, or bowls placed on and transported by the conveyor, wherein the tray, pallet, or bowl can form a surface on which the ice cream products are transported. Therefore, the term "transport surface" can refer to any surface on which ice cream products are positioned, whether it is the conveyor itself, such as a conveyor belt, or it can refer to the surface of a "loose" carrier, such as the aforementioned tray, pallet, or bowl.

[0027] This invention improves the freezing process of ice cream products. While the tunnel parameters of the hardening tunnel can remain constant over time, variations in the hardening tunnel can still occur, for example, due to frosting or residue from the last batch of ice cream. Frosting and residue can alter airflow, humidity, and other environmental parameters within the hardening tunnel, affecting how the freezing process of the ice cream products will function. Therefore, the need to set and adjust the hardening tunnel parameters is important for maintaining consistent adhesion of ice cream products over time. For different types of ice cream products and even for the same type, the method of this invention can maintain adhesion within adhesion intervals over time.

[0028] The term "continuous measurement" can be understood as a real-time measurement of the adhesiveness of an ice cream product that is continuously measured while the freezing and hardening process is underway. The term "continuous measurement" can also refer to a given time interval, where the adhesiveness of the ice cream product can be measured at a specific point in time and repeated at the same time intervals. The time interval for continuously measuring the adhesiveness of an ice cream product can range from seconds, minutes, hours, or days. Continuous measurement can also refer to sequential measurements of adhesiveness at locations where the time interval varies over time based on, for example, the adhesiveness of the ice cream product and / or the core temperature or how long the hardening tunnel has been operating.

[0029] The term "continuous adjustment of tunnel parameters" can be understood as real-time adjustment of hardened tunnel parameters relative to the measurement of the adhesiveness of an ice cream product. The term "continuous adjustment" can also refer to adjustments made repeatedly after specific time intervals. These time intervals can range from seconds, minutes, hours, or days. Continuous adjustment can also be understood as sequentially adjusting the hardened tunnel parameters after time intervals, where the time intervals can vary depending on the adhesiveness of the ice cream product being measured, how long the hardened tunnel has been frozen, or are related to the adjustable tunnel parameters themselves.

[0030] It is difficult to change tunnel parameters during ice cream production and maintain sufficiently good quality in the ice cream product. The results of changing adjustable tunnel parameters can usually be seen first after a given time interval (e.g., 30 minutes) of the ice cream product's adhesion, during which time much of the ice cream product has passed through the hardened tunnel. It is advantageous to continuously adjust the tunnel parameters to maintain adhesion within, for example, a desired predetermined adhesion interval. If this value is measured, it can be used as the basis for manually or automatically adjusting the adjustable tunnel parameters, supplemented, for example, by inputting other relevant measurement process characterization parameters.

[0031] In an advantageous embodiment of the invention, the adhesiveness is measured as the ice cream product is lifted away from the conveyor downstream of the hardened tunnel.

[0032] In an advantageous embodiment of the invention, the adhesiveness is measured downstream of the hardened tunnel and prior to any optional active loosening of the ice cream product on the hardened tunnel conveyor downstream of the hardened tunnel.

[0033] In an advantageous embodiment of the invention, the tunneling parameters are continuously adjusted based on the adhesiveness of the ice cream product to provide adhesiveness of the ice cream product within adhesiveness intervals.

[0034] In an advantageous embodiment of the invention, adhesion is measured as the torque when the ice cream is lifted with its respective stick.

[0035] The measurement of adhesive torque can be understood as a lifting mechanism fixed beside the conveyor that can lift and rotate around a fixed point on the lifting mechanism. The ice cream product can be lifted downstream of the hardened tunnel by the lifting mechanism, or it can be lifted at a point on the conveyor where the ice cream product moves further down the production line.

[0036] The lifting mechanism for adhesion measurement can be, for example, a robotic arm, a lever, etc.

[0037] Advantageously, adhesion can be measured by torque, and then the adhesion can be measured as the ice cream product is removed from the conveyor.

[0038] In an advantageous embodiment of the invention, the adhesiveness is measured as the force / torque when lifting the ice cream, for example by a gripper and / or a suction device.

[0039] In an advantageous embodiment of the invention, adhesion is measured as lifting force.

[0040] Adhesion can be measured as lifting force from, for example, robotic arms, linear lifting and / or rotary systems.

[0041] In an advantageous embodiment of the invention, adhesion is measured as rotational force.

[0042] In an advantageous embodiment of the invention, adhesion is measured as displacement force.

[0043] In an advantageous embodiment of the invention, adhesion is measured as tilting force.

[0044] In an advantageous embodiment of the invention, adhesion is measured as displacement caused by a test force.

[0045] In an advantageous embodiment of the invention, the test force is a predetermined, clearly defined test force.

[0046] Using test forces to measure adhesion can be advantageous, i.e., measuring the force required for an ice cream product to slide and / or measuring how much an ice cream product has displaced under a certain fixed test force.

[0047] In an advantageous embodiment of the invention, the step of measuring adhesion is performed inside the hardened tunnel, downstream of the hardened tunnel, or before the ice cream product is released from the conveyor.

[0048] Advantageously, the adhesion inside the hardened tunnel can be measured to change tunnel parameters earlier in the process, thus within a predetermined adhesion interval. When the predetermined adhesion interval is reached, more ice cream products can be produced over time.

[0049] In an advantageous embodiment of the invention, the condition of the transport surface is measured before multiple ice cream products are served on the hardened tunnel conveyor.

[0050] It may be advantageous to measure the transport surface before placing ice cream products onto the conveyor. It may also be advantageous to measure for the presence of any frost or ice cream residue on the conveyor that could affect adhesion. Measurements can be performed visually, where a camera can be used to detect the presence of any frost or residue. Alternatively, vision-based measurements can be performed using laser measurement if any refraction is present or how much refraction is measured. Refraction can indicate the presence of a layer of frost, ice cream residue, or anything else on the conveyor by comparing the refraction to that on a clean conveyor.

[0051] Measuring the surface temperature of hardened tunnel transport surfaces may also be beneficial.

[0052] Measurements can also be taken as the weight of the conveyor. The conveyor can be a plate, where the weight of each plate is known. The weight of the plate can be measured before ice cream products are placed on it, and this weight can be compared to the original weight of the plate. If there is a difference between the weight of the plate and its original weight, it can indicate ice cream residue or frosting on the plate.

[0053] The properties of a conveyor can also be measured using electrical conductivity. The transport surface can also have its conductivity measured during conveyor cleaning and before production begins and the tunnel hardens. The conductivity of a clean conveyor can be compared to that of a conveyor that has already passed through a hardened tunnel. The difference between the conductivity of a clean conveyor and that of a conveyor that has passed through a hardened tunnel can indicate, for example, the presence of frost or residue on the conveyor, thus potentially altering its adhesiveness.

[0054] In an advantageous embodiment of the invention, the condition of the transport surface of the hardened tunnel conveyor is measured, and the condition is modified based on the measured condition.

[0055] The conditions for measuring and modifying the transport surface may include, for example, transport surface temperature, transport surface frost conditions, remaining transport surface ice cream products, transport surface humidity, transport surface impurities, and adjustable adhesion parameters.

[0056] In an advantageous embodiment of the invention, the condition of the transport surface of the hardened tunnel conveyor is measured for the transport surface, and the condition is modified based on the measurement conditions in the transport surface cooling device / tunnel upstream of the hardened tunnel.

[0057] Therefore, modifications can be made in individual tunnels through simple temperature adjustments, but modifications can also be achieved through dedicated fans located upstream of hardened tunnels or only inside hardened tunnels.

[0058] In an advantageous embodiment of the invention, the adjustable tunnel parameters may further include any one of the following: tunnel temperature, airflow (fan speed), conveyor speed, humidity, air balance, quantity of ice cream products, defrosting of the evaporator, defrosting of the tunnel, effective feed rate of ice cream products upstream, and / or any combination thereof.

[0059] In an advantageous embodiment of the invention, the core temperature is measured by inserting a temperature sensor into the ice cream product, and the adhesiveness is measured by pulling the sensor in while the temperature sensor is placed inside the ice cream product.

[0060] In an advantageous embodiment of the invention, the step of measuring the core temperature of the ice cream product further includes measuring the tunnel temperature and / or ambient temperature.

[0061] In an advantageous embodiment of the invention, the step of adjusting the adjustable tunnel parameters is further based on the tunnel temperature and / or the ambient temperature.

[0062] Advantageously, the cooling process of the ice cream products in the hardening tunnel can be adjusted based on the temperature inside the hardening tunnel and the ambient temperature. Ambient temperature can affect the ice cream products following the hardening tunnel along the production line, where it is advantageous to ensure that the ice cream products do not soften, melt, or become too sticky on the conveyor.

[0063] Ambient temperature can be understood as the temperature inside the room where ice cream production is taking place. Ambient temperature can be measured at different locations along the ice cream production line. These locations could be upstream or downstream of a hardened tunnel, but they could also be any other location along the production line. The ambient temperature can be the average of all temperatures measured in the room where ice cream is produced, or any combination of the measured temperatures and the average temperature.

[0064] When developing different products for ice cream around the world where ambient temperatures can vary greatly, it is advantageous to adjust the hardening tunnels according to the ambient temperature. Denmark's hardening tunnels may be exposed to different ambient temperatures compared to the United States, India, or other parts of the world. It would be advantageous to control the hardening tunnels independently, in the same way as their location on Earth.

[0065] In an advantageous embodiment of the invention, the continuous measurement of the core temperature of the ice cream product and the continuous adjustment of the adjustable tunnel parameters based on the core temperature of the ice cream product are performed automatically.

[0066] Advantageously, continuous adjustments are made automatically to ensure correct settings are made based on ongoing measurements of the core temperature. Technicians in the freezing tunnel field will experiment with different settings and see if they have the correct impact on the production of ice cream products. The effects of setting changes will not be immediately apparent, so if erroneous changes to the adjustable tunnel parameters during hardening have already occurred, it will take longer to produce ice cream products correctly.

[0067] In an advantageous embodiment of the invention, the adhesiveness of the ice cream product is specified as the measured core temperature data.

[0068] In an advantageous embodiment of the invention, the adhesiveness of the ice cream product being measured is a subset of the measured data.

[0069] In this context, the measured data refers to any data measured in an ice cream production line (including ice cream hardening tunnels). The measured data can be any measured core temperature data, measured adhesion data, etc.

[0070] In an advantageous embodiment of the invention, the adjustable tunnel parameters are monitored.

[0071] In an advantageous embodiment of the invention, the adjustable tunnel parameters are monitored and the measured adjustable tunnel parameters are specified.

[0072] In an advantageous embodiment of the invention, the measured adjustable tunneling parameters are a subset of the measured adjustable parameters.

[0073] In this context, the measured adjustable parameter refers to any adjustable parameter, for example, set by an operator in an ice cream production line that includes adjustable tunnel parameters.

[0074] In an advantageous embodiment of the invention, the measured adhesiveness of the ice cream product is stored in a memory as measured adhesiveness data.

[0075] In an advantageous embodiment of the invention, the measured adhesiveness of the ice cream product is stored in a memory as measured adhesiveness data associated with ice cream product type data.

[0076] In an advantageous embodiment of the invention, the measured adhesiveness of the ice cream product is designated as adhesiveness data and is a subset of the measured data.

[0077] In an advantageous embodiment of the invention, the step of measuring the adhesiveness of the ice cream product is stored as adhesiveness data associated with the relevant ice cream product type, as well as optionally further measured data and / or adjustable parameters for further measurement.

[0078] Adhesion data can be stored in associated memory and retrieved for use when production of the same type of ice cream is started later, after other ice cream products have been manufactured and controlled based on other and different adhesion data related to or associated with that type of ice cream product.

[0079] In an advantageous embodiment of the invention, the adhesion data is used in a step of the method to associate the adhesion data with a specific type of ice cream product.

[0080] In an advantageous embodiment of the invention, the adhesion data is used in a step of the method to correlate the adhesion of the ice cream product with the adjustment of the hardening tunnel.

[0081] Advantageously, preserving and collecting measured adhesion over time allows for optimization of hardening tunnel adjustments. The correlation between measured ice cream product adhesion and tunnel parameters or ice cream product type will help ensure more stable production of ice cream products downstream of the hardening tunnel, where adhesion remains within a predefined core temperature interval. This will result in higher ice cream product yields, better quality, and lower costs.

[0082] In an advantageous embodiment of the invention, the ice cream product is further conveyed to a coating, packaging, or any other workstation downstream of the conveyor.

[0083] After measuring the core temperature of the ice cream product, it is advantageous to process the ice cream product further downstream in the production line. The ice cream product can be conveyed to a station for coating the ice cream product. The ice cream can bypass the coating station and be conveyed directly to the packaging station.

[0084] In an advantageous embodiment of the invention, the measured adhesiveness of the ice cream product is automatically applied, at least in part, to the adjustment of the adjustable tunnel parameters.

[0085] In an advantageous embodiment of the invention, the measured adhesiveness of the ice cream product is automatically applied, at least in part, to the adjustment of the adjustable tunneling parameters via artificial intelligence.

[0086] In an advantageous embodiment of the invention, the measured adhesiveness of the ice cream product is automatically applied, at least in part, to adjusting the adjustable tunneling parameters via artificial intelligence, the adjustment being established through supervised machine learning.

[0087] In an advantageous embodiment of the invention, the measured adhesiveness of the ice cream product is automatically applied, at least in part, to adjusting the adjustable tunneling parameters via artificial intelligence, the adjustment being established through unsupervised machine learning.

[0088] In an advantageous embodiment of the invention, the measured data and the measured adjustable parameters are used as training data for the machine learning model of the artificial intelligence.

[0089] In an advantageous embodiment of the invention, the measured data, such as measured core temperature data and / or measured adhesion data, and / or the measured adjustable parameters, such as measured adjustable tunneling parameters, are applied as training data for the machine learning model of the artificial intelligence.

[0090] In an advantageous embodiment of the invention, the measured data and the measured adjustable parameters are combined with data on the definition of ice cream product categories by the artificial intelligence and applied as training data for a machine learning model.

[0091] In an advantageous embodiment of the invention, the measured data, such as measured core temperature data and / or measured adhesiveness data, and / or measured adjustable parameters, such as measured adjustable tunneling parameters, are combined with data on the definition of ice cream product category types by the artificial intelligence and applied as training data for a machine learning model.

[0092] In an advantageous embodiment of the invention, the measured adhesiveness of the ice cream product is automatically measured.

[0093] In an advantageous embodiment of the invention, the measured adhesiveness of the ice cream product is measured manually.

[0094] In an advantageous embodiment of the invention, the adhesion of the ice cream product occurs between the transport surface of the conveyor and the ice cream product.

[0095] In an advantageous embodiment of the invention, the adhesion of the ice cream product occurs between the transport surface and the ice cream product, wherein the transport surface is the surface of a carrier such as a plate, tray, and / or bag, on which the ice cream product is located.

[0096] The carrier may include, for example, a plate, tray, etc. on which ice cream products are carried, and then the transport surface is regarded as the surface of the carrier carrying the ice cream products.

[0097] In an advantageous embodiment of the invention, the transport surface is integrated with the conveyor or a component carried by the conveyor, such as a carrier.

[0098] In an advantageous embodiment of the invention, the transport surface has been coated with, for example, Teflon or other low-adhesion coatings.

[0099] A fast-operation production line will have fewer frozen products, which may mean that the adhesion is too high.

[0100] If the hardened tunnel conveyor needs to run slower to achieve the required adhesion, less product is produced per time interval, and the product may be colder than required for downstream processing, which means excessive energy use.

[0101] Therefore, using a coating can quickly reduce adhesion, which means optimal productivity and energy use.

[0102] In an advantageous embodiment of the invention, the method includes the step of measuring the temperature of the ice cream product.

[0103] In an advantageous embodiment of the invention, the measurement of the temperature of the ice cream product is a measurement of the core temperature of the ice cream product.

[0104] In an advantageous embodiment of the invention, the measurement of the temperature of the ice cream product is a measurement of the surface temperature.

[0105] In an advantageous embodiment of the invention, the method further includes adjusting adjustable hardening tunnel parameters, at least in part, according to the type of ice cream product.

[0106] In an advantageous embodiment of the invention, the measured core temperature and the measured adhesion are used in combination as the basis for manually and / or automatically adjusting the adjustable tunnel parameters.

[0107] The present invention also relates to an ice cream hardening tunnel comprising: an ice cream hardening tunnel conveyor extending through the hardening tunnel; an adhesion measurement system disposed within and / or outside and downstream of the hardening tunnel; and a cooling control system configured to manually and / or automatically adjust adjustable tunnel parameters based on the adhesion measured by the adhesion measurement system.

[0108] In an advantageous embodiment of the invention, the adhesion measurement system is arranged upstream of any optional active ice cream loosener associated with the ice cream hardening tunnel conveyor.

[0109] In an advantageous embodiment of the invention, the hardening tunnel is also associated with a core temperature measurement system arranged inside and / or outside and downstream of the ice cream hardening tunnel.

[0110] In an advantageous embodiment of the invention, the conveyor has a length of at least 200 meters, for example at least 300 meters, or for example at least 400 meters, within the hardened tunnel.

[0111] The present invention also relates to an ice cream production line, comprising: a hardened tunnel, upstream of which are an ice cream product feeder, an automatic ice cream product transfer system, an optional ice cream coater, and an ice cream packaging system.

[0112] In an advantageous embodiment of the invention, the hardened tunnel of the ice cream production line is operated according to a method for controlling the hardened tunnel.

[0113] The present invention also relates to an ice cream manufactured by a method for controlling hardening tunnels.

[0114] The present invention also relates to an ice cream product formed from a coated ice cream article, the ice cream article comprising a coating, and wherein the weight of the coating of the ice cream product has a tolerance of less than + / -15% by weight of the coating, for example, a tolerance of less than 10% by weight of the coating, for example, a tolerance of less than 8% by weight of the coating, for example, a tolerance of less than 5% by weight of the coating, for example, a tolerance of less than 2.5% by weight of the coating, for example, a tolerance of less than 1% by weight of the coating.

[0115] In one embodiment, the present invention relates to an ice cream product manufactured based on an ice cream article hardened by a method for controlling hardening tunnels, wherein the ice cream article includes a coating, and wherein the weight of the coating of the ice cream product has a tolerance of less than + / -15% by weight of the coating, for example, a tolerance of less than 10% by weight of the coating, for example, a tolerance of less than 8% by weight of the coating, for example, a tolerance of less than 5% by weight of the coating, for example, a tolerance of less than 2.5% by weight of the coating, for example, a tolerance of less than 1% by weight of the coating.

[0116] The aforementioned tolerance is preferably based on a batch of cream products continuously manufactured from more than 1,000 ice cream products within an ice cream hardening tunnel, operating according to the invention (i.e., claims 1 to 55). The improved tolerance is due to the fact that the measured core temperature of the ice cream products facilitates more efficient operation of the hardening tunnel, and also because ice cream products with a stable core temperature can now be supplied to a downstream coating unit, which can now be more easily and predictably controlled, since the coating of the ice cream products depends heavily on the core temperature of the ice cream products at the time of coating. If it is too cold, excessive coating will adhere to the ice cream products, and if the core temperature of the ice cream products is too high, at most less coating will be deposited. Attached Figure Description

[0117] Various embodiments of the present invention will now be described with reference to the accompanying drawings, wherein:

[0118] Figure 1 , Figure 1 a and Figure 1 b illustrates the principle of an embodiment of the present invention.

[0119] Figure 2 The principle of an alternative layout for an ice cream hardening tunnel within the scope of this invention is illustrated.

[0120] Figure 3 The downstream of a hardened tunnel controlled within the scope of this invention is shown.

[0121] Figure 4 An implementation scheme focusing on an adhesion measurement system is shown.Figure 3 Close-up view,

[0122] Figure 5 This shows what is now seen from the other side. Figure 3 and Figure 4 A view of the adhesion measurement system.

[0123] Figure 6 It shows Figure 5 A close-up view of the adhesion measurement system.

[0124] Figure 7 It shows Figures 3 to 6 A variation of the adhesion core temperature measurement system,

[0125] Figure 8 It shows Figure 3 A close-up view of an ice cream product transfer system.

[0126] Figures 9 to 12 Different methods for measuring the data and adjusting tunnel parameters in embodiments of the invention are shown.

[0127] Figures 13 to 14 Two different types of control implementation schemes are shown, and in which

[0128] Figures 15 to 17 Different implementations of the control system embodied in the cooling control system are shown.

[0129] Figures 18a to 18b A block diagram illustrating the process of manufacturing ice cream products is shown. Detailed Implementation

[0130] Figure 1 Some key components of an embodiment of the present invention are shown. Further explanation will follow with reference to other accompanying drawings regarding features, operating methods, device configurations, etc.

[0131] Figure 1 An ice cream hardening tunnel HT with an upstream US and a downstream DS end is shown. In this embodiment, the terms upstream and downstream will be used with reference to the hardening tunnel HT unless otherwise stated.

[0132] The Ice Cream Product Positioning System (IIP) is located upstream of the Ice Cream Hardening Tunnel (HT), and the Ice Cream Product Positioning System (IIP) is established to position individual ice cream products (II) on the ice cream channel conveyor (HTC).

[0133] In certain applications, the ice cream product positioning system IIP can also be referred to in the art as a cutter arranged with an extruder, by which the ice cream product is extruded and slightly cut above the surface of the ice cream tunnel conveyor HTC, optionally including the insertion of a stick into the ice cream product. This system and its variations are known and well described in the art.

[0134] Ice cream positioning can be performed by one or more robots or other assemblies, such as an assembly of ice cream product II extruded or cut from an ice cream recipe / product (not shown) positioned upstream of the ice cream positioning system IIP. This part of the process can be performed using equipment / methods already available to those skilled in the art. In some embodiments, ice cream product II may be provided with a stick.

[0135] The ice cream hardening tunnel conveyor HTC extends from the input of the ice cream hardening tunnel HT, passes through the ice cream hardening tunnel HT, and exits from the ice cream hardening tunnel HT, reaching the ice cream product transfer system IITS via the ice cream product adhesion measurement system AMS.

[0136] The purpose of this ice cream product transfer system IITS is to transfer ice cream products II from the ice cream tunnel conveyor HTC via another conveyor FC to other systems in the ice cream production line, such as the coating system IIC, the packaging system IPP, the boxing system IPB, etc.

[0137] Figure 1A illustrates three distinct adhesion zones of the aforementioned ice cream hardening tunnel conveyor. A portion of the hardening tunnel transport surface upstream of the tunnel conveyor exhibits a first type of adhesion, referred here as pre-tunnel adhesion (PRTA), which represents the adhesion generated when the freshly produced ice cream products II are positioned at the tunnel conveyor HTC just before being conveyed into the hardening tunnel HT. As the ice cream products enter the hardening tunnel HT, they gradually harden as they are cooled to temperatures below their initial production temperature. Therefore, temperature development occurs, and the core temperature of the ice cream products gradually decreases through the tunnel, for example, from -5 degrees Celsius to, for example, -18 degrees Celsius, depending on numerous factors. This, along with many other factors, leads to a change in adhesion between the ice cream products and the transport surface, and this adhesion is referred here as tunnel adhesion (TA). Subsequently, the ice cream products II will exit the hardening tunnel HT, and since the ambient temperature is typically higher than the temperature inside the hardening tunnel HT, the adhesion will again be affected to reach even higher or lower temperatures, depending on numerous factors such as ambient temperature, the distance from the exit of the hardening tunnel to the ice cream reaching the ice cream product transfer system IITS, the conveyor belt speed, the type of ice cream product, etc. Tunnel adhesion (TA) and / or post-tunnel adhesion (POTA) can be measured at one or more points as an indication of adhesion, and the measured adhesion of ice cream products can be used as a basis for controlling hardening tunnels, i.e., controlling hardening tunnels by adjusting adjustable tunnel parameters.

[0138] Figure 1 b shows Figure 1 and Figure 1 A variation of system a, in which the product loosener (LOS) is positioned at or just before the ice cream product arrives at the ice cream product transfer system (IITS). When the ice cream product has been loosened from the transport surface, such as from the tray or plate carrying it, allowing it to be lifted or removed from the hardened tunnel conveyor (HTC), the adhesion between the ice cream product and the hardened tunnel conveyor no longer represents what happened in the tunnel, in a manner attractive for controlling the hardened tunnel (i.e., for adjusting adjustable tunnel parameters). After the active loosening of the ice cream product, the adhesion is therefore no longer referred to and understood as the aforementioned post-tunnel adhesion (POTA), but rather as post-loosening adhesion (PA).

[0139] Establishing any practical relationship between the measured adhesion and the conditions occurring in the tunnel is extremely difficult, or even impossible.

[0140] Figure 2The principle of an alternative layout of an ice cream hardening tunnel HT applied according to embodiments within the scope of the present invention is illustrated. The ice cream hardening tunnel HT shown is associated with a hardening tunnel conveyor HTC extending through the ice cream hardening tunnel HT, the conveyor being able to move in the direction indicated by the associated arrow under the control of a cooling control system CCS via an automatically adjustable drive system (not shown).

[0141] In addition, the ice cream hardening tunnel includes an adjustable cooling device (not shown), which is also controlled by a cooling control system CCS, which controls the cooling temperature and optionally also adjustably controls the airflow within the hardening tunnel HT.

[0142] It should be noted that the cooling control system CCS can be a single device or multiple controllers working together. The illustrated cooling control system CCS is communicatively coupled to an operator interface (OI), through which the operator can modify adjustable channel parameters based on the adhesiveness measurement of the ice cream product according to the present invention. Therefore, it should be noted that, according to the present invention, many prior art ice cream hardening tunnels can be controlled using only an addon that measures the adhesiveness of the ice cream product inside or downstream of the hardening tunnel, thereby allowing the operator to effectively cool the hardening tunnel in a timely manner by modifying the adjustable channel parameters.

[0143] At the upstream US end of the ice cream hardening tunnel HT, the hardening tunnel conveyor HTC extends into the hardening tunnel HT. Upstream US of the hardening tunnel HT, ice cream products (not shown) are positioned on the hardening tunnel conveyor HTC via an ice cream product positioning system IIP, which takes the form of four separate stations connected to the mixer MIX, including a freezer F / extruder, a stick inserter, and a cutter. This facilitates the continuous and automatic placement of ice cream products (not shown) on the hardening tunnel conveyor HTC before transport to the ice cream hardening tunnel HT.

[0144] The mixer (MIX) mixes the ingredients related to the recipe of the ice cream product to be produced, and the freezer (F) provides the desired extrusion temperature for the extruder used in the ice cream product positioning system (IIP).

[0145] Inside the ice cream hardening tunnel HT, the hardening tunnel conveyor HTC extends through the hardening tunnel to cool the ice cream product from its temperature upstream of the tunnel to a lower temperature as it leaves the ice cream hardening tunnel HT downstream.

[0146] The length of the hardened tunnel conveyor HTC, the cooling applied by the cooling system (not shown) (including optional internal ventilation), the movement of cold air within the hardened tunnel HT, and the speed of the hardened tunnel conveyor HTC will determine the resulting cooling from a temperature (e.g., -5 degrees Celsius to, for example, -18 degrees Celsius), which is measured as the core temperature.

[0147] Some of these parameters are called adjustable tunneling parameters, and these adjustable tunneling parameters can be adjusted manually and / or automatically.

[0148] The hardened tunnel conveyor HTC then exits the hardened tunnel HT and extends via the ice cream adhesion measurement system AMS and the optional product loosener LOS to the ice cream product transfer system IITS.

[0149] The Ice Cream Product Transfer System IITS is designed to transfer cooled ice cream products (not shown) to other equipment further downstream of the ice cream product production line (not shown). This figure only shows a portion of another conveyor for further transporting ice cream products down to an optional coating, another conveyor suitable for its specific purpose, packaging, boxing, and anything else that may be necessary and related.

[0150] Here, the ice cream adhesion measurement station AMS is located at the downstream end DS near the exit of the ice cream hardening tunnel HT to reduce the impact of environmental conditions (e.g., temperature) on the adhesion measurement of ice cream products transported by the hardening tunnel conveyor HTC or a subset of ice cream products transported by the hardening tunnel conveyor HTC.

[0151] In an advantageous embodiment, the Adhesion Measurement System (AMS) is designed to perform online measurements of the adhesiveness of ice cream products, which means that the measurements are performed without interrupting the movement of the hardened tunnel conveyor (HTC).

[0152] It is important to note that the location of the adhesion measurement system may differ from the indicated location just outside the hardened tunnel HT.

[0153] Therefore, in alternative implementations, if feasible, the adhesion measurement system can thus be integrated with and work together with the ice cream product transfer system IITS, for example, performing the measurement of ice cream product adhesion while transporting ice cream products from the hardened tunnel conveyor to some other conveyor mechanism COND further downstream of the ice cream production line or just before it.

[0154] Another possible way to perform adhesion measurements on relevant ice cream products is to position the adhesion measurement system (AMS) inside a hardened tunnel (HT).

[0155] Another possible way to perform adhesion measurements on relevant ice cream products is to position two or more adhesion measurement systems (AMS) at points inside the hardened tunnel HT and / or outside the downstream DS of the hardened tunnel HT, as described above.

[0156] The measured adhesion can be used as a basis for manual, semi-automatic and / or automatic adjustment of adjustable channel parameters, i.e., from a broader perspective, to adjust the effective cooling performed in the ice cream hardening tunnel based on the measured adhesion of the relevant ice cream products, whether these ice cream products are real ice cream products or imitations of ice cream products.

[0157] The system described above includes several related components shown for illustrative purposes. It goes without saying that the principles of the invention can be applied to other constructions and other designs of the ice cream hardening tunnel HT and related equipment.

[0158] A hardened tunnel comprises one or more heat exchangers, referred to elsewhere as evaporators. If two or more evaporators are used, the hardened tunnel can defrost one of the evaporators while the remaining evaporators are being cooled, thus allowing defrosting of the evaporators to occur while the hardened tunnel is running. The number of active evaporators can be adjusted using the tunnel parameter ATP, if available and desired.

[0159] Figure 3 The downstream output of a hardened tunnel controlled within the scope of this invention is shown. Ice cream hardening tunnel HT, for example, regarding... Figure 1 and Figure 2The ice cream hardening tunnel HT, as explained, has a downstream DS end, which is the outlet of the hardening tunnel HT. The hardening tunnel conveyor HTC extends through this outlet towards the ice cream product transfer system IITS via an optional ice cream loosener LOS. In this embodiment, the hardening tunnel conveyor HTC is implemented to transport ice cream product II on a conveyor plate CP. During operation, the conveyor moves in the direction of the arrow. If a transport surface is referenced, then if such a plate is applied, it will be referenced relative to the surface of the conveyor plate CP. If the conveyor transports ice cream product II directly on the conveyor element, the transport surface should be understood as the surface on which the ice cream product is transported. Therefore, other embodiments of the conveyor are certainly applicable within the scope of the invention, wherein the “loosening” plate or tray is positioned or not positioned on top of the conveyor below, but easily removable plates / trays / etc. are advantageous because they can be easily positioned and removed on the conveyor and are easy to clean in the operating environment. Furthermore, if, for example, the removal plate / tray is specifically designed / formed to carry or hold a specific type of ice cream product (e.g., if the ice cream product is carried in a “pocket”), it is easier to make specification changes. The illustrated implementation includes an adhesion measurement system (AMS), which is placed outside the hardened tunnel (HT).

[0160] In this embodiment, the Adhesion Measurement System (AMS) is designed to perform adhesion measurements on the selected ice cream product II and then interface the results with the operator via a suitable interface (which may be visual, auditory, tactile, etc. (not shown)). This facilitates valuable assistance to the operator in appropriately adjusting the adjustable tunnel parameters of the ice cream hardening tunnel HT, and thereby modifying the effective cooling of the ice cream hardening tunnel HT if the measured adhesion differs from, for example, the expected adhesion predetermined for a specific ice cream product type. If the hardening tunnel HT is in the process of switching from hardening to another ice cream product type, the required adjustments to the adjustable tunnel parameters may be slightly more frequent, as different ice cream product types may require some “major” adjustments during the initial period. It is anticipated that adjustments to the adjustable tunnel parameters can be made at a lower frequency and as “minor” adjustments during subsequent maintenance periods, where the process is running and the adjustments are made solely to maintain a stable state of ice cream product handling. In reality, this stable state is not entirely stable, for example, because frost formation on components within the hardening tunnel affects the effective cooling of the ice cream products carried on the hardening tunnel conveyor. By tracking this “drift,” the process can be adjusted based on the core temperature measured during maintenance periods, and any interruptions in the hardening process can be reduced or even avoided (this drift is usually only detected when the ice cream product is no longer normal, or, for example, if the process itself is negatively affected and physically impacted by the drift).

[0161] It is also noted here that the control of the hardened tunnel in this invention allows for minor adjustments to the adjustable tunnel parameters even when small deviations from the expected adhesion are measured, and when such deviations are detected before subsequent undesirable process conditions, these undesirable process conditions are typically used as the basis for adjusting the adjustable tunnel parameters, thereby reducing or even avoiding the impact of undesirable process conditions.

[0162] It is also noted here that the measured adhesiveness of ice cream products can be used as a basis for automatically adjusting ice cream tunnels.

[0163] Figure 4 This illustrates the focus on the adhesion measurement system AMS. Figure 3 A close-up view.

[0164] Figure 5 It shows Figure 3 and Figure 4The view of the adhesion measurement system, now seen from the other side. The adhesion measurement system AMS shown may include an optional core temperature measurement device (CME) mounted on the movable adhesion measurement system head AMSH. The adhesion measurement system head AMSH can move back and forth in the direction of movement of the hardened tunnel conveyor HTC, indicated by the arrow.

[0165] The core temperature measurement device (CME) includes a core temperature measurement device probe (CMEP) that can move downwards to probe into the ice cream product to be measured, and then move upwards once the probe has been inserted for a sufficient time to obtain a reliable and representative core temperature measurement of the ice cream product.

[0166] In the illustrated embodiment, the conveyor moves continuously in the direction of the arrow, for example, at 20 cm per second, and the adhesion measurement system head AMSH is thus arranged and automatically controlled to follow the movement of the ice cream product as the probe is inserted into the first ice cream product II1 (e.g., the first ice cream product II1 to be measured shown), when the probe is inserted at a measuring point close to the internal portion of the first ice cream product II1 to be measured, and when it leaves the ice cream product in question.

[0167] After the core temperature has been obtained and the probe has been removed from the ice cream product, the AMSH adhesion measurement system head will return to its original position, ready for a new measurement.

[0168] The Adhesion Measurement System (AMS) includes an Adhesion Measurement Device (AME), which includes an Adhesion Measurement Pusher (AMP). The AMP is also mounted on the Adhesion Measurement System Head (AMSH) and moves together with the AMSH while the core temperature is measured by the Core Temperature Measurement Device Probe (CMSEP). This provides the movement of the AMSH, which is synchronized with both the first ice cream product II1 and the second ice cream product II2 on a moving conveyor, thus measuring adhesion simultaneously / at the same time interval. The second ice cream product II2 is (slightly) pushed in the direction of the conveyor's movement by the Adhesion Measurement Pusher (AMP), and the force required to slightly move the second ice cream product II2 in the direction of the conveyor's movement, as indicated by the arrow, is then measured. This measurement can then be used as input for manual and / or automatic adjustments of adjustable tunnel parameters. After invasive core temperature measurement, for example, if the ice cream product is damaged and unusable, the system can further dispose of the tested ice cream product II1. The system can also be designed for the systematic disposal of ice cream products subjected to invasive testing. This treatment can be performed in many different ways within the scope of the invention, for example, by slightly shifting the probe of the tested ice cream product II1 so that the subsequent ice cream product transfer system IITS does not pick up the shifted ice cream product for transfer downstream of the ice cream production line.

[0169] Figure 6 It shows Figure 5 A close-up view of the adhesion measurement system.

[0170] Figure 7 It shows Figure 5 and Figure 6 A variant of the Adhesion Measurement System (AMS) in which the optional core temperature measurement device (CME) now includes an infrared thermometer head (ITMH) for measuring the surface temperature of one or more ice cream products. The measured surface temperature is then converted into a measured ice cream core temperature using data representing, for example, geometry, weight, ice cream type, ambient temperature, and ambient humidity outside the hardened tunnel, all relevant to a specific ice cream product type. Note that this method of measuring core temperature may be less accurate and less suitable for the aforementioned invasive applications of the probe under certain conditions; however, on the other hand, this method of measuring the core temperature of ice cream products may be feasible in specific inventive applications because the control of the invention is related to the relevant ice cream type, and pre-established information about the ice cream type can significantly improve the quality of the core temperature measurement based on the measured surface temperature.

[0171] Figure 8A portion of the system is shown, in which ice cream product II is removed from the hardening tunnel conveyor HTC via an ice cream transfer system IITS. In the specifically indicated embodiment, ice cream product II is held by ice cream product holders IIG with their respective bars, and then ice cream product II is lifted from the hardening tunnel conveyor HTC and transferred to further downstream processing of ice cream products in the ice cream production line, such as coating, packaging, boxing, etc. The hardening tunnel conveyor moves in the direction of the arrow and is then ready for optional further steps to harden new ice cream products positioned on a conveyor upstream of the hardening tunnel HT before re-entering the ice cream hardening tunnel HT. In the currently shown embodiment, the ice cream product may undergo mechanical action via a product loosener LOS before being held by the ice cream product holder IIG. This product loosener can also be referred to as a hammer, as it actually involves mechanical hammering on the conveyor plate CP to mechanically loosen the ice cream product on the conveyor plate. However, it should be noted that in an advantageous embodiment, due to the advanced control of the adhesion of the ice cream product to the conveyor surface based on measurement according to the present invention, the product loosener (LOS) can even be omitted, or at least controlled to hammer only when absolutely necessary, thereby reducing energy consumption and noise, and minimizing the risk that the product loosener may cause the ice cream product to move to a point where the ice cream transfer system may be unable to pick up the relevant items, thus resulting in waste.

[0172] Figures 9 to 12 It shows the relationship with Figure 1 The implementation plan relates to various methods of transmitting the measured data MD and the adjustable parameters MAP of the measurement.

[0173] exist Figure 9 In this process, measured data points (MDs) are established at various points along the ice cream production line, and measured adjustable parameters (MAPs) are collected to track how these adjustable parameters are set. These measured adjustable parameters are read and stored in memory, and can then be applied, for example, through a cooling control system (CCS) to the automatic, semi-automatic, or manual control of the hardening tunnel.

[0174] Figure 10 This demonstrates a method for transmitting the measured data MD and the measured adjustable parameter MAP via an interface to an AI-based control system AI and / or an AI-based monitoring system AI.

[0175] Figures 11 to 12 This paper illustrates one embodiment of several applicable embodiments within the scope of the invention, showing various ways of routing data to and from the cooling control system CCS.

[0176] Figure 13 An ice cream production line according to the present invention is shown (see example).Figures 15 to 17 The settings of the cooling control system CCS or any controller CSY, wherein the measured data MD, in particular, for example, according to Figures 1 to 12 and / or Figures 14 to 17 In any of the above-described embodiments, the measured adhesion data MAD is stored in the memory MEM. The measured data MD (e.g., the measured adhesion data MAD) is obtained by a relevant sensor or any circuit that enables the creation of data related to the control and / or monitoring of the ice cream manufacturing line, particularly data that can preferably be associated with data determining the type of ice cream product to which the measured adhesion data MAD pertains. These measured and stored adhesion data MADs are transmitted to the operator interface OI, facilitating the operator to adjust the adjustable tunnel parameter ATP and transmit these parameters to the cooling control system CCS of the corresponding hardening tunnel HT. Thus, the adjustable tunnel parameter ATP can be adjusted based on the currently measured adhesion data MAD of the ice cream product item II currently being processed in the hardening tunnel HT, and also simultaneously using other relevant measured data MDs as guidance, the measurement preferably guided by a predetermined setpoint of the ice cream adhesion data also stored in the memory MEM. The measured data MDs (including the measured adhesion data MAD) can be visually displayed to the operator and / or displayed via any other suitable interface device (such as audio).

[0177] The comparison between the adhesion data stored at the set point and the adhesion data MAD measured during the running time should preferably be performed for the same type of ice cream product.

[0178] The measurement data can be any of the following, but is not limited to:

[0179] Tunnel temperature (e.g., at various points), tunnel humidity (e.g., at various points), tunnel airflow (e.g., at various points), actual conveyor speed, core temperature of ice cream products, adhesion of ice cream products to the conveyor transport surfaces, quantity of ice cream products in the hardened tunnel, ice cream product rate, ambient temperature outside the hardened tunnel, defrosting amount, temperature of the transport surfaces, condition of the transport surfaces, condition of the ice cream extruder (including temperature, viscosity, rate); tunnel running time, in a broader sense: cooling effect of the tunnel; weight of ice cream products, ice cream product waste, weight of ice cream products coated, temperature of the coating material, feed rate of the coating material, coating rate (how many ice cream products are coated per unit time), coating / immersion time of ice cream products, packaging rate (such as ice cream products packaged per unit time); boxed ice cream products per extruded ice cream product, such as per unit time, and / or any relevant measurements of the ice cream hardening tunnel and remaining ice cream production line.

[0180] Adjustable parameters can be any of, but are not limited to, adjustable tunnel parameters, such as conveyor speed, fan speed, tunnel temperature, tunnel humidity, number of active evaporators, any other settings affecting the cooling effect of the hardened tunnel, air balancing system, pre-cooling of upstream transport surfaces, feed rate, number of ice cream products passing through the feed, etc. In addition to adjustable tunnel parameters, these may also include the speed of the ice cream product transfer system, coating material temperature, coating / immersion time, coating material composition, ice cream product composition, extruder speed, packaging settings, boxing settings, etc.

[0181] Similarly, other adjustable parameters (e.g., adjustable tunnel parameters) can be monitored as measured adjustable parameters (in other words, the measured adjustable parameters in this context would refer to monitored adjustable parameters to reflect the current adjustable settings) and compared with runtime measurement data (if such values ​​exist) that reflect the current actual values ​​associated with such settings.

[0182] An example could be an operator setting the tunnel fan speed to 30 Hz, which is recorded and understood as a measurable adjustable parameter, while the actual runtime measurement of the tunnel fan speed delivered by the fan is, for example, 28.5 Hz and is understood as the measured data.

[0183] The adhesion data stored at setpoints can be provided as target adhesion, adhesion setpoint intervals, adhesion development, etc., whether applicable or practical, as guidance for operators to adjust adjustable tunnel parameters. Therefore, setpoint adhesion data can be provided for certain time periods to help operators make highly optimized adjustments at any time during operation, such as adhesion data related to the initial time period Tinit or adhesion data related to the maintenance time period Tmain.

[0184] Similarly, stored setpoint adhesion data and runtime-measured adhesion data (MAD) can be automatically compared, and an alarm can be set for the operator if process conditions develop in an undesirable manner. Process conditions include, for example, runtime-measured ice cream product adhesion or other parameters such as runtime-measured core temperature of the ice cream product (if measured).

[0185] Figure 14A variation of the invention is illustrated, wherein setpoint adhesion data and runtime measured adhesion data (MAD) are coupled to a cooling control system (CCS) including a memory (MEM) as the basis for automatically adjusting adjustable tunnel parameters (not shown). The algorithm for automatically adjusting the adjustable tunnel parameters can be stored and executed by the cooling control system (CCS) based on the measured adhesion data (MAD); this control is based on a control algorithm relevant to the specific type of ice cream product processed by the hardening tunnel discussed.

[0186] It should be noted that the setpoint core temperature data cited above can also be called target core temperature data, that is, data that states what the target should be for a specific type of ice cream product.

[0187] Of course, if needed, it can still facilitate the operator's over-control of automatic adjustments.

[0188] It should be noted that measurements of adhesion can provide more predictable control guidance than existing technical parameters, because the conveyors for hardened tunnels can be relatively long, typically extending 200 to 600 meters within cooling tunnels, and thus provide a significant delay in response to modifications to tunnel parameters.

[0189] It should be emphasized that automatic control based on measured adhesion can be performed analytically, for example, based on a desired adhesion interval, such as for a given type of ice cream. However, other control algorithms can also be applied within the scope of this invention, particularly by responding to the development of measured adhesion, for example, by means of P control, PID control loop, I control loop, etc.

[0190] Favorable control can also be applied through artificial intelligence, for example by using supervised or unsupervised machine learning, where control is based on measured adhesion as input.

[0191] Artificial intelligence can also be applied to proactively provide alerts or guidance to operators in order to facilitate improved handling of adjustable tunnel parameters.

[0192] Various advantageous control methods have been described, including, for example, control based on PID control loops. However, artificial intelligence-based control can also be applied. Note that various types of machine learning control can be applied. For example, machine learning control can be applied to approximate a nonlinear mapping from measured sensor data (sensor signals) to control signals or actuation commands. In this case, various types of neural network models can be applied, for example. Control can also be treated as a regression problem, where machine learning control can provide control over adjustable tunneling parameters based on minimizing a cost function (e.g., the measured control performance). Furthermore, control can advantageously be based on reinforcement learning. Advantageously, reinforcement learning enables the optimization of control performance over time based on feedback from measurement data and rewards. Furthermore, reinforcement learning is highly adaptable to changes in system conditions, which is advantageous. In summary, non-limiting examples of algorithms that can be used for control include neural networks, genetic algorithm-based control, genetic programming control, reinforcement learning, regression trees, linear regression, and nonlinear regression models, etc.

[0193] Advantageously, machine learning models may be able to adapt to conditions to achieve optimal control, while other classic non-machine learning-based control methods require preset parameters, which may not be well-suited to, for example, changing conditions.

[0194] In an advantageous embodiment of the invention, control is based on a recurrent neural network model. This is advantageous because the recurrent neural network model can learn the dependencies between time steps of the data. Therefore, the model is able to apply control not only based on current knowledge of the measured data, but also based on the sequential dependencies between adjustable tunneling parameters and the actual measured data. This can provide more accurate and robust control.

[0195] Figure 15 A schematic example of a control system CSY is shown, which may be part of the controller of an ice cream production line or part of one of several controllers in an ice cream production line, such as... Figure 2The cooling control system described herein. According to an embodiment of the invention, the control system CSY is based on machine learning. The system includes a machine learning control model MLCM configured to output adjustable tunneling parameters ATP of the hardening tunnel HT, for example, as disclosed in any of the figures and texts included in this application. Sensors SENS may be configured to measure measured data MD (which here particularly includes measured core temperature data MCTD and / or measured adhesion data MAD) and a comparator unit CU. The comparator unit CU is configured to compare one or more received setpoints SP with the measured data MD (e.g., the core temperature received from the sensor SENS). The setpoint SP may, for example, be the desired core temperature and / or adhesion of the ice cream product. The comparator unit CU compares the setpoint with the received measured data MD to provide the machine learning control algorithm with a measurement of the error between the two. The setpoint may, for example, be the core temperature, and the error may, for example, be any measure of difference, including ratios, etc.

[0196] A machine learning control model (MLCM) is configured to determine adjustable tunnel parameters ATP and provide these parameters to control the adjustable tunnel parameters of the hardened tunnel of its associated cooling control system (CCS, not shown). The cooling control system (CCS, not shown) of the hardened tunnel receives the adjustable tunnel parameters ATP from the MLCM and controls the hardened tunnel HT accordingly. The effect of the adjusted tunnel parameters is measured by a sensor that measures measurement data, which may be, for example, the core temperature of the ice cream. The measured data MD (which may include several other types of measurements performed in the hardened tunnel HL, concerning the hardened tunnel HL or concerning the ice cream production line) is received by a comparator unit CU, which compares the measured data MD with a setpoint to calculate the error between the two. In this example, the error is the difference between the measured data and the setpoint, where the setpoint is the core temperature value of the ice cream, and the measured data is also the core temperature value of the ice cream. This difference is received by the machine learning control model MLCM, which can then adjust the adjustable tunnel parameters ATP to minimize the error between the measured data MD and the setpoint.

[0197] Optionally, more than one setpoint can be applied. Thus, the machine learning control model can provide control based on more than one setpoint. Setpoints may include, for example, core temperature, adhesion, hardened tunnel conveyor speed, tunnel temperature, humidity within the tunnel, wind speed, and transport surface temperature.

[0198] In an alternative exemplary embodiment of the invention, the machine learning control model MLCM is a Long Short-Term Memory network. This type of neural network is able to access and utilize long-term dependencies in the sequential data provided to the model. This can advantageously improve the accuracy of the model, for example, by providing control that causes the measured data MD to be very close to the desired setpoint. In particular, compared to models that cannot utilize long-term dependencies.

[0199] The machine learning control model of this embodiment, including an exemplary long short-term memory network model, can be a supervised model, and therefore, the model is trained on training data. The training data can, for example, include a historical dataset comprising measured data MD and the corresponding adjustable tunneling parameter signal ATP. Advantageously, this enables the model to learn the relationship between the adjustable tunneling parameter ATP and the measured data. Optionally, the training data may also include one or more setpoints.

[0200] In another alternative exemplary embodiment of the invention, the machine learning control model can be a reinforcement learning model. In this case, for example, the model is rewarded when an action taken by the model results in the model minimizing the error between the measured data and the setpoint; for example, corresponding to a given reward or a given cumulative reward for the model optimizing the action taken by the reinforcement learning model. In other words, the model receives information (adjustable tunneling parameters) about the system state affected by the actions it determines. Information about the system state can be given, for example, through measurements (e.g., sensor measurements) (e.g., torque-based adhesion measurements). The reward system provides feedback to the agent regarding rewards. Rewards are based on the results of actions determined by the model, and guiding rewards can be understood as providing guidance to improve the model's decision-making strategy, for example, determining adjustable tunneling parameters to optimize the reward. Over time, the reinforcement learning model learns which actions optimize the reward, thereby learning the optimal control strategy.

[0201] Machine learning-based control models are advantageous, for example, because the model can learn system behavior based on data, and therefore can be optimized over time by retraining the model as more and more data is collected. The model is also adaptive, as it can be adapted by training it on different training data. Therefore, the model can be suitable for, for example, providing control over the production of various types of ice cream, and for various production line locations characterized by differences in external operating parameters or conditions, such as different environmental conditions that may affect production.

[0202] Different types of machine learning models can be used for machine learning control models, including, for example, various types of reinforcement learning models, including deep reinforcement learning and Q-learning. Other models that can be used as machine learning control models include one or more of the following reinforcement learning control models: Deep Deterministic Policy Gradient (DDPG) algorithm, Proximal Policy Optimization (PPO), Actor Commenting Algorithm including Flexible Actor Commentator (SAC), and Deep Q-Network (DQN). We note that, according to embodiments of the present invention, genetic programming can also be utilized.

[0203] According to an embodiment of the invention, the Deep Deterministic Policy Gradient (DDPG) algorithm is a model-free, off-policy reinforcement learning method that can be advantageously implemented as a machine learning control model. The DDPG agent is a participant-judge reinforcement learning agent that searches for the optimal policy that maximizes the expected cumulative long-term reward while learning the Q-function and the policy. The algorithm uses off-policy data and the Bellman equation to learn the Q-function and uses the Q-function to learn the policy.

[0204] According to embodiments of the present invention, Proximity Policy Optimization (PPO) can be used as a machine learning control model. PPO can be classified as a policy gradient method for training a policy network of an agent. The policy network is the function used by the agent to make decisions. To train a correct policy network, PPO takes small policy updates (step sizes) so that the agent can reliably reach the optimal solution. Steps that are too large may lead the policy in the wrong direction, thus offering little possibility of recovery; steps that are too small reduce overall efficiency. Therefore, PPO implements a pruning function that restricts the agent's policy updates from being too large or too small. Advantageously, PPO achieves a balance between performance and understanding.

[0205] According to embodiments of the present invention, the Deep Q-Network (DQN) algorithm is a model-free, policy-free reinforcement learning method that can be advantageously implemented as a machine learning control model. The Deep Q-Network agent is a value-based reinforcement learning agent, which trains the evaluator to estimate the expected discount to accumulate long-term rewards when following the optimal policy. DQN can be considered a variant of Q-learning characterized by objective evaluation and experience buffering. DQN can be considered a relatively simple and efficient model. Furthermore, DQN can mitigate data correlation. Essentially, DQN combines the principles of deep neural networks with Q-learning, enabling the agent to learn optimal policies in complex control of reinforcement tunneling, etc. DQN can utilize experience replay, which advantageously helps to decorrelate sequential experiences by storing sequential experiences in a replay memory buffer. This memory buffer is randomly sampled during network updates to break temporal dependencies and stabilize learning.

[0206] The Flexible Actor Commentator (SAC) is an algorithm that optimizes stochastic policies in a way that deviates from the policy, bridging the gap between stochastic policy optimization and DDPG-style methods. While the SAC algorithm may be best suited for continuous action spaces, it can be implemented as a machine learning control model according to an embodiment of the present invention.

[0207] Machine learning control models (e.g., reinforcement learning-based) can take a long time to train, potentially leading to a large amount of product (such as ice cream products) being wasted, as reinforcement learning models are trained by testing different parameters (such as adjustable tunneling parameters) and learning from the corresponding feedback (rewards) given in response to these actions (e.g., adhesion, such as torque-based, etc.), as described elsewhere in this disclosure.

[0208] Optionally, the reinforcement learning control model can be trained using reward shaping and / or imitation learning. Advantageously, in imitation learning, an ice cream-making expert is determining adjustable tunneling parameters to achieve a given desired quality, and furthermore, the expert is evaluating the quality of the produced product, including, for example, adhesion, etc., as described elsewhere in this disclosure, given the determined adjustable tunneling parameters, and providing feedback on whether the quality (adhesion, etc.) matches the desired quality and / or adhesion, etc. The expert can adjust the parameters during production and continue to evaluate the quality, including measurements of adhesion, etc., while adjusting the parameters. The reinforcement learning control model is then able to learn from the expert the parameters that maximize the reward (providing the desired quality, adhesion, etc.). Advantageously, imitation learning can greatly minimize the number of training iterations required before the reinforcement learning control model becomes capable of performing at a level that provides the desired product quality, adhesion, etc. Optionally, the reinforcement learning control model can be trained further without imitation learning to improve the performance of the reinforcement learning model.

[0209] Note that the concept of mimicking adjustable tunneling parameters determined by human experts can be achieved using various types of machine learning, including different types of supervised learning, and thus not just reinforcement learning. However, while reinforcement learning can sometimes be time-consuming to train, reinforcement learning control models often outperform traditional supervised learning algorithms.

[0210] Reinforcement learning models can be trained and operated on a variety of data related to, for example, tunnels and manufactured products, including, for example, external operating parameters of the environment, such as parameters including environmental conditions. Data types that can be used to train machine learning control models, including, for example, external operating parameters, have been described elsewhere, and we note that these data can also be applied to train other machine learning models according to the invention, including reinforcement learning models such as those described above.

[0211] Optionally, training the machine learning control model according to the invention may include using a model of hardened tunnels and the ice they produce, as well as ice adhesion, as a starting point and using it as the first best guess of the system. For example, an analytical model or an empirically determined model. Preferably, the machine learning model can be trained first to replicate or approximate the AI ​​model to become a copy of the mathematical model of the system, and then the machine learning control model that has already approximated the model can be trained based on the training data. This can advantageously minimize the iterations required to train the machine learning control model from the initial guess.

[0212] In an alternative embodiment of the invention, control may be based on a genetic algorithm. The genetic algorithm method can be further advantageously combined with machine learning control methods, including those already described in this disclosure. Advantageously, the genetic algorithm may employ an interactive process to adapt a solution to the control problem, which involves probabilistically selecting the best-fit solution through a set of genetic operators.

[0213] Figure 16 A schematic example of a cooling control system (CCS) that can be implemented to perform automatic control based on a machine learning control model (not shown) is shown. The cooling control system can be implemented using various types of machine learning models, including, for example, those related to... Figure 15 The described model. This particular example illustrates training a machine learning control model using a controller based on measured data and measured adjustable control parameters. Note that other types of hardware can be used to train the machine learning control model of this invention. For example, one or more processors (PUs), memory units (MUTs), including GPUs, CPUs, etc., can be utilized. Further note that various types of hyperparameter optimization techniques can optionally be used to optimize the machine learning control model.

[0214] The controller receives the measured data MD and the measured adjustable / hardened tunnel parameters MAP. The data pairs of measurement data and corresponding measured adjustable tunnel parameters are used as training data, where the measurement data is the input and the measured adjustable tunnel parameters are the output, sometimes also called the target. The measured adjustable tunnel parameters can be obtained by one or more experienced personnel manually controlling them. For example, one or more experienced personnel adjust the adjustable tunnel parameters to achieve a specific setpoint, such as a specific core temperature, and this data can then be stored for use in training the data along with the measurement data. This allows a machine learning control model to model the relationship between the measurement data and the measured adjustable tunnel parameters. By using this type of training data to train the machine learning control model, the model can mimic the control provided by one or more experienced personnel. This training data can be used to train various machine learning models, including artificial neural networks, recurrent neural networks, probabilistic machine learning models, and so on.

[0215] Optionally, the setpoint and / or the error between the setpoint and the measurement data can also be used as training data.

[0216] It should be understood that regardless of the training data used, the architecture of a model can vary when a neural network-type algorithm is used as a machine learning control model; for example, the depth, the number of nodes per layer, and the type of nodes used in each layer. It should also be noted that training can be performed using a variety of numbers of epochs. Furthermore, many types of performance testing methods and measures can be used to evaluate the performance of the machine learning control model.

[0217] It should be noted that the above examples of control algorithms, whether or not they are based on artificial intelligence, are advantageously and preferably relevant to specific types of ice cream products.

[0218] Figure 18a A block diagram of the process along a production line for producing ice cream products is shown. The production line PL comprises multiple workstations located along the line PL. First, different ice cream ingredients are fed into a mixer (technically optional), where the ingredients (a mixture of ice cream components) are mixed. The material from the mixer MIX is then transferred to a freezer SF, where it is processed into an ice cream composition. The mixture is added to the freezer SF, and air is added at the same end of the freezer. The air can also be understood as ice cream components typically supplied to the freezer through a separate dedicated inlet. In the freezer SF step, the input ice cream components (mixture and air) are processed while being cooled and partially frozen, resulting in partial crystallization and / or replacement of the ice cream composition. The ice cream composition is cooled to a temperature below zero degrees Celsius by the freezer SF to obtain the desired ice cream quality with an ice cream foam structure of suitable size and shape. Air is continuously supplied to the freezer SF at its input end. Inside the freezer, the ice cream composition is subjected to shearing, for example, by a churning device in a freezing bottle, to make the ice cream composition softer and less cold for consumption.

[0219] In the next step of the method, the ice cream composition is guided to an ice cream former (ICF), where it is shaped and divided into ice cream products. The ice cream former (ICF) can be an ice cream cutter, where the flow of ice cream composition is guided to an outlet shaped into the desired ice cream product. When the ice cream product type is ice cream on a stick, a stick inserter is typically placed at the end of the outlet of the ice cream former (ICF). At the end of the ice cream cutter, a wire is placed to divide the ice cream composition into ice cream products and allow them to fall onto a conveyor. The ice cream former (ICF) can also be an ice cream filler, where valves divide the flow of ice cream composition. After the ice cream composition is separated by the valves, a piston can be used to push the ice cream into ice cream containers, such as waffle, cookie, or inedible containers.

[0220] Ice cream products are conveyed from the ice cream former (ICF) to the hardening tunnel (HT), where they are cooled. The type of hardening tunnel varies depending on the type of ice cream being manufactured and is specific to each production line. The hardening tunnel can be, for example, as shown below. Figure 3The diagram shows a hardening tunnel in which ice cream products are conveyed on a transport surface. This type of hardening tunnel HT typically includes air ventilation, an evaporator, a heat exchanger, and other components (not shown) related to uniformly controlling the temperature within the hardening tunnel HT. Other types of hardening tunnels may include hardening tunnels where the conveyor comprises a casting form. Hardening tunnels with a casting form conveyor may be circular and rotate about a center in a nearly horizontal plane. Ice cream products are shaped and divided into casting forms on a conveyor belt, then conveyed in a rotary motion. Coolant is applied to the underside of the casting form to harden the ice cream products in the casting form. Another type of hardening tunnel with a casting form can also be used. The casting form is conveyed in a linear direction, and the casting form is connected as a slit in the belt. The slit with the casting form is filled with ice cream products at one end and conveyed in a linear direction with the casting form on top. After the ice cream products are released from the casting, the casting forms form a 180-degree turn at the end of the belt and are conveyed back to the ice cream forming unit. At the ice cream forming unit, the casting form can be refilled with ice cream products. Depending on the specific production of the ice cream product, the number of castings perpendicular to the conveying direction can vary from, for example, 2 to 12 or even more. For two hardening tunnels with castings, cooling fluid can be applied from below to cool the ice cream product by spraying coolant on top and allowing the cooling fluid to flow downwards along the outside of the casting, as in a so-called cascade system. More often, this system is a bath in which cold liquid enters from below and slightly heated fluid flows over the outside of the casting. All three types of hardening tunnels are used to harden and cool ice cream products after the ice cream former. Ice cream products can be conveyed through the hardening tunnel HT for minutes or even hours to ensure a uniform freezing temperature. Adhesion can be established between the ice cream product and the surface on which it is being conveyed through the hardening tunnel HT. Adhesion may also develop through the hardening tunnel due to the cooling conditions. In some production lines PL, the hardening tunnel is optional, and the ice cream product is cooled in the freezer before the ice cream former. Making the freezer sufficiently cool is often a very expensive process, and handling the ice cream composition through the ice cream former is further complicated due to the harder ice cream composition.

[0221] The next step along the ice cream production line is the packing station, where ice cream products are typically packaged in foil. Ice cream products can be placed in longitudinal sheets of foil that are welded together to typically seal one product. The foil is then cut and separated, thus packaging and sealing an ice cream product within the foil. Packing station packs can also be packs where ice cream products are directly packaged in cardboard or cartons without any foil. Packing station packs can also include auxiliary packing station packs where individually foil-sealed ice cream products are packaged into boxes. Ice cream products can be packaged into boxes or containers by hand or robot.

[0222] Along the entire production line PL, one or more sensors (not shown) can be placed at different locations to measure different stations (ice cream forming unit, hardening tunnel, freezer, mixer, coating station, packaging station, ingredient feeder, etc.) and / or ice cream characteristics, ice cream composition properties and / or parameters, and different properties. The sensors can also be wired or wirelessly connected to one or more controllers (not shown) to transmit observed or measured properties, parameters, and / or characteristics to one or more controllers. One or more controllers can also be connected to different stations along the production line PL to adjust different workstations based on measurement and / or observation results. The location of one or more sensor SENS can be used by the controllers for any upstream adjustments to ice cream ingredients, ice cream products, or any parameters related to upstream workstations.

[0223] One or more sensors can be weight sensors, vision sensors, cameras, flow sensors, pressure sensors, temperature sensors, distance sensors, or any other sensors used to observe the characteristics, parameters, or properties of any kind of ice cream. Sensors can also be used to measure parameters of any workstation.

[0224] By along Figures 18a to 18b The different steps of the production line PL shown depict the preparation of ice cream composition ICO from ingredient ICN in the mixer MIX and freezer SF. Ice cream composition ICO is shaped and separated into ice cream products ICI at the ice cream former ICF. Ice cream products ICI are processed through production line PL, where they are refined in the hardening tunnel and packaging station. At the end of production line PL, ice cream products ready for sale are manufactured. This can be a single ice cream product in foil, typically purchased in small shops. Alternatively, the ice cream product can be a box containing multiple foil-wrapped ice cream products available in supermarkets.

[0225] Figure 18b It shows the relationship with Figure 18aThe same embodiment is shown, wherein one or more optional components are added to the ice cream production line PL. An optional ingredient feeder INF can be placed before the ice cream former ICF to mix the ice cream composition from the freezer SF with small pieces of chocolate, berries, cake, caramel, or any other edible substance.

[0226] Figure 18b The diagram also illustrates the placement of one or more optional coating stations (COAs) along the production line (PL) after the ice cream product has left the hardening tunnel (HT). A coating station (COA) can typically be a station that immerses the ice cream product in a warm chocolate bath. The ice cream product is then lifted, with the coated chocolate dripping off, but a new layer is added to it. The ice cream product may also be coated with other edible materials or different types of chocolate. After the initial dip coating, an additional coating may be provided in the form of another layer of chocolate or small pieces of solid chocolate, berries, or any other edible solid.

[0227] Additional optional workstations (not shown) along the production line PL can be any of the following: smart cutter, coating inspection station, serialization, packaging inspection station, manual station, cleaning station, or any other workstation related to the production of ice cream products.

Claims

1. A method for controlling hardened tunnels, comprising: Adjustable tunnel parameters (ATP) are set for the hardened tunnel. Upstream of the hardened tunnel, multiple ice cream products are provided on a transport surface (TP) carried by a hardened tunnel conveyor (HTC). The ice cream product is conveyed through the hardened tunnel on the conveyor, creating adhesion between the ice cream product and the conveying surface. The adhesiveness of the ice cream product is continuously measured within and / or downstream of the hardened tunnel (HT). The tunnel parameters are continuously adjusted based on the measured adhesion.

2. The method according to claim 1, wherein, The ice cream products are transferred from the hardened tunnel conveyor (HTC) to another conveyor downstream of the hardened tunnel conveyor (HTC) via the ice cream transfer system IITS.

3. The method according to any one of the preceding claims, wherein, The ice cream product is transferred from the hardened tunnel conveyor (HTC) to another conveyor downstream of the hardened tunnel conveyor (HTC) via an ice cream transfer system IITS, wherein the ice cream transfer system IITS includes lifting equipment.

4. The method according to any one of the preceding claims, wherein, The ice cream product includes a respective ice cream stick, and wherein the ice cream product is transferred from the hardened tunnel conveyor (HTC) to another conveyor downstream of the hardened tunnel conveyor (HTC) via an ice cream transfer system (IITS), and wherein the ice cream transfer system (IITS) lifts the ice cream product via an ice cream product holder (IIG).

5. The method according to any one of the preceding claims, wherein, The adhesion is measured as the ice cream product is lifted away from the conveyor downstream of the hardened tunnel.

6. The method according to any one of the preceding claims, wherein, The adhesiveness is measured downstream of the hardened tunnel and prior to any optional active loosening of the ice cream product from the hardened tunnel conveyor (HTC) downstream of the hardened tunnel.

7. The method according to any one of the preceding claims, wherein, The tunneling parameters are continuously adjusted based on the adhesiveness of the ice cream product to provide adhesiveness of the ice cream product within adhesiveness intervals.

8. The method according to any one of the preceding claims, wherein, Adhesion was measured as the torque when the ice cream was lifted in its respective stick.

9. The method according to any one of the preceding claims, wherein, Adhesion is measured as the force / torque when the ice cream is lifted, for example, by a gripper and / or a suction device.

10. The method according to any one of the preceding claims, wherein, Adhesion was measured as lifting force.

11. The method according to any one of the preceding claims, wherein, Adhesion was measured as rotational force.

12. The method according to any one of the preceding claims, wherein, Adhesion is measured as displacement force.

13. The method according to any one of the preceding claims, wherein, Adhesion was measured as tilt force.

14. The method according to any one of the preceding claims, wherein, Adhesion is measured as displacement caused by the test force.

15. The method according to any one of the preceding claims, wherein, The test force is a predetermined and clearly defined test force.

16. The method according to any one of the preceding claims, wherein, The step of measuring adhesion is performed inside the hardened tunnel, downstream of the hardened tunnel, or before the ice cream product is released from the conveyor.

17. The method according to any one of the preceding claims, wherein, Before serving multiple ice cream products on the Hardened Tunnel Conveyor (HTC), measurements are taken on the transport surface to indicate its condition.

18. The method according to any one of the preceding claims, wherein, The condition of the transport surface of the hardened tunnel conveyor (HTC) is measured for the transport surface, and the condition is modified based on the measured condition.

19. The method according to any one of the preceding claims, wherein, The condition of the transport surface of the hardened tunnel conveyor (HTC) is measured for the transport surface, and the condition is modified based on the measured condition in the transport surface cooling device / tunnel upstream of the hardened tunnel.

20. The method according to any one of the preceding claims, wherein, The adjustable tunnel parameters may also include any of the following: tunnel temperature, airflow (fan speed), conveyor speed, humidity, air balance, quantity of ice cream products, evaporator defrosting, tunnel defrosting, upstream effective feed rate of ice cream products, and / or any combination thereof.

21. The method according to any one of the preceding claims, wherein, The core temperature is measured by inserting a temperature sensor into the ice cream product, and the adhesiveness is measured by pulling the sensor in while it is placed inside the ice cream product.

22. The method according to any one of the preceding claims, wherein, The step of measuring the core temperature of the ice cream product also includes measuring the tunnel temperature and / or ambient temperature.

23. The method according to any one of the preceding claims, wherein, The step of adjusting the adjustable tunnel parameters is also based on the tunnel temperature and / or the ambient temperature.

24. The method according to any one of the preceding claims, wherein, The continuous measurement of the core temperature of the ice cream product and the continuous adjustment of the adjustable tunnel parameters based on the core temperature of the ice cream product are performed automatically.

25. The method according to any one of the preceding claims, wherein, The measured adhesion of the ice cream product is specified as the measured core temperature data (MAD).

26. The method according to any one of the preceding claims, wherein, The measured adhesion (MAD) of the ice cream product is a subset of the measurement data (MD).

27. The method according to any one of the preceding claims, wherein, The adjustable tunneling parameters (ATP) are monitored.

28. The method according to any one of the preceding claims, wherein, The adjustable tunneling parameter (ATP) is monitored and designated as the measured adjustable tunneling parameter (MATP).

29. The method according to any one of the preceding claims, wherein, The measured adjustable tunneling parameter (MATP) is a subset of the measured adjustable parameter (MAP).

30. The method according to any one of the preceding claims, wherein, The measured adhesiveness of the ice cream product is stored in the memory as Measured Adhesion Data (MAD).

31. The method according to any one of the preceding claims, wherein, The measured adhesiveness of the ice cream product is stored in the memory as measured adhesiveness data (MCTD) associated with ice cream product type data (IITD).

32. The method according to any one of the preceding claims, wherein, The measured adhesion of the ice cream product is designated as Measured Adhesion Data (MCTD) and is a subset of Measured Data (MD).

33. The method according to any one of the preceding claims, wherein, During the measurement step, the adhesiveness of the ice cream product is stored as adhesiveness data associated with the relevant ice cream product type, as well as optional additional measured data (MD) and / or additional measured adjustable parameters.

34. The method according to any one of the preceding claims, wherein, The adhesion data is used in the step of the method of associating the adhesion data with a specific type of ice cream product.

35. The method according to any one of the preceding claims, wherein, The adhesion data is used in the step of the method that correlates the adhesion of the ice cream product with the adjustment of the hardening tunnel.

36. The method according to any one of the preceding claims, wherein, The ice cream product is further conveyed to coating, packaging, or any other workstation downstream of the conveyor.

37. The method according to any one of the preceding claims, wherein, The measured adhesion of the ice cream product is automatically applied, at least in part, to the adjustment of the adjustable tunnel parameters.

38. The method according to any one of the preceding claims, wherein, The measured adhesiveness of the ice cream product is automatically applied, at least in part, to adjust the adjustable tunnel parameters using artificial intelligence.

39. The method according to any one of the preceding claims, wherein, The measured adhesiveness of the ice cream product is automatically applied, at least in part, to adjust the adjustable tunneling parameters using artificial intelligence, the adjustment being established through supervised machine learning.

40. The method according to any one of the preceding claims, wherein, The measured adhesiveness of the ice cream product is automatically applied, at least in part, to adjust the adjustable tunneling parameters using artificial intelligence, the adjustment being established through unsupervised machine learning.

41. The method according to any one of the preceding claims, wherein, The measured data (MD) and the measured adjustable parameters (MAP) are used as training data for the machine learning model of the artificial intelligence.

42. The method according to any one of the preceding claims, wherein, The measured data (MD), such as the measured core temperature data (MCTD) and / or the measured adhesion data (MAD), and / or the measured adjustable parameters (MAP), such as the measured adjustable tunneling parameters (MATP), are used as training data for the machine learning model of the artificial intelligence.

43. The method according to any one of the preceding claims, wherein, The measured data (MD) and the measured adjustable parameters (MAP), combined with the data on the definition of ice cream product types by the artificial intelligence, are used as training data for the machine learning model.

44. The method according to any one of the preceding claims, wherein, The measured data (MD), such as the measured core temperature data (MCTD) and / or the measured adhesiveness data (MAD), and / or the measured adjustable parameters (MAP), such as the measured adjustable tunneling parameters (MATP), are combined with the data defining the ice cream product type in the artificial intelligence and applied as training data for the machine learning model.

45. The method according to any one of the preceding claims, wherein, The measured adhesion of the ice cream product is automatically measured.

46. ​​The method according to any one of the preceding claims, wherein, The measured adhesion of the ice cream product was measured manually.

47. The method according to any one of the preceding claims, wherein, The ice cream product is adhesive between the conveyor surface and the ice cream product.

48. The method according to any one of the preceding claims, wherein, The ice cream product is adhesive between the transport surface and the ice cream product, wherein the transport surface is the surface of a carrier, such as a plate, tray, and / or bag, on which the ice cream product rests.

49. The method according to any one of the preceding claims, wherein, The transport surface is integrated with the conveyor or, for example, a component carried by the conveyor.

50. The method according to any one of the preceding claims, wherein, The transport surface has been coated with, for example, Teflon or other low-adhesion coatings.

51. The method according to any one of the preceding claims, wherein, The method includes the step of measuring the temperature of the ice cream product.

52. The method according to any one of the preceding claims, wherein, The measurement of the temperature of the ice cream product refers to the measurement of the core temperature of the ice cream product.

53. The method according to any one of the preceding claims, wherein, The temperature of the ice cream product being measured is the surface temperature.

54. The method according to any one of the preceding claims, wherein, The method also includes adjusting the adjustable hardening tunnel parameters, at least in part, with reference to the type of ice cream product.

55. The method according to any one of the preceding claims, wherein, The measured core temperature, in combination with the measured adhesion, is used as the basis for manually and / or automatically adjusting adjustable tunnel parameters.

56. An ice cream hardening tunnel, comprising: Ice cream hardening tunnel conveyor (HTC) The ice cream hardening tunnel conveyor (HTC) extends through the hardening tunnel (HT). An adhesion measurement system (AMS) is arranged inside the ice cream hardening tunnel and / or outside and downstream of the hardening tunnel (HT). The cooling control system (CCS) is configured to manually and / or automatically adjust the adjustable tunneling parameters (ATP) based on the adhesion measured by the adhesion measurement system (AMS).

57. The ice cream hardening tunnel according to claim 56, wherein, The adhesion measurement system (AMS) is positioned upstream of any optional active ice cream loosener associated with the ice cream hardening tunnel conveyor (HTC).

58. The ice cream hardening tunnel according to claim 56, wherein, The hardened tunnel is also associated with a core temperature measurement system (CMS) located inside the ice cream hardened tunnel and / or outside and downstream of the hardened tunnel (HT).

59. The ice cream hardening tunnel according to claim 56, wherein, The conveyor has a length of at least 200 meters, for example, at least 300 meters, or for example, at least 400 meters, within the hardened tunnel.

60. An ice cream production line, comprising: Hardened tunnel, Ice cream dispenser upstream of the hardened tunnel, Automated ice cream product transfer system Optional ice cream spreader, Ice cream packaging system.

61. The ice cream production line according to claim 56, wherein, The hardened tunnel of the ice cream production line Operate according to any one of claims 1 to 55.

62. An ice cream manufactured by any one of claims 1 to 55.

63. An ice cream product formed from a coated ice cream article, the ice cream article comprising a coating, and wherein the weight of the coating of the ice cream product has a tolerance of less than + / -15% based on the weight of the coating, for example, a tolerance of less than 10% based on the weight of the coating, for example, a tolerance of less than 8% based on the weight of the coating, for example, a tolerance of less than 5% based on the weight of the coating, for example, a tolerance of less than 2.5% based on the weight of the coating, for example, a tolerance of less than 1% based on the weight of the coating.

64. The ice cream product according to claim 63, wherein the ice cream product is manufactured based on an ice cream article (II) hardened by the method according to any one of claims 1 to 55, wherein the ice cream article includes a coating, and wherein the weight of the coating of the ice cream product has a tolerance of less than + / - 15% based on the weight of the coating, for example, a tolerance of less than 10% based on the weight of the coating, for example, a tolerance of less than 8% based on the weight of the coating, for example, a tolerance of less than 5% based on the weight of the coating, for example, a tolerance of less than 2.5% based on the weight of the coating, for example, a tolerance of less than 1% based on the weight of the coating.

Images