Title of Invention

A METHOD FOR EVALUATING THE QUALITY OF PRINTED MATTER PRODUCED BY A PRINING PRESS OR PRINTING MACHINE

Abstract

This invention relates to a method for evaluating the quality of printed matter produced by a printing press or printing machine, with the printing machine producing several copies of the same printed matter, comprising the method steps of; providing an inspection system having an image sensor adapted to create an image data signal in response to sensing the printed copies; selecting a quantity of copies from the produced copies of the printed matter; evaluating said image data for the copies in said selected quantity with regard to at least one error type selected from a group of different error types comprising a color error, an intensity error, a contour error or a positioning error, where, within the selected quantity of copies, an error of a particular error type detected on at least one of the copies is evaluated in relation to at least one error of a different error type detected on the same copy or on a different copy. Classifying the printed matter as being of good or poor quality based on the evaluation, wherein said selected copies define a common capture of image data and wherein all errors are evaluated relative to one another as detected from the image data of the same capture.

Full Text

The invention relates to a method for evaluating the quality of printed matter produced by printing press or a printing machine with the printing machine producing several copies of the same printed matter. Print images generates by a printing machine are checked for print since a long time by the operating personnel of the printing machine during a running production, either visually or with the help of optical auxiliary agents. According to the assessment of the operating person, a classification takes, i.e. a categorization of the assessed print products in a group of print products with prior laid-down features, i.e. certain error features that were the object of the previous inspection. The total quality of the checked print products is classified in a part quantity or grade with a good quality and a part quantity or grade with a bad quality, i.e. not usable or marketable quality, whereby the print image of the print products to be assessed is judged as either good or as bad, i.e. as defective. Assessment of the quality of a print product by a printing machine by the operating personnel is subject to extensive fluctuations, as the assessment depends on the judging capacity and particularly the knowledge and experience of the assessing person, and as a result varies from person to person. Nowadays, camera systems are increasingly being used in the printing industry for different applications, e.g. in inspection systems, web observation systems or registration measuring systems, whereby these systems are arranged either in a printing machine or in a machine processing print material. These systems carry out their functions, for example, 'inline', i.e. during the running production of the print product to be used, which poses a significant challenge on account of the large data quality supplied by a camera system and the fast process sequence in production of the print product for the respective camera system and an image processing system evaluating its image data. The problem becomes more acute if the print product has spectral-photometric features or identification features that are difficult to identify, and in a quality control a reliable assessment is required even for these identification features in spite of the usually high transportation speed of the print product in the short time that is available. Furthermore, valuable print products, i.e. in the production of currency notes, security bonds or certificates, each individual identification feature of the print product has to be subjected to a test. At the same time, due to economic reasons, there is the requirement that particularly in high-valued print products, e.g. in the production of currency notes or security bonds, precisely because of their high material costs and production costs, the quantity of wastage has to be kept as less as possible, as long as it is justifiable on the basis of a prior laid-down quality standard. In the camera systems mentioned above, often electronic image sensors are used for taking pictures, particularly colour cameras with at least one image sensor consisting of a CCD-chip, whose light-sensitive pixel gives out an output signal corresponding to the colour scanned in the observation zone, e.g. in three separated signal channels, i.e. the colour channels at least for the colours red, green and blue. There is the need to evaluate the output signal of a photographing unit, i.e. image data of the picture taken by the photographing unit, with an image processing system connected to the photographing unit in such a way, that a need-based, balanced assessment of the quality of the print product produced by a printing machine can take place. For assessing the quality, the print product is preferably tested for different criteria. From the post-published document DE 103 35 147 A1 we know of a method for determining the condition of bank notes in which data of at least two different properties of the bank notes are evaluated, in which the data of at least two different properties of each bank notes are linked with one another and the condition of the bank note is derived from the linked data of different properties. It can also be foreseen that an average value for each of the different properties is determined for a quantity of bank notes in order to determine the condition of the quantity of bank notes for the respectively different properties, or that an average value for the linked properties for a quantity of bank notes is determined in order to determine the total condition of the quantity of bank notes. The similarly post-published document DE 103 14 071 B3 relates to a methods for qualitative assessment of a material with at least one identification feature, whereby with an electronic image sensor at least one colour image is scanned of the identification feature, whereby the image sensor directly or indirectly provides at least one first electrical signal correlated to the colour image, whereby an evaluation device connected to the image sensor evaluates the first electrical signal, whereby from at least one reference image a second electrical signal is obtained and stored in a data storage, whereby a second electrical signal has for at least two different properties of the reference image respectively a rated value for the first electrical signal, whereby the first signal is compared with at least two rated values contained in the second electrical signal, whereby in the comparison at least the colour image of the identification feature is tested for a colour variation from the reference image and the identification feature is tested for association to a certain grade of identification features or tested for a definite geometric contour or for a relative arrangement with respect to at least another identification feature of the material. The material could be a bank currency note or a security bond. In any case, it has to do with testing of the material, i.e. testing of a single piece with which at least one identification feature of the concerned material is checked with respect to certain criteria in different but independently conducted test sequences parallel to one another. From the document DE 102 34 086 A1 we know of a method for signal evaluation of an electronic image sensor in the sample identification of image contents of a test body, in which the categorisation of the test body to a particular grade of a test bodies is decided. In this method, the content of an image scanned by the test body is evaluated on the basis of an associative function formed on the basis of methods of fuzzy logic, whereby even several associative functions can be linked with one another to a super-ordained associative function. From the document DE 102 34 085 Al we know of a method for analysing colour variations of images scanned by an image sensor, whereby the image signal received by the image sensor is analysed pixel-wise. From the document DE 101 32 589 A1 we know of a method for qualitative assessment of printed material with at least one identification feature, in which an image of the material to be assessed is scanned by an image sensor, and for this image the geometric contour and/or the relative arrangement of several identification features among one another is evaluated in an evaluating unit. It is the task of this invention to create a method for assessing a quality of a print product produced by a printing machine, in which errors occurring in the production of several copies of these print products are assessed in a balanced manner. This task is fulfilled by the invention with the help of the features mentioned in claim 1. The advantages that can be achieved with the help of the invention are mainly, that the assessment of the quality of print product produced by a printing machine takes place in a very balanced manner on a broad basis, because each detected error is not assessed singularly but in the context of other identified errors, because a holistic assessment of all errors that have occurred in a selective quantity of copies takes place in such a way, that the errors are assessed in relation to one another, through which in the final result the yield of copies of the print product classified as marketable or at least worthy of further processing gets increased. The method thus increases productivity and cost-effectiveness in the production process of the print products. A required quality standard is ensured and unnecessary wastage is avoided. As samples from the selected quantity of produced copies of the print product is subjected to scanning by an image sensor generating common image data, there cannot be any position differences between the detected errors, i.e. errors in their respective location data, because the obtained image data is evaluated pixel-precise, so that in the calculations for assessing the quality of samples of the print product produced in the printing machine, corrections in the determined positions of the detected errors can be dispensed with, which could however be necessary if errors are determined by multiple sensors that are positioned differently with respect to the samples of the print product to be tested. Therefore, it is a special advantage of the suggested solution, that all the errors to be assessed in relation to one another can be detected from the image data of the same scan. Errors identified in a produced print product are weighed in relation to their topology, e.g. combined in a super-ordained, multi-dimensional associational function and assessed in a combined viewing of all detected errors on the basis of a preferably need-based- parameter-able classification threshold. The method can also be utilized to evaluate the assessment obtained from the image data with respect to a gradual variation in the quality of produced print products. A gradual variation in quality of produced print products can be identified before it grows into defects causing large wastage. The method is particularly suited for assessing the quality of a high-valued print product whose production is expensive, e.g. in valuable print product, e.g. a bank currency note or a security bond. A design example of the invention is depicted in the accompanying drawings and described in details below. The following are shown: Fig.1. A schematic depiction of an inspection system; Fig.2. A part of the method in a signal flow diagram; Fig.3. A depiction of a first aggregated associative function; Fig.4. A depiction of second aggregated associative function; Fig.5. A depiction of a parametric second aggregated associative function. An inspection system used as a model for assessing the quality of a print product produced by a printing machine has one or more colour-lines cameras 01 coupled with one another, as shown in fig. 1, or an image scanning unit 01 designed as colour surface camera 01, that scans a print image 03 lit up by a lighting unit 02, whereby a print image 03 has been generated with a printing machine on a printing material (not shown) consisting of paper. The image data of the individual colour channels determined by the image scanning unit 01 from the picture of print image 03 are evaluated in an image processing system 04. The output of the result takes place, for example, on a monitor 06 connected to the image processing system 04. Inputs, e.g. parameters to be essentially conveyed to the image processing system 04 for its calculations, are fed through a keyboard 07 connected to the image processing system 04. The image scanning unit 01 is arranged in the printing machine in such a way that with each scan the respective print image of several samples of the print product produced in this printing machine is determined. The printing machine is preferably designed as a rotary printing press, especially as a printing machine printing in offset method, in a steel plate relief method, silk screen method or in a hot-press method. If the printing machine is designed as a sheet-fed offset machine, it should be ensured that the sheet can be inspected even at a machine speed of say 18000 sheets per second. If the printing substance to be printed on is a material track, then the inspection system should be in a position to subject the quality of samples of the print product that are guided through the printing machine at a machine velocity of 15 m/sec. to inspection of single pieces. Errors occurring in the production of the print product, e.g. a bank currency note, can be categorised for certain types of errors, e.g. a) colour error, if at a certain position of the print material a wrong colour has been printed; b) error of intensity, if the correct colour tone has been printed at a particular position of the printing substance, but however not in the desired correct colour intensity; c) contour errors, if the print image or an identification feature of the print image is at least partly defective in its outline, i.e. particularly incomplete; or d) layout errors, if a mask thread or any other identification feature of the print image is missing or appearing in a wrong location. The error types can once again the categorised with respect to certain properties, namely whether the defect of a particular defect type occurs in a series of several samples of the print product produced in a printing machine, e.g. as single error or as multiple error. Also colour defect and intensity defect can be classified and evaluated with respect to the respective error magnitude, i.e. with respect to the area-wise extent of the defect. Thus the quality of the print product at least with respect to certain types of defects and/or a defect quantity and/or a defect magnitude can be assessed. On account of the production method applied in a printing machine it can be assumed that in several sample of the print product printed one after the other, the occurring printing defects occur column-wise relative to the printing cylinders of the printing mechanism of the printing press, i.e. the errors get repeated on the print substance on a line in its movement direction through the printing mechanism, by which a further property of an error can be defined. If required, the mentioned error types and/or properties of the errors can be supplemented with further error features. Particularly for conducting the method for assessment of quality of a print product in a machine processing the print material and connected to the printing press, it should also be considered as a side-condition that an inspection of the print material can take place in a so-called half-sheet evaluation or even alternatively only half-wise. A starting situation for the method for assessing the quality of a print product could consist of the following: that several inspection channels i with i = 1 to imax, here e.g. with imax = 4 correspond to the four error types - colour error, intensity error, contour error and layout error- are foreseen, that for each individual sample of print product the error quantity M should be assessed M = 1 to Mmax or the error magnitude N with N = 1 to Nmax pixel of the image sensor, and that for several printed samples of the print product following one another, occurring print errors the number K of the errors m content in a column s should be considered as K = 1 to Kmax and the application or non- application of the half-sheet evaluation should be considered as yes/no decision. The method foresees that the four inspection channels i, the error quantity M or the error magnitude N and the number K of the errors m contained in the same column s should be fuzzified. A defuzzification for assessing the quality of a print product can consist of a simple evaluation of an integer value L obtained from the method, in that it is checked whether the integer value L obtained from the method is greater than a set threshold value Lmax, i.e. L > Lmax by setting the threshold value Lmax follows the fixing of a degree, from which the produced print product can fuzzified as good or as bad, i.e. defective, i.e. with the threshold value Lmax the quality standard required for the print product is fixed. All errors and/or properties to be assessed in relation to one another are detected from the image data of the same scan of the image sensor, which is why a coordination of the image data with respect to the location of a detected error and/or a detected peculiarity is not required. A part of a sequence of this method has been depicted as an example in fig. 2 in a signal flow diagram. The signal shows a hierarchic structure of the method. The fuzzification can foresee that the inspection channels i are arranged linearly in a first associative function uc, e.g The error quantity M is similarly allocated linearly in a second associative function uf, whereby the error quantity M is preferably limited to a maximum number Mmax of the error M, in that the detected errors m with the maximum number Mmax of the errors m can be weighed as a weighing factor. As a second associative function µx one then obtains The method for assessing the quality of a print product seeks to conjunctively aggregate the first associative function uc and the second associative function ux, i.e. to link both the associative functions µc; µf multiplicatively with one another. The multiplication of both associative functions µc: µf gives a new first aggregated associative function µg1, which can be depicted according to the example described here as follows: Fig. 3 shows a graphic depiction of a first aggregated associative function µgl, whereby as example 4 inspection channels i and for the error quantity the value Mmax = 20 have been selected. The first aggregated associative function µgl has a value range between 0 and 1. Even the number K of the errors m contained in a column s can be fuzzified, once again preferably in a linear allocation, so that under the knowledge that in the column a number Ns of successive printed samples of the print product are evaluated, a third associative function us can be set up as us = with s The third associative function us can similarly be conjunctively aggregated with the first associative function us and/or second associative function uf. For example, by means of a conjunctive aggregation of all three associative functions uc; uf; us one obtains a second aggregated associative function µg2 that can be depicted as follows: For the sake of simplicity, in the three associative functions µc; µf; µs linear allocations were made for their respective elements. Of course, depending on the requirement, for one or more of the associative functions µc; µf; µs also non-linear allocations are possible. Fig. 4 shows a graphic depiction of this second aggregated associative function µg2, whereby as an example 4 inspection channels i, for the error quantity M the value Mmax = 20 and for the number Ns of the successive printed samples the value Ns = 6 were selected. Like the first aggregated associative function µgl, the second aggregated associative function µg2 has a value range between 0 and 1 as given on the Y-axis of the diagram. The linear allocations selected here as examples are clearly identifiable. The second aggregated associative function µg2 is a multi-dimensional, here four- dimensional function, in which for its depiction the Y-axis of the diagram has been used twice, mainly for depicting the number Ns of successive printed samples of print product per column s and for depicting the value range of this second aggregated associative function ug2. The double utilization is made possible by the superimposition of the individual samples of the print product per column s with a respective inspection channel i, whereby a block size shown in the diagram gets enlarged with each edition of a further inspection channel i. According to the depiction of the second aggregated associative function µg2 in fig. 4, for its value of µg2 = 0.3 a threshold value Lmax is defined through a horizontal surface parallel to the basic surface of the diagram, whereby the surface forms a classification threshold Lmax. Depending on the respective application, i.e. the respective required quality of the print product to be produced, the classification threshold Lmax is preferably set for ug2 in the range of 0.2 to 0.4. From the example shown in fig. 4 it is clear that in the parameters selected here as model for error detection, with only one single inspection channel i, i.e. i = 1, even for an error quantity M of 15 errors m, a sample of the print product to be tested for its quality is still assessed as good. Only during error detection with two inspection channels i, i.e. i = 2, and an error quantity M of 10 errors m per sample of the print product to be tested, a printed sheet, assuming that Ns = 6 samples of the print product in a certain column s are arranged on the print sheet, is assessed to be of bad quality and preferably removed from the production flow. The second aggregated associative function µg2 is parameter-able in an extension to the extent that a weight-age g with respect to the inspection channel i can be controlled. In this case, for the second aggregated associative function µg2 one obtains the following depiction: µg2 = with i Fig. 5 shows a graphic depiction of a parameterized second aggregated associative function ug2, in which as an example 5 inspection channels i, for Mmax the value Mmax = 20, for Ns the value Ns = 6 and for the inspection channels i the weightage g of g = 0.3 have been selected. The classification threshold Lmax was again fixed at µg2 = 0.3. Similarly, in the method for assessing the quality of a print product, the error quantity M can be substituted by the error magnitude N, or the error magnitude N can be taken in as a further criterion. The method described for assessing the quality of a print product means in the application that not each individual error detected on a printed sheet should lead to the fact that this printed sheet should be removed as wastage. Rather, each individual detected error is assessed in its context, whereby with the help of mathematical means, particularly by applying method of fuzzy logic, the gravity of each error is weighed and/or assessed particularly in alternating relationship in other detected errors and/or in proportion to other detected errors. Accordingly, a holistic assessment of all errors takes place which have been defined within the quantity of samples of the print product printed on a particular sheet, whereby the errors detected within the selected quantity are assessed in their respective relation to one another. The assessment of errors in their respective relation to one another is favourable, in that all errors to be assessed are almost simultaneously determined by the same image scanning unit 01 and all information required for assessing the quality of the print product can be taken from the image data corresponding to the scan. For example, the risk in errors bank currency notes produced in the steel-plate relief offset method is comparatively high; however even the material costs and the total production costs of this print product are relatively high. With the help of the described method, in the actual printing process a preliminary selection with respect to the printed sheet can be made. Sheets that do not exceed the number of errors laid down in the classification threshold Lmax are fed to a machine that will further process the sheet, whereby each sample of the print product printed on the respective sheet can be subjected once again to an individual test. Such a machine connected to the printing press could be a cutting unit, particularly a cutting unit for individually separating the samples of the print product printed on each sheet, which have already formed a number-wise restricted quantity of samples for assessment of their quality. Such a number-wise restricted quantity of samples could be in a few tens or even a few hundreds or more samples of the print product. In the production of the print product, due to the successive sequence of the produced samples of the print product, several such number-wise equal batches can be selected one after the other in the production flow for quality test. Thus a fixed number of associatively produced samples can be combined to a batch of samples, whereby successively several batches of samples are formed. All produced samples are preferably allocated to one of these batches. From each of these batches also an image of their respective sample is made in order to subject the produced samples of the print product to a flawless assessment of their qualities. Each sheet having several copies of the print product, e.g. several bank currency notes can be subjected to a further quality tests, in that during the post-processing those copies of the print product which had been earlier classified as good quantity are removed, that either reveal very big errors or a particularly high number of errors. As in the preliminary test the entire sheet is not being classified as wastage, the yield of the produced print product increases. At the same time, the post-processing does not have to bear the load of sheets in which strong errors were not detected during pre-sorting. The additional evaluation of the assessment obtained from the image data with respect to a gradual variation in the quality of produced print product takes place by means of a link with a data of at least one machine sensor. Such a machine sensor could be a vibration recorder on a machine frame of the printing press. In a printing press printing in the (wet-) offset method, the machine sensor can also be designed as sensor controlling the feed of the wet agent. In a printing press printing in the (wet) offset method or in a steel- plate relief method, it may be appropriate to measure the temperature of a tempering agent tempering the forming cylinder of a printing press, especially a cooling agent cooling the cylinder, with the help of a sensor to take the measured data of this sensor into account additionally in the quality test of the print product produced in the printing press. In a printing press printing in the steel-plate relief method it could also be meaningful to additionally monitor the power consumption a wiping unit removing the ink overflow from the steel-plate with a machine sensor and to consider the information derived from the measured signal of the machine sensor about a too high or too low wiping in the quality test of the print products produced by the printing press. In the result, the errors detected from the common picture in the print image of the print products to be produced are assessed in their relation to one another, whereby the assessment thus obtained can be additionally linked to the information of at least one further machine sensor in a control unit carrying out the evaluation, in order to especially identify at an early stage any variation, especially gradually setting in variation in the quality of the produced print product. From the measured signals of the at least one additional machine sensor, the control unit can obtain the information that the printing machine is for example in a print-technically critical operating condition, so that it is probable that errors causing wastage in a short time manifest themselves on the sample of the produced print products. Already now the control unit can intervene in the printing process, in that at least one unit of the printing press influencing the printing process is automatically post-guided by the control unit in order to bring the printing press back from its print-technically critical operating condition to its proper operating condition. Thus a control process or a regulating process evaluating measured signals of the machine sensors serves the purpose of early detection of negative influences relevant for the printing process, whereas the assessment obtained from the print image of the produced print products especially confirms the adherence to quality specifications and, if required, documents it in the sense of a quality proof. On the other hand, depending on the assessment of the quality obtained from the print image of the produced print products, those aggregates of the printing machine can be post-regulated that are in a critical operating condition, whereby each of these units influencing the printing process has a machine sensor monitoring these units, whereby the control unit determines at least one unit negatively influencing the printing process on the basis of the detected errors and/or the relevant measured signals of the respective machine sensors and alters the setting of the at least one determined unit till such time as the assessment of the quality of the print products obtained from the print image of the produced print products again reaches the classification level of good. In this case, in conjunction with the assessment obtained from the print image of the produced print products, settings of units of the printing machine with the allied machine sensors are checked regarding their relevance with respect to their quality of the print product to be produced and, if required, automatically altered by the control unit for fulfilling the quality specifications. List of reference signs 1 Image scanning unit, colour lines camera, colour surface camera 2 Lighting unit 3 Print image 4 Image processing system 05 6 Monitor 7 Keyboard g weightage i, imax inspection channel m errors M, Mmax error quantity N, Nmax error magnitude Ns number of copies per column K, Kmax number of errors per column L numerical value Lmax threshold value, classification threshold s, smax column µc associative function, first µf associative function, second µs associative function, third µg1 aggregated associative function, first µg2 aggregated associative function, second. WE CLAIM 1. A method for evaluating the quality of printed matter produced by a printing press or printing machine, with the printing machine producing several copies of the same printed matter, comprising the method steps of: - providing an inspection system having an image sensor adapted to create an image data signal in response to sensing the printed copies; - selecting a quantity of copies from the produced copies of the printed matter; - evaluating said image data for the copies in said selected quantity with regard to at least one error type selected from a group of different error types comprising a color error, an intensity error, a contour error or a positioning error, where, within the selected quantity of copies, an error of a particular error type detected on at least one of the copies is evaluated in relation to at least one error of a different error type detected on the same copy or on a different copy; characterized by comprising: - classifying the printed matter as being of good or poor quality based on the evaluation, wherein said selected copies define a common capture of image data and wherein all errors are evaluated relative to one another as detected from the image data of the same capture. 2. The method as claimed in claim 1, wherein the image data are captured with an image sensor that detects colors. 3. The method as claimed in claim 1, wherein the evaluation derived from the image data is analyzed with regard to a slowly building deviation in the quality of the produced printed matter. 4. The method as claimed in claim 1, wherein the copies of the printed matter are produced in a sequence. 5. The method as claimed in claim 4, wherein copies of the sequentially printed matter are evaluated with regard to their quality by columns. 6. The method as claimed in claim 1, wherein a numerically limited quantity of copies is selected out of the copies of printed matter that are produced. 7. The method as claimed in claim 1, wherein the quality of the copies belonging to the selected quantity of copies of the printed matter to be evaluated is classified by an overall evaluation of all of the errors detected within the selected quantity of copies. 8. The method as claimed in claim 1, wherein the severity of each error is evaluated relative to the other detected errors using methods of fuzzy logic. 9. The method as claimed in claim 1, wherein the types of errors are each fuzzified in a classification function (µc; µf; µs). 10.The method as claimed in claim 9, wherein an aggregated classification function (µg1; µg2) is formed by an aggregation of classification functions (µc; µf; µs) that fuzzify at least two different error types. 11. The method as claimed in claim 10, wherein at least two classification functions (µc; µf; µs) are conjunctively aggregated to the aggregated classification functions (µg1; µg2). 12. The method as claimed in claim 10, wherein the aggregated classification function (µg2) is formed at least four dimensionally. 13. The method as claimed in claim 9, wherein at least one of the classification functions (µc; µf; µs) relates to a linear classification. 14. The method as claimed in claim 9, wherein at least one element in at least one of the classification functions (µc; µf; µs) is weighted with one parameter (g). 15. The method as claimed in claim 9, wherein the aggregated classification function (µg1; µg2) is evaluated with regard to a classification threshold (Lmax). 16. The method as claimed in claim 15, wherein the classification threshold (Lmax) for the evaluation of the printed matter as belonging to a quantity of copies that has been classified as good or poor is set at a value. 17. The method as claimed in claim 16, wherein the classification threshold (Lmax) is set at a value between 0.2 and 0.4. 18. The method as claimed in claim 1, wherein the method is performed in the printing press or in a machine processing the printed copies of the printed matter. 19. The method as claimed in claim 1, wherein an established number of sequentially produced copies are respectively combined into a quantity of copies. 20. The method as claimed in claim 19, wherein several quantities of copies are formed one after the other. 21. The method as claimed in claim 20, wherein all produced copies are assigned to one of these quantities of copies. 22. The method as claimed in claim 21, wherein, for each of these quantities, a capture is produced of its respective copies. 23. The method as claimed in claim 1, wherein the evaluation of the quality is made by a comparison of the image captured by the inspection system with at least one reference image. 24. The method as claimed in claim 1, wherein the evaluation of the quality occurs during the ongoing production process of the printing press. 25. The method as claimed in claim 1, wherein the evaluation of the quality occurs in the ongoing production process of a machine processing the printed copies of the printed matter. 26. The method as claimed in claim 24, wherein a quantity of copies of the printed matter that has been classified as poor is removed from the production process. 27. The method as claimed in claim 1, wherein the printed matter is printed in an offset printed method, in a steel engraving printing method, in a serigraphy printing method, or in a hot embossing method. 28. The method as claimed in claim 1, wherein copies of the printed matter are printed on several printed sheets. 29. The method as claimed in claim 28, wherein the copies of the printed matter printed on the printed sheet are evaluated with regard to the quality of their copies at a machine speed of up to 18,000 sheets per hour. 30. The method as claimed in claim 1, wherein the copies of the printed matter are printed on a material web. 31. The method as claimed in claim 30, wherein the copies of the printed matter printed on the material web are evaluated with regard to their quality at a machine speed of up to 15 m/s. 32. The method as claimed in claim 1, wherein the selected quantity of copies of the printed matter is presorted by its classification with regard to a subsequent process step. 33. The method as claimed in claim 32, wherein individual copies of the classified quantity of copies of the printed matter are subjected to an individual examination in the subsequent processing step. 34. The method as claimed in claim 3, wherein the analysis of the evaluation derived from the image data with regard to a slowly building deviation in the quality of produced printed matter occurs by correlating it with a measurement signal of at least one machine sensor. 35. The method as claimed in claim 34, wherein a control device keeps the printing press in an operating state that is proper with regard to printing technology or returns it to such an operating state by evaluating the measurement signal from the at least one machine sensor. 36. The method as claimed in claim 1, wherein the evaluation derived from the printed image of the produced printed matter documents adherence to quality standards. 37. The method as claimed in claim 3, wherein, in connection with the evaluation derived from the printed image of the produced printed matter, the settings of aggregates of the printing press are checked for their relevance with regard to the quality of the printed matter to be produced and changed by the control device in order to adhere to quality standards. 38. The method as claimed in claim 4, wherein the characteristic of the error relates to a number of errors in sequentially printed copies. 39. The method as claimed in claim 1, wherein the characteristic of the error relates to the presence of an individual error or multiple errors. 40. The method as claimed in claim 1, wherein the characteristic of the error relates to its respective error magnitude. 41. The method as claimed in claim 1, wherein the printed copies of the printed matter are inspected in a half-sheet evaluation.

Documents:

01003-kolnp-2006 abstract.pdf

01003-kolnp-2006 claims.pdf

01003-kolnp-2006 correspondence others.pdf

01003-kolnp-2006 description (complete).pdf

01003-kolnp-2006 drawings.pdf

01003-kolnp-2006 form-1.pdf

01003-kolnp-2006 form-2.pdf

01003-kolnp-2006 form-3.pdf

01003-kolnp-2006 form-5.pdf

01003-kolnp-2006 international publication.pdf

01003-kolnp-2006 international search authority report.pdf

01003-kolnp-2006 pct form.pdf

01003-kolnp-2006-correspondence-1.1.pdf

01003-kolnp-2006-form-18.pdf

1003-KOLNP-2006-CORRESPONDENCE.pdf

1003-KOLNP-2006-EXAMINATION REPORT.pdf

1003-KOLNP-2006-FORM 18.pdf

1003-KOLNP-2006-FORM 26.pdf

1003-KOLNP-2006-FORM 3.pdf

1003-KOLNP-2006-FORM 5.pdf

1003-KOLNP-2006-FORM-27-1.1.pdf

1003-KOLNP-2006-FORM-27.pdf

1003-KOLNP-2006-GRANTED-ABSTRACT.pdf

1003-KOLNP-2006-GRANTED-CLAIMS.pdf

1003-KOLNP-2006-GRANTED-DESCRIPTION (COMPLETE).pdf

1003-KOLNP-2006-GRANTED-DRAWINGS.pdf

1003-KOLNP-2006-GRANTED-FORM 1.pdf

1003-KOLNP-2006-GRANTED-FORM 2.pdf

1003-KOLNP-2006-GRANTED-SPECIFICATION.pdf

1003-KOLNP-2006-OTHERS.pdf

1003-KOLNP-2006-REPLY TO EXAMINATION REPORT.pdf

abstract-01003-kolnp-2006.jpg