METHOD FOR CATEGORIZATION OF PACKAGES FOR LOADING A TERMINAL STATION

Abstract

A method for categorizing packages (1) for loading a terminal station (3), in particular a shipping container, the method including: a) acquiring at least one item-specific information for each package (1) of a plurality of packages (1) in a sorter (2) for loading a terminal station (3); b) categorizing the packages (1) based on the respective object-specific information acquired, wherein at least one category from a plurality of categories is assigned for each of the packages (1); wherein, during the categorization, a weighting factor dependent on the object-specific information or on a further object-specific information of the respective package (1) is determined, wherein the object-specific information is subjected to the weighting factor so that a weighted object-specific information of the respective package (1) is obtained.

Claims

1. A method for categorizing packages (1) for loading a terminal station (3), in particular a shipping container, the method comprising: a) Acquiring at least one item-specific information for each package (1) of a plurality of packages (1) in a sorter (2) for loading a terminal station (3); b) Categorizing the packages (1) based on the respective object-specific information acquired, wherein at least one category from a plurality of categories is assigned for each of the packages (1); wherein, during the categorization, a weighting factor dependent on the object-specific information or on a further object-specific information of the respective package (1) is determined, wherein the object-specific information is subjected to the weighting factor so that a weighted object-specific information of the respective package (1) is obtained.

2. The method of claim 1, further comprising: c) Determining a loading sequence in which the packages (1) are to be loaded into the terminal station (3), taking into account the at least one category associated with each of the packages (1); and d) Loading the terminal station (3) in the loading sequence.

3. The method according to claim 1, in which said acquiring of the at least one object-specific information comprises acquiring of a volume and at least one further object-specific information of the respective package (1), and in which, during said categorizing, the weighting factor to be subjected to the volume is determined from the further object-specific information, whereby a weighted volume of the respective package (1) is obtained.

4. The method according to claim 1, wherein the categorizing comprises sorting the packages (1) to one of at least two terminal stations (3) separated from each other, which are reloaded in the loading sequence into the terminal station (3).

5. The method according to claim 4, wherein the reloading of the packages (1) comprises ejecting the packages (1) from at least one of the terminal stations (3) onto a discharge conveyor (11) guided between the terminal stations (3) and a loading station for terminal stations (100).

6. The method according to claim 4, in which the at least two terminal stations (3) are reloaded into the terminal station (3) in the loading sequence after the sum of the weighted volumes of the packages (1) sorted to the terminal stations (3) has reached a receiving volume of the terminal station (3).

7. The method according to claim 1, wherein acquiring the at least one object-specific information comprises acquiring at least one mechanical property for at least a portion of the plurality of packages (1).

8. The method according to claim 1, wherein acquiring the at least one object-specific information comprises generating an image of the package (1), and wherein categorizing comprises matching the generated image with images in a database, each of which is assigned at least one category.

9. The method of claim 8, comprising depositing the generated image in the database, wherein the depositing includes assigning to the image at least the at least one category that, when matched, is assigned to the image in the database that has the least deviation from the image.

10. The method according to claim 1, wherein acquiring the at least one object-specific information comprises acquiring a volume-independent object-specific information, preferably a weight, a damage, a shape, a strength or a source of danger.

11. The method according to claim 1, in which, for said acquiring, the packages (1) are fed into a circulating sorter (2), preferably a recumbent sorter (2), a pocket sorter (2) or a combined recumbent and pocket sorter (2), wherein said acquiring of the at least one item of object-specific information takes place while the packages (1) are being transported in the circulating sorter (2).

12. The method according to claim 1, wherein said acquiring the at least one object-specific information comprises acquiring a respective strength of the plurality of packages (1) or a respective outer wrapper or outer packaging of the plurality of packages (1), wherein the packages (1) are each classified into one of at least two categories of different strength ranges when categorized.

13. The method according to claim 1, in which, during said acquiring of the at least one item of object-specific information, it is detected whether the respective package (1) has reversibly deformable outer packaging or not, the packages (1) being divided during the categorization into packages (1) with reversibly deformable outer packaging and those without reversibly deformable outer packaging.

14. The method according to claim 1, in which, when the at least one item of object-specific information is acquired for at least some of the packages (1) of the plurality of packages (1), at least one further property from the group consisting of weight, volume and dimensions is acquired.

15. The method according to claim 14, wherein the at least one further property from the group of weight, volume and dimensions is detected at least for those packages (1) of the plurality of packages (1) for which the strength of their respective outer wrapper or outer packaging has been detected during said acquiring step, wherein the packages (1) are each classified into one of at least two categories of different strength ranges during said categorizing step.

16. The method according to claim 12, wherein when loading the terminal station (3), the packages (1) of the category of a first strength range are loaded into the terminal station (3) before the packages (1) of the category of a second strength range higher than the first strength range.

17. The method of claim 16, wherein, preferably prior to loading, a first total volume of the packages (1) of the first category and a second total volume of the packages (1) of the second category loaded into the shipping container (100) in the loading sequence are determined as a function of an expected compression of the packages (1) of the second category when loading the packages (1) of the first category onto the packages (1) of the second category.

18. The method according to claim 1, comprising, prior to said acquiring, introducing the plurality of packages (1), and preferably further packages (1), into the sorter (2), wherein the packages (1) are buffered in the sorter (2) and only then the plurality of packages (1) are loaded into the shipping container (100) in the loading sequence, preferably directly, when the loading of the plurality of packages (1) indicates the complete loading of the shipping container (100).

19. The method of claim 18, wherein complete loading of the terminal station (3) is expected when the plurality of packages (1) determined for loading the terminal station (3) has a fill volume equal to or approaching a receiving volume of the terminal station (3), taking into account an expected packing density at the determined loading sequence.

20. The method according to claim 1, wherein a loading condition is detected before loading the terminal station (3), wherein it is preferably detected whether the terminal station (3) is empty.

21. The method according to claim 1, in which a loading state is detected after loading of the terminal station (3), wherein it is preferably detected whether the terminal station (3) has a desired filling level, and wherein, particularly preferably, if the desired filling level is exceeded or not reached, a volume is detected with which the desired filling level is exceeded or not reached.

22. The method according to claim 21, wherein for detecting the loading state, a fill level image of an upper filling opening of the terminal station (3) is generated and the generated fill level image is matched with images in a database to which a loading state is assigned, wherein each loading state is assigned a sum of weighted volumes of packages (1) and/or a plurality of individual weighted volumes of packages (1) and/or at least one volume-independent object-specific information for each of the packages (1) assigned to the loading state.

23. The method of claim 22, comprising depositing the generated fill level image in the database, wherein during said depositing, the fill level image is assigned the loading state which, during the matching, is assigned to the image in the database which has the smallest deviation from the fill level image.

24. The method according to claim 22, wherein the loading state detected by said matching is matched with the sum of the weighted volumes of the packages (1) received in the terminal station (3).

25. The method according to claim 21, further comprising continuously or iteratively adapting an algorithm for categorizing the packets (1), for which purpose the least deviation detected in said matching is minimized by varying the weighting factor and using a thereby obtained varied weighting factor in a further categorizing step of a further packet (1), wherein said adapting of the algorithm for categorizing the packets (1) is preferably performed by means of machine learning.

26. The method according to any claim 1, wherein said acquiring at least one item-specific information comprises detecting damage to at least one of the packages (1), preferably an outer wrapper or outer packaging of the package (1), wherein upon detecting damage for at least one of the packages (1), the respective package (1) is assigned to a damaged package (1) category in said categorizing step, wherein the packages (1) of the damaged package (1) category are assigned to a final position in the loading sequence upon determining the loading sequence.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Further details of the invention are explained with reference to the figures below. Thereby shows:

[0043] FIG. 1 an exemplary embodiment of a sorter;

[0044] FIG. 2 an exemplary embodiment of a loading tower for shipping containers; and

[0045] FIG. 3 an example of an arrangement for loading a shipping container with parcels in schematic representation.

DESCRIPTION OF THE PREFERRED EMBODIMENTS OF THE INVENTION

[0046] FIG. 1 shows an exemplary embodiment of a sorter 2 for carrying out the process. In the present case, the sorter 2 is designed as a cross-belt sorter which, for example, forms a circulating transport loop and has at least one feed for packages 1 to be sorted. As is known in principle from the prior art, the packages 1 can be detected and categorized by sensors on the sorter 2. For example, in addition to sender and address data, physical properties of the package can also be detected, for example dimensions and the weight of the package 1. In one embodiment, it can be provided that still on the sorter 2, in addition to the already mentioned object-specific information, at least one mechanical property is additionally detected for at least part of the plurality of packages 1 and preferably for all of the packages 1. The mechanical property may be, for example, a strength of the package or an outer packaging of the package 1. Accordingly, when categorizing the packages 1 based on the object-specific information, a distinction can be made according to the strength of the packages 1. For example, packages 1 having a substantially solid (cardboard) packaging can be distinguished from packages 1 that are, for example, in foil bags.

[0047] For categorization, the packages 1 of different categories can be presorted into different terminal stations 3. A camera system 4 above the terminal stations 3 can be used to detect a loading state of the terminal stations 3. For example, in the case of the packages 1 packed in usual solid cartons, the bulk and filling behavior of these packages 1 can be inferred from the bulk and filling behavior of the packages 1 occurring in the relevant terminal station 3 when they are poured from the terminal station 3 into the shipping container 100 for loading the shipping container.

[0048] FIG. 2 shows a loading tower 5 for loading a shipping container 100, which has a camera system 6 at its upper end, which is set up to detect the filling state of the shipping container 100 before the shipping container 100 is filled, in particular to determine whether there are still items from a previous sorting process in the shipping container, or whether the shipping container 100 is completely empty and thus available for loading with parcels 1. Alternatively, the camera system 6 can also be provided outside the loading tower so that the shipping containers 100 to be loaded are already checked for complete emptying before they are moved into the loading tower 5.

[0049] After the packages 1 have been categorized and pre-sorted for this purpose, for example, in the manner described above in terminal stations 3, the loading sequence can be recorded with additional consideration of the at least one mechanical property for at least some of the plurality of packages 1. Thereby, at least two of the categories or the packages 1 assigned to the categories may differ in at least one mechanical property. For example, the packages 1 of a first category may have a greater strength than the packages 1 of a second category. For example, the packaging of the packages 1 of the first category may be a substantially rigid packaging, for example a packaging made of cardboard, while the packaging of the packages 1 of the other category may be a soft packaging, for example a foil bag. For achieving a maximum number of packages 1 that can be loaded into the shipping container, it may be provided that the packages 1 with the soft packaging are loaded into the shipping container 100 before the packages 1 of the category of packages 1 with hard packaging. As a result, the loading of the packages 1 with hard packaging onto the packages 1 with soft packaging results in a compression of the packages 1 with soft packaging and thus in a compression of the packages 1 with soft packaging, thereby increasing the number of packages received in the shipping container 100.

[0050] In addition, the bulk and packing behavior of the packages 1 with fixed packaging in the terminal station 3 can be used to infer the bulk and packing behavior of the packages 1 in the shipping container when they are reloaded into the shipping container 100. Also, this information can be used to load the highest possible number of packages 1 into the shipping container without fear of overfilling the shipping container 100. In particular, the safety discounts taken into account in the prior art to prevent overfilling of the shipping container, which must be avoided at all costs, with respect to the number of packages 1 loaded into the shipping container 100 no longer have to be observed, since process-safe loading of the shipping container 100 is achieved on the basis of the categorization of the packages 1.

[0051] FIG. 3 shows a schematic diagram of an arrangement for loading a shipping container 100 with parcels 1 for carrying out the method. The arrangement has a sorter 2, which is designed as a cross-belt sorter. A dimensioning weighing system (DWS system) 7 is provided for recording object-specific information. The DWS system 7 can, for example, be set up to determine the outer dimensions of the package 1 for volume determination in addition to the weight. The DWS system 7 may further be arranged to detect damage to the package 1 or a wrapper of the package 1. The determination of the outer dimensions of the package 1 as well as the determination of possible damages of the package 1 may be determined based on an image and suitable image processing. For generating the image, the DWS system 7 may comprise an optical camera system.

[0052] The DWS system 7 is connected via a data link to a control system 8, which receives the object-specific information determined by the DWS system 7. The control system 8 may have an image memory 9 or be connected to an image memory 9 via another data link. The control system 8 may further be arranged for machine learning or may be connected to a separate machine learning system 10 via a data interface. The DWS system 7 may be directly connected to the machine learning system 10 via a data interface if the machine learning system 10 is not part of the control system 8.

[0053] The machine learning system 10 or the control system 8 is arranged to categorize the packages 1 based on the acquired object-specific information. The machine learning system 10 may be further configured to determine damage or other characteristic properties of the packages 1 based on the object-specific information captured via the DWS system 7. For determining the categorization, the machine learning system 10 may make use of an image memory 9 that holds a database of reference images with at least one associated categorization. The machine learning system 10 and/or the control system 8 can be set up to store images captured by the DWS system 7, which have been categorized with the aid of the machine learning system 10 by matching reference images of the image memory 9, in the image memory 9 with assignment of the categorization.

[0054] Depending on the categorization or independently of it, the packages 1 can be presorted to one of the two terminal stations 3. The terminal stations 3 may—but need not—be provided for separating packets 1 that differ from each other in at least one assigned category after categorization. However, it may also be provided that the two terminal stations 3 receive parcels 1 that have been assigned the same category or categories during categorization, so that the two terminal stations 3 merely represent separate buffer stores for storing the parcels 1 prior to loading the shipping container 100.

[0055] During categorization, a weighting factor may be determined to be applied to an actual volume of the package 1 determined by the DWS system 7. The weighting factor may be arranged to take into account an expected packing volume of the particular package 1 when the package 1 has been loaded into the shipping container 100. The packing volume of the package 1 may depend on its dimensions, its strength, and/or other object-specific properties. For example, a soft package 1, such as a foil bag, may have a packing volume that is substantially less than its actual volume. Thus, it may be taken into account that soft packages 1 may occupy spaces between solid and/or cuboid packages when loaded into the shipping container 100, for example, and thus in effect and in the limiting case even occupy no additional volume. Similarly, particularly small but solid packages 1 may have a small packing volume because they may occupy spaces between solid and cuboid packages. Finally, solid and bulky packages 1, for example where one edge length is substantially greater than at least one other edge length of the package 1, may have a packing volume after loading into the shipping container 100 that is greater than their actual volume. In particular, this may relate to elongated packages 1 and flat packages 1.

[0056] After the sum of the weighted volumes of the packages 1 in the two terminal stations 3 has reached a for volume of the shipping container 100, the terminal stations 3 or the packages 1 received therein can be reloaded into the shipping container 100. For this purpose, the terminal stations 3 can be discharged onto a discharge conveyor 11. From the discharge conveyor 11, the parcels 1 are introduced into the shipping container 100, for example via a filling opening at or near the top of the shipping container 100.

[0057] In order to further increase the process reliability of the fill-level-optimized filling of the shipping container 100, a camera system 6 or other sensor system can be provided that detects the fill state, in particular the empty state, of the shipping container 100 before the shipping container 100 is filled.

[0058] Similarly, the same camera system 6 or a second camera system may be configured to capture a fill state of the shipping container 100 after the shipping container 100 has been filled. For this purpose, for example, an image of the shipping container 100 or of the filling opening of the shipping container 100 can be captured via the top side of the shipping container 100. By comparison with reference images in an image memory 9, it can be determined to what extent the optimum fill level of the shipping container 100 has been achieved. The image of the shipping container 100 stored in the image memory 9 can be linked to the individual weighted volumes and, if applicable, other properties of the packages 1 in the shipping container 100.

[0059] By comparing the determined fill level and by relating the fill level to the weighted volumes linked to the fill level via the image, an optimization of the loading process of the shipping container 100 can be achieved. From a plurality of fill level images associated with respective weighted volumes, machine learning can be used to detect regularities that lead to underfilling or overfilling of the shipping container 100. For example, it may be recognized that the proportion of small and/or compressible packages 1 may be increased if there is a certain proportion of bulky packages 1 that form teaching spaces that can fill the small and compressible packages 1. This may result in the weighting factor of small and/or compressible packets 1 being further decreased.

[0060] The features of the invention disclosed in the foregoing description, in the drawing as well as in the claims may be essential for the realization of the invention both individually and in any combination.