TUNNEL PASTER AND METHOD FOR OPERATING A TUNNEL PASTER

Description

[0001] The invention relates to a method for operating a tunnel pasteurizer with the features of the preamble of claim 1 and a tunnel pasteurizer with the features of the preamble of claim 12.

[0002] Tunnel pasteurizers are a well-known technology used to pasteurize containers holding packaged products. In this process, the containers are transported by a conveyor system through several sequentially successive treatment zones, where they are heated and preferably cooled again by treatment media at different temperatures. For effective pasteurization, it is crucial that the products remain at a sufficiently high temperature for a sufficient duration to ensure a minimum level of pasteurization that achieves good microbial inactivation.

[0003] Different media temperatures are set in the treatment zones, allowing the temperature of the containers to be slowly raised and then preferably slowly lowered again. However, to avoid excessively affecting the taste of beverages or other foods, it is also important to prevent over-pasteurization.

[0004] Consequently, precise control of the media temperatures using a control device is necessary. The actual media temperatures are measured by the control device and compared with the target media temperatures. In case of a deviation, heating and / or cooling systems for the treatment media are adjusted to maintain the target media temperatures as closely as possible.

[0005] For example, DE 10 2005 042 783 A1 discloses a method for controlling the water temperature of the water dispensed for pasteurizing products, taking into account the heat transfer to the products when controlling the water temperature. However, it has been found that with known control methods, undesirable fluctuations occasionally occur between the treatment zones, preventing uniform treatment. This can lead to a reduction in product quality.

[0006] US patent 2014 / 065014 A1 discloses a system and a method for controlling the temperature in a temperature treatment machine for food containers.

[0007] DE 10 2005 042783 A1 discloses a method for controlling water temperature and a tunnel pasteurizer.

[0008] DE 103 10 047 A1 discloses a device and a method for pasteurizing products.

[0009] DE 36 37 661 A1 discloses a method and a device for pasteurizing food products in containers, wherein the number of pasteurization units taken in is calculated for a reference container in each controllable elemental zone.

[0010] The present invention is therefore based on the objective of providing a tunnel pasteurizer and a method for operating a tunnel pasteurizer in which the treatment of the containers is more uniform, the product quality is improved and energy and resource consumption is reduced.

[0011] To solve this problem, the invention provides a method for operating a tunnel pasteurizer with the features of claim 1.

[0012] Advantageous embodiments of the invention are mentioned in the dependent claims.

[0013] By generating initial values ​​for optimization from the actual media temperatures of the treatment zones during container processing, and by using a predictive model to determine the target media temperatures in such a way as to achieve at least a minimum degree of pasteurization, the target media temperatures are coupled via optimization. Consequently, the treatment zones are controlled simultaneously by the optimization process running during treatment, thus preventing vibrations. This results in more uniform treatment of the containers during transport through the treatment zones, thereby improving product quality.

[0014] The tunnel pasteurizer can be located within a beverage processing plant. Specifically, the tunnel pasteurizer can pasteurize the product as it is being filled into the container. "Pasteurization" here can mean that the product is heated to such an extent that any germs it may contain are killed. Preferably, the tunnel pasteurizer is located downstream of a filling line for filling the containers and / or downstream of a capper for sealing the containers.

[0015] The tunnel pasteurizer can be used to pasteurize containers such as bottles, cans, and other receptacles. These containers can be designed to hold gaseous, liquid, solid, and / or pasty products. The products can include beverages, hygiene products, pastes, chemical, biological, and / or pharmaceutical products. The containers can be equipped with a seal to hermetically seal the product from the environment.

[0016] The transport system can include a conveyor belt that moves the containers through the treatment zones. The conveyor belt can be perforated or mesh-like to allow the treatment medium flowing from the containers to pass through to a drain.

[0017] In the treatment zones, the containers can be covered with treatment media, in particular water. Preferably, in a first part of the treatment zones, the containers can be covered with at least one warm treatment medium and heated. Subsequently, in a second part of the treatment zones, the containers can be covered with at least one cold treatment medium and cooled.

[0018] The "actual media temperatures of the treatment zones" can refer to the temperature of the treatment medium in a treatment zone during operation, preferably in a section of pipe before it exits the nozzles for pouring over the containers. "Target media temperatures" can refer to preset values ​​for the media temperatures stored in a memory unit of the control system.

[0019] In each treatment zone, the actual media temperatures can be recorded by at least one temperature sensor and transmitted to the control unit. The control unit can be connected to the heating and / or cooling systems to regulate them.

[0020] The control unit may comprise a microprocessor, a memory unit, one or more analog and / or digital interfaces, and / or a display unit. A machine controller may be or comprise the control unit. The control unit may be configured to at least partially execute the method for operating the tunnel pasteurizer. For this purpose, the method for operating the tunnel pasteurizer may be stored, at least partially, as a computer program in the memory unit or on a data carrier.

[0021] Optimization here can refer to a generally known, universal optimization algorithm, preferably implemented in the control system. The optimization process involves minimizing or maximizing a performance function that preferably determines, based on the media temperatures, the deviation of the expected pasteurization level from the minimum pasteurization level, and then minimizing or maximizing this deviation. The performance function can also take into account the prediction model for the pasteurization level and / or the second prediction model for energy and / or resource consumption.

[0022] The prediction model can determine, preferably calculate, the expected degree of pasteurization as output from the media temperatures as input.

[0023] The degree of pasteurization can refer to the number of pasteurization units (PU). It can also refer to the period of time the product in the containers within the tunnel pasteurizer is heated above a certain temperature threshold. This temperature threshold is in the range of 45°C to 90°C.

[0024] The minimum degree of pasteurization can refer to the degree of pasteurization at which a desired minimum product quality is achieved in the containers. It can also mean that a predetermined microbial count in the product is not exceeded. In the context of the present invention, the minimum degree of pasteurization is a minimum period of time during which the product is heated above the temperature threshold in the tunnel pasteurizer.

[0025] "During container treatment" can mean that the initial value calculations and the optimization itself are performed simultaneously with the container treatment. It can also mean that a loop is continuously executed during treatment, in which the initial values ​​are calculated from the (current) actual media temperatures for each iteration, and the optimization is performed to determine the (new) target media temperatures. This allows the target media temperatures to be continuously determined as a specification for the control system.

[0026] The optimization takes place across at least two of the treatment zones simultaneously.

[0027] This prevents temperature fluctuations between the at least two treatment zones and ensures particularly uniform treatment of the products packaged in the containers. It is conceivable that the optimization could take place across exactly two of the treatment zones or across all of them simultaneously.

[0028] Preferably, in this method, an instantaneous pasteurization level for each container row can be determined, preferably orthogonally to the direction of travel, and then summed to determine the expected pasteurization level. This allows the pasteurization level to be determined with a particularly simple predictive model without high computational effort. In other words, the pasteurization level for each treatment time point of a container row can first be determined individually as an instantaneous pasteurization level. Subsequently, the instantaneous pasteurization levels can be summed or integrated. It is therefore conceivable that the instantaneous pasteurization level for each container row can be determined for several treatment times within a treatment period and then summed over the treatment period.

[0029] Advantageously, the instantaneous degree of pasteurization for each treatment zone can be determined for each row of containers, taking into account the temperature of the treatment medium and at least one heat transfer parameter of the treatment medium to the containers. This allows the degree of pasteurization to be determined even more easily and with significantly less computational effort. Since the treatment medium is, for example, sprayed onto the containers, it typically has a different temperature than the product itself. The at least one heat transfer parameter can be designed to take into account the temperature of the treated containers and / or the product contained therein from one or more medium temperatures of the treatment medium(s). The at least one heat transfer parameter can be a function or a characteristic curve.

[0030] When optimizing target media temperatures, the actual media temperatures are permuted by at least one change value, and a gradient of the expected pasteurization degree is determined using the prediction model. Since the optimization process is more efficient when a gradient is considered, computational power can be saved. "Permuting" here means that the actual media temperatures are changed by the change value to determine the gradient. This change value can be a small value compared to the media temperature. The change value can be in the range of -5°C to +5°C, preferably in the range of -0.5°C to +0.5°C. To determine the gradient, the prediction model is called multiple times with the actual media temperatures modified by the change values, so that the gradient is determined from the resulting change in the pasteurization degree.It has also been revealed that a gradient can be determined analytically by transforming the mathematical models, which further minimizes the computational effort.

[0031] The target media temperatures can be optimized to ensure that a maximum product temperature is not exceeded. This prevents over-pasteurization of the containers. The maximum product temperature can be determined using the predictive model, preferably with the aid of at least one heat transfer parameter. The maximum product temperature can be the temperature at which the product's taste and quality deteriorate. For example, the maximum product temperature could be in the range of 61°C to 67°C.

[0032] The target media temperatures can be optimized such that a maximum temperature difference between two adjacent treatment zones is not exceeded. This results in particularly uniform product treatment. The maximum temperature difference can be the difference between the media temperatures of two adjacent treatment zones and / or lie within a range of 0°C to 25°C, preferably 0°C to 20°C. It can also be the difference between a first product temperature in a first treatment zone and a second product temperature in a second treatment zone adjacent to the first.

[0033] The target media temperatures can be optimized to ensure that maximum energy and / or resource consumption during container processing is not exceeded and / or is minimized. This prevents increased energy and / or resource consumption when the tunnel pasteurizer starts or stops. In the event of a stop, the media temperatures in the pasteurization zones must be lowered to prevent over-pasteurization of the products. When restarting after a stop, the media temperature in the pasteurization zones is then raised again. It is conceivable that, through optimization, a slightly higher degree of pasteurization of the containers is accepted in exchange for reduced energy and / or resource consumption. "Energy and / or resource consumption" can refer to the consumption of the heating and / or cooling systems. This energy consumption can include energy used for heating and / or cooling the containers.Resource consumption can include water consumption, for example of fresh water or cooling water.

[0034] Preferably, a second predictive model can be used to determine and minimize expected energy and / or resource consumption from the target media temperatures, and then compared with the maximum energy and / or resource consumption. This allows for a particularly simple determination of energy and / or resource consumption during optimization, based on the media temperatures.

[0035] Preferably, energy and / or resource consumption can be determined zone by zone or per container row and then summed. This allows energy and / or resource consumption to be determined using a particularly simple predictive model without significant computational effort. In other words, the energy and / or resource consumption for each treatment zone or container row can first be determined individually as zone consumption or container row consumption. Subsequently, the zone / container row consumptions can be summed or integrated. The following explains the calculation methods using zone consumption as an example. The calculation using container row consumption is performed in the same way.

[0036] Advantageously, for each treatment zone, a zone consumption and / or a tank row consumption can be determined, taking into account the corresponding medium temperature, at least one heat transfer parameter of the treatment medium to the tanks, and the heat capacity of the tanks. This allows energy and / or resource consumption to be determined even more easily and with particularly low computational effort.

[0037] The at least one heat transfer parameter can be the same one previously described in relation to the degree of pasteurization. For example, the temperature of the container or the product packaged within it can be determined using the medium temperature and the heat transfer parameter. The temperature of the container can then be used to determine the heating or cooling of the product packaged within the corresponding treatment zone, and subsequently, using its mass and heat capacity, the energy and / or resource consumption can be determined. Additionally, the heat capacity and mass of the container can be taken into account to determine the energy and / or resource consumption.

[0038] Preferably, the target media temperatures can be optimized such that a TAT value (time above temperature) and / or a KP value (killing point temperature) and / or one or more PE values ​​(pasteurization units) are not exceeded. The TAT value is particularly useful for determining the minimum degree of pasteurization. Furthermore, the KP value ensures that pasteurization is carried out at a temperature at which microbial inactivation occurs. Since it is also possible to introduce pasteurization units (PE units) into the packaged product at lower temperatures, the KP temperature can be used to ensure sufficient microbial inactivation. Moreover, the invention provides a tunnel pasteurizer with the features of claim 13 to solve the problem.

[0039] Because the control system is designed to generate initial values ​​for optimization from the actual media temperatures in the treatment zones during container treatment, and to determine the target media temperatures using the predictive model in such a way that at least a minimum pasteurization level of the containers is achieved, the target media temperatures are coupled via optimization. Consequently, the treatment zones are controlled simultaneously by the optimization process running during treatment, thus preventing vibrations. As a result, the containers are treated more uniformly during transport through the treatment zones, improving product quality.

[0040] The control device of claim 12 can be configured to carry out the previously described method for operating the tunnel pasteurizer, preferably according to one of claims 1-11.

[0041] The tunnel pasteurizer or the control device may include the features previously described in relation to the method for operating the tunnel pasteurizer, either individually or in any combination.

[0042] Further features and advantages of the invention are explained in more detail with reference to the following exemplary embodiments. These will show: Figure 1: Exemplary embodiments of a tunnel pasteurizer and a method for operating the tunnel pasteurizer in a top view and as a flowchart, respectively; Figure 2: An exemplary embodiment of a first prediction model for determining the degree of pasteurization as a flowchart for the method from the Figure 1 ; and Figure 3 shows an embodiment of a second prediction model for determining energy and / or resource consumption as a flowchart for the method from the Figure 1 .

[0043] In the Figure 1Exemplary embodiments of the tunnel pasteurizer 1 and the method 100 for operating the tunnel pasteurizer are shown in a top view and as a flowchart, respectively.

[0044] The left side of the Figure 1 The tunnel pasteurizer 1 has several sequentially arranged treatment zones Z1 to Z4, through which the containers 2 are transported in direction T by the conveying device 3. The conveying device 3 is designed here, for example, as a conveyor belt, but can also be any other suitable conveying device. A product has been packaged into the containers 2 and is pasteurized by the tunnel pasteurizer 1.

[0045] During transport through treatment zones Z1 and Z2, containers 2 are sprayed with heated treatment media (water), with the media temperature in treatment zone Z2 being higher than in treatment zone Z1. This gradually heats the containers 2 and maintains them above a minimum temperature of 60 °C for at least 10 minutes. This kills any germs in the containers 2 and pasteurizes the product. Heating devices H1 and H2 are provided to heat the treatment media in treatment zones Z1 and Z2. These devices may include a heater, heat exchanger, or similar equipment.

[0046] The containers 2 are then transported through treatment zones Z3-Z4 and gradually cooled during this process. To achieve this, the containers 2 are sprayed with a cool treatment medium (water), with the medium temperature being lower in treatment zone Z4 than in treatment zone Z3. This allows the containers 2 to be cooled in a controlled and slow manner, enabling them to be transported to further treatment stations downstream of the tunnel pasteurizer 1. Cooling units K3 and K4 are provided to cool the treatment media in treatment zones Z3-Z4. These units can include, for example, a controlled supply of fresh water, cooling devices, heat exchangers, and similar equipment.

[0047] Furthermore, temperature sensors T 1 - T 4 are provided in the treatment zones Z 1 - Z 4 to record the respective actual media temperatures.

[0048] The heating and cooling devices H 1 , H 2 , K 3 , K 4 and the temperature sensors T 1 - T 4 are connected to the control device 4 via suitable connecting lines.

[0049] In the right area of ​​the Figure 1 The control unit 4 is shown, in which the procedure 100 for operating the tunnel pasteurizer 1 proceeds as follows: In step 101, the actual media temperatures of the individual treatment zones Z1-Z4, measured by the temperature sensors T1-T4, are recorded, for example, by means of an interface that acquires an analog or digital signal from the temperature sensors T1-T4. The actual media temperatures are then stored in a storage unit of the control unit 4, which is not shown here.

[0050] In step 102, the actual media temperatures are compared with target media temperatures also stored in the storage unit, whereby a difference between the target media temperatures and the actual media temperatures is calculated.

[0051] In step 103, the heating and cooling units H1, H2, K3, and K4 are then controlled via comparison so that the actual medium temperatures correspond as closely as possible to the target medium temperatures. Control signals are transmitted via the connecting lines to the heating and cooling units H1, H2, K3, and K4, and the heating or cooling output is adjusted to maintain the target medium temperatures as accurately as possible.

[0052] In step 104, during the treatment of container 2, the target media temperatures are adjusted using the following optimization: First, in step 104a, initial values ​​for the optimization are calculated from the actual media temperatures. In other words, the actual media temperatures are set as the starting value for the optimization.

[0053] In step 104b, the initial values ​​and the values ​​discussed below are used to calculate the Figure 2The predictive model 210 described below calculates the expected degree of pasteurization. Optionally, the initial values ​​are used in conjunction with the method described below. Figure 3 The predictive model 220 described calculates the expected energy and / or resource consumption.

[0054] Furthermore, the actual media temperatures (the temperatures of the treatment zones) or the initial values ​​are permuted by a small change value, for example by 0.5°C, and also entered into the prediction model 210 or 220. This determines changes in the degree of pasteurization or energy and / or resource consumption due to the media temperatures affected by the change value, and from this, the gradients of the degree of pasteurization or energy and / or resource consumption are calculated.

[0055] Furthermore, the control unit contains four quality criteria preselected by the operating personnel. These include the minimum degree of pasteurization and, optionally, a maximum product temperature, a maximum temperature difference between two adjacent treatment zones Z1-Z4, and a maximum energy and / or resource consumption. The minimum degree of pasteurization can be specified in the form of one or more pasteurization units (PU), a TAT value, a KP value, or a combination of these calculation methods.

[0056] Using the initial values, the gradients of the pasteurization degree or energy and / or resource consumption and the quality criteria, the target media temperatures are then optimized using a generally known optimization algorithm so that the aforementioned quality criteria are achieved as well as possible.

[0057] The determined target media temperatures are then stored in control unit 4, and steps 101-104 are repeated based on these values, including optimization of the target media temperatures. In other words, steps 101-104 are continuously repeated during the treatment of containers 2 with tunnel pasteurizer 1. It is also conceivable that steps 101-103 and step 104 are executed in parallel.

[0058] By generating initial values ​​for optimization 104 from the actual media temperatures of the treatment zones Z1-Z4 during the treatment of containers 2, and by determining the target media temperatures using the prediction model 210 in such a way as to achieve at least a minimum pasteurization level of the containers 2, the target media temperatures are coupled via the optimization. Consequently, the treatment zones Z1-Z4 are controlled simultaneously by optimization 104 during the treatment, thus preventing vibrations. As a result, the containers 2 are treated more uniformly during transport through the treatment zones Z1-Z4, thereby improving product quality.

[0059] Furthermore, the optional quality criteria prevent overpasteurization, uneven pasteurization due to temperature fluctuations, high energy and / or resource consumption, and excessively low treatment temperatures. This ensures that containers 2 are pasteurized in such a way that the quality of the packaged products is exceptionally high and contamination with unkilled germs is avoided.

[0060] In the Figure 2 The prediction model 210 for determining the degree of pasteurization is shown in a flowchart. It can be seen that in step 211 of the prediction model 210, a media temperature is entered for each of the treatment zones Z1-Z4.

[0061] For each of the treatment zones Z1 to Z4, the product temperature prevailing in the containers 2 is determined in step 212 using at least one heat transfer parameter. This at least one heat transfer parameter is preferably determined experimentally by measurement, for example, by spraying a container with a treatment medium in a test chamber at predetermined temperature steps and measuring the product temperature in the container for each temperature step. Calculation methods are also conceivable.

[0062] Subsequently, for each treatment zone Z1-Z4, the instantaneous degree of pasteurization for each row of containers at each treatment time is determined based on the product temperature. This can be, for example, the input of pasteurization units (PE), which can be determined using methods generally known in the literature (e.g., H.W. Del Vecchio, CA Dayharsh, and FC Baselt: Thermal death time studies on beer spoilage organisms. Proceedings of the American Society of Brewing Chemists, 1951, page 45; Andrew Geoffrey Howard Lea and John R. Piggott, editors: Fermented Beverage Production. 2nd edition. Springer, 2003. Page 379; Carsten Zufall, Karl Wackerbauer: The Biological Impact of Flash Pasteurization Over a Wide Temperature Interval, Journal of The Institute of Brewing Volume 106, Issue 3 (pages 164-168)).

[0063] Subsequently, for each container series, the instantaneous pasteurization levels of one container series are summed up over the treatment period in step 213 and output as the pasteurization level in step 214.

[0064] In the Figure 3 The prediction model 220 for determining energy and resource consumption is shown in a flowchart. It can be seen that in step 221 of the prediction model 220, a media temperature and a current product temperature are entered for each of the treatment zones Z1-Z4.

[0065] For each of the treatment zones Z 1 - Z 4, the product temperature prevailing in the containers 2 due to spraying with the treatment medium is now determined in step 222 using the at least one heat transfer parameter previously described in relation to step 212.

[0066] Furthermore, the temperature difference by which the product heats up or cools down as it passes through the respective treatment zone Z1-Z4 is determined. Using the heat capacity of the product packaged in container 2, the mass of the product filled, and the temperature difference, the energy absorbed or released by container 2 can then be calculated. Since the number of containers currently in each treatment zone Z1-Z4 is also known, for example, by means of a counting device at the entrance of the tunnel pasteurizer 1, the zone consumption required for treatment by a treatment zone Z1-Z4 can be determined. For example, the previously described calculation of the energy and resource consumption for a tunnel pasteurizer is disclosed in WO 2010 / 094487 A1.

[0067] Subsequently, the zone consumptions of all treatment zones Z 1 - Z 4 are summed up in step 223 and output as energy and resource consumption in step 224.

[0068] The stated pasteurization level or the energy and / or resource consumption is, as in relation to Figure 1 As described above, it is used in optimization 104 to optimize the target media temperatures.

[0069] It is understood that the features mentioned in the previously described embodiments are not limited to these specific combinations and are possible in any other combinations.

Claims

1. Method for operating a tunnel pasteuriser (1) with a plurality of sequentially successive treatment zones (Z1 - Z4), wherein containers (2) with a product packed therein are transported by a conveying device (3) through the treatment zones (Z1 - Z4) and thereby are heated with treatment media having different actual media temperatures, are pasteurised and preferably then cooled again, wherein the actual media temperatures are detected by a control unit (4) and compared with target media temperatures, and wherein heating and / or cooling devices (H1, H2, K3, K4) are controlled based on the comparison, characterised in that during the treatment of the containers (2) initial values for an optimisation (104) are formed (104a) from the actual media temperatures of the treatment zones (Z1 - Z4), and the target media temperatures are determined by a prediction model (210) for determining the expected degree of pasteurisation with the optimisation (104) such that at least a minimum degree of pasteurisation of the containers (2) is achieved (104b), wherein the minimum degree of pasteurisation is a minimum period of time during which the product in the tunnel pasteuriser (1) is heated above a temperature threshold, wherein the temperature threshold is in a range of 45°C - 90°C, wherein the optimisation takes place simultaneously over at least two of the treatment zones (Z1 - Z4), wherein when optimising the target media temperatures, the actual media temperatures are permuted by at least one change value and thus a gradient of the expected degree of pasteurisation is determined using the prediction model (210), wherein when determining the gradient, the prediction model is called up several times with the actual media temperatures changed by the change values, so that the gradient is determined from the degree of pasteurisation changed by this.

2. Method according to claim 1, wherein a momentary degree of pasteurisation per container row is determined (212) preferably orthogonal to the running direction and then summed up (213) to determine the expected degree of pasteurisation.

3. Method according to claim 2, wherein for the treatment zones (Z1 - Z4) in each case the momentary degree of pasteurisation per container row is determined (212) taking into account the media temperature of the treatment zone (Z1 - Z4) and at least one heat transfer parameter of the treatment medium to the containers (2).

4. Method according to one of the preceding claims, wherein the change value is in a range from -5°C to +5°C, preferably in a range from -0.5°C to +0.5°C.

5. Method according to one of the preceding claims, wherein the target media temperatures are optimised in such a way that a maximum product temperature is not exceeded.

6. Method according to one of the preceding claims, wherein the target media temperatures are optimised in such a way that a maximum temperature jump between two adjacent treatment zones (Z1 - Z4) is not exceeded.

7. Method according to one of the preceding claims, wherein the target media temperatures are optimised in such a way that a maximum energy and / or resource consumption during the treatment of the containers (2) is not exceeded.

8. Method according to claim 7, wherein an expected energy and / or resource consumption is determined and minimised from the target media temperatures by a second prediction model (220) and compared with the maximum energy and / or resource consumption.

9. Method according to claim 8, wherein the expected energy and / or resource consumption is determined (222) per zone or per row of containers and then summed up (223).

10. Method according to claim 9, wherein for each of the treatment zones (Z1 - Z4) a zone consumption and / or a container row consumption is determined taking into account the corresponding media temperature, at least one heat transfer parameter from the treatment medium to the containers (2) and the heat capacity of the containers (2).

11. Method according to one of the preceding claims, wherein the target media temperatures are optimised in such a way that a TAT value, time above temperature value, and / or a KP value, killing point temperature value, and / or one or more PE values, pasteurisation unit values, are not exceeded.

12. Tunnel pasteuriser (1) with a plurality of sequentially successive treatment zones (Z1 - Z4), with a conveying device (3) for transporting containers (2) with a product packed therein through the treatment zones (Z1 - Z4), wherein the treatment zones (Z1 - Z4) are adapted to heat the containers (2) with treatment media of different actual media temperatures, to pasteurise them and preferably cool them again, wherein a control unit (4) is adapted to detect the actual media temperatures and to compare them with target media temperatures and to control heating and / or cooling devices (H1, H2, K3, K4) based thereon, characterised in that the control unit (4) is adapted during the treatment of the containers (2) to form (104a) initial values for an optimisation (104) from the actual media temperatures of the treatment zones (Z1 - Z4), and to determine the target media temperatures by a prediction model (210) for determining the expected degree of pasteurisation with the optimisation (104) such that at least a minimum degree of pasteurisation of the containers (2) is achieved (104b), wherein the minimum degree of pasteurisation is a minimum period of time during which the product in the tunnel pasteuriser (1) is heated above a temperature threshold, wherein the temperature threshold is in a range of 45°C - 90°C, wherein the optimisation takes place simultaneously over at least two of the treatment zones (Z1 - Z4), wherein when optimising the target media temperatures, the actual media temperatures are permuted by at least one change value and thus a gradient of the expected degree of pasteurisation is determined using the prediction model (210), wherein when determining the gradient, the prediction model is called up several times with the actual media temperatures changed by the change values, so that the gradient is determined from the degree of pasteurisation changed by this.