EP3967495A1 - Système et procédé de commande pour machines d'impression permettant de régler et de surveiller les paramètres relatifs au séchage, à la migration et/ou à la réticulation - Google Patents

Système et procédé de commande pour machines d'impression permettant de régler et de surveiller les paramètres relatifs au séchage, à la migration et/ou à la réticulation Download PDF

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Publication number
EP3967495A1
EP3967495A1 EP20195498.9A EP20195498A EP3967495A1 EP 3967495 A1 EP3967495 A1 EP 3967495A1 EP 20195498 A EP20195498 A EP 20195498A EP 3967495 A1 EP3967495 A1 EP 3967495A1
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EP
European Patent Office
Prior art keywords
data
printing
drying
parameters
crosslinking
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Application number
EP20195498.9A
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German (de)
English (en)
Inventor
Heinz AUMÜLLER
Michael SCHEFTNER
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Hubergroup Deutschland GmbH
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Hubergroup Deutschland GmbH
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Priority to EP20195498.9A priority Critical patent/EP3967495A1/fr
Publication of EP3967495A1 publication Critical patent/EP3967495A1/fr
Withdrawn legal-status Critical Current

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
    • B41F—PRINTING MACHINES OR PRESSES
    • B41F33/00—Indicating, counting, warning, control or safety devices
    • B41F33/0009—Central control units
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
    • B41F—PRINTING MACHINES OR PRESSES
    • B41F23/00—Devices for treating the surfaces of sheets, webs, or other articles in connection with printing
    • B41F23/04—Devices for treating the surfaces of sheets, webs, or other articles in connection with printing by heat drying, by cooling, by applying powders
    • B41F23/0403—Drying webs
    • B41F23/0406—Drying webs by radiation
    • B41F23/0409—Ultraviolet dryers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
    • B41F—PRINTING MACHINES OR PRESSES
    • B41F23/00—Devices for treating the surfaces of sheets, webs, or other articles in connection with printing
    • B41F23/04—Devices for treating the surfaces of sheets, webs, or other articles in connection with printing by heat drying, by cooling, by applying powders
    • B41F23/0403—Drying webs
    • B41F23/0406—Drying webs by radiation
    • B41F23/0413—Infrared dryers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
    • B41F—PRINTING MACHINES OR PRESSES
    • B41F23/00—Devices for treating the surfaces of sheets, webs, or other articles in connection with printing
    • B41F23/04—Devices for treating the surfaces of sheets, webs, or other articles in connection with printing by heat drying, by cooling, by applying powders
    • B41F23/0403—Drying webs
    • B41F23/0423—Drying webs by convection
    • B41F23/0426—Drying webs by convection using heated air
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
    • B41F—PRINTING MACHINES OR PRESSES
    • B41F23/00—Devices for treating the surfaces of sheets, webs, or other articles in connection with printing
    • B41F23/04—Devices for treating the surfaces of sheets, webs, or other articles in connection with printing by heat drying, by cooling, by applying powders
    • B41F23/044—Drying sheets, e.g. between two printing stations
    • B41F23/045—Drying sheets, e.g. between two printing stations by radiation
    • B41F23/0453—Drying sheets, e.g. between two printing stations by radiation by ultraviolet dryers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
    • B41F—PRINTING MACHINES OR PRESSES
    • B41F23/00—Devices for treating the surfaces of sheets, webs, or other articles in connection with printing
    • B41F23/04—Devices for treating the surfaces of sheets, webs, or other articles in connection with printing by heat drying, by cooling, by applying powders
    • B41F23/044—Drying sheets, e.g. between two printing stations
    • B41F23/045—Drying sheets, e.g. between two printing stations by radiation
    • B41F23/0456—Drying sheets, e.g. between two printing stations by radiation by infrared dryers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
    • B41F—PRINTING MACHINES OR PRESSES
    • B41F23/00—Devices for treating the surfaces of sheets, webs, or other articles in connection with printing
    • B41F23/04—Devices for treating the surfaces of sheets, webs, or other articles in connection with printing by heat drying, by cooling, by applying powders
    • B41F23/044—Drying sheets, e.g. between two printing stations
    • B41F23/0463—Drying sheets, e.g. between two printing stations by convection
    • B41F23/0466—Drying sheets, e.g. between two printing stations by convection by using heated air
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
    • B41F—PRINTING MACHINES OR PRESSES
    • B41F33/00—Indicating, counting, warning, control or safety devices
    • B41F33/0036—Devices for scanning or checking the printed matter for quality control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
    • B41F—PRINTING MACHINES OR PRESSES
    • B41F33/00—Indicating, counting, warning, control or safety devices
    • B41F33/02—Arrangements of indicating devices, e.g. counters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
    • B41F—PRINTING MACHINES OR PRESSES
    • B41F33/00—Indicating, counting, warning, control or safety devices
    • B41F33/16—Programming systems for automatic control of sequence of operations
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
    • B41P—INDEXING SCHEME RELATING TO PRINTING, LINING MACHINES, TYPEWRITERS, AND TO STAMPS
    • B41P2233/00—Arrangements for the operation of printing presses
    • B41P2233/10—Starting-up the machine

Definitions

  • the invention relates to a control system for printing presses for setting and monitoring parameters relevant to drying, migration and/or crosslinking for pigmented and unpigmented printing inks such as printing inks and toners, coatings, primers and laminating adhesives, and a method for controlling printing press parameters which control drying, migration and/or crosslinking of the applied materials. Furthermore, the invention relates to a computer-readable medium and a computer program comprising control instructions for the method mentioned.
  • Optimum drying and curing of layers of printing ink or varnish as well as primers or lamination adhesives, ie coating materials in printing processes, and their controllability is essential for the production of high-quality printed products.
  • the coating materials mentioned can be cured or dried physically and/or chemically, for example by crosslinking.
  • drying can be carried out by evaporating solvents using thermal air dryer units or by absorbing or penetrating solvents into the printed substrate.
  • chemical drying and crosslinking processes the hardening or drying of oxidatively hardening printing inks or paints can take place through oxidation with the oxygen in the air.
  • Another example of chemical crosslinking reactions occurs when using 2K paints or varnishes that are mixed with a hardener (second component) to form a polymeric, three-dimensional network during chemical curing.
  • a hardener second component
  • Such 2K systems can consist, for example, of polyol-isocyanate combinations, or of epoxy-amine systems.
  • the control instructions of the control system can be output to one or more UV lamps or electron beam dryers.
  • the hardening or drying can be carried out by process combinations from the drying mechanisms mentioned.
  • a variety of dryer units can be used depending on the types of drying. For example, IR radiators, warm air dryers, UV radiators, EBC (electron beam hardening) radiators, microwaves or lasers are used for drying in printing processes.
  • IR radiators warm air dryers
  • UV radiators UV radiators
  • EBC (electron beam hardening) radiators microwaves or lasers
  • a large number of processes are known for the production of printed products. These processes can be divided into the following known groups: gravure printing processes, relief printing processes including flexo printing or letterpress printing processes, offset printing processes, screen printing processes, pad printing processes, toner-based digital printing processes and inkjet printing processes.
  • gravure printing processes relief printing processes including flexo printing or letterpress printing processes
  • offset printing processes screen printing processes
  • pad printing processes toner-based digital printing processes
  • inkjet printing processes inkjet printing processes.
  • printing processes such as offset printing require the operating personnel to be highly qualified and, because of their complexity and/or process-related fluctuation parameters, make the reproducibility of printed products more difficult.
  • Drying and curing parameters are typically adjusted manually by an operator in offset printing systems or processes. Based on empirical values, an operator can, for example, change the power, position or number of radiators or other dryer units. Manual and person-dependent adjustments are mostly based on the empirical values of the respective operator and therefore cannot be standardized. Different approaches can lead to different results in the quality of the printed products and/or to instability and unpredictability in the printing process.
  • the radiation or drying power of the printing machine is often regulated in such a way that it is in excess used and/or that printing is performed at low speed. Setting too high a radiation or dryer output on the printing press, however, results in high energy consumption and/or high emissions of pollutants such as ozone or solvents and/or a high level of waste heat, which can result in undesirable heating of the press room. Strong heating can also change the tack and viscosity of printing inks and/or varnishes, which can have a negative impact on the printing process.
  • the dimensional stability and/or processability of substrates is also temperature dependent.
  • Another goal is to reduce both the energy consumption for drying and crosslinking processes. Energy savings allow for better press profitability and lower production costs. Another goal is to reduce pollutant emissions to an unavoidable minimum. Another goal is to optimize the control process in such a way that the service life of the dryer units used, which are associated with high initial investment costs, such as UV lamps or ESH emitters, for example, is extended. At the same time, there should be no loss of efficiency due to printing machines that produce too slowly.
  • the invention relates to an optimization or control system for printing machines for setting and monitoring parameters that are crucial for drying, migration and/or crosslinking for pigmented and unpigmented printing inks, varnishes, primers and/or laminating adhesives
  • the control system comprises: an input unit for accepting input data comprising operating data and order data of a printing machine, a central processing unit for receiving the input data and a storage unit for storing the input data and/or information about at least one printed product.
  • the central processing unit is designed to determine at least one reference value for the drying and/or crosslinking quality based on the input data stored in the memory unit and the stored information using at least one predictive analysis technique.
  • the input unit is designed to accept measurement data.
  • the control system has at least one sensor and/or an input interface for acquiring the measurement data.
  • control system is characterized in that the central processing unit has a self-learning synchronization module which is designed to compare the specific reference value continuously or at regular intervals with current measurement data or with a comparison variable determined using the measurement data, whereby depending on a deviation at least a reference value at least one process parameter relevant to drying, migration and/or crosslinking can be calculated by means of the synchronization module and the at least one process parameter can be output to at least one printing press and/or an operating unit of the printing press.
  • a self-learning synchronization module which is designed to compare the specific reference value continuously or at regular intervals with current measurement data or with a comparison variable determined using the measurement data, whereby depending on a deviation at least a reference value at least one process parameter relevant to drying, migration and/or crosslinking can be calculated by means of the synchronization module and the at least one process parameter can be output to at least one printing press and/or an operating unit of the printing press.
  • At least one reference value can be determined using a predictive analysis technique, which can be compared with current measurement data or with a comparison variable determined on the basis of the measurement data in order to determine process parameters relevant to drying, migration and/or crosslinking for pigmented and unpigmented printing inks, coatings, primers and To regulate lamination adhesive on at least one printing machine accordingly.
  • a tolerance band can be assigned to each reference value. In this case, during the comparison with current measurement data or with a comparison variable determined using the measurement data, it is checked whether the measured values or the comparison variable lie within the tolerance range or not.
  • This process can be used for a variety of coating materials, i.e. printing inks, paints, primers or laminating adhesives.
  • control according to the invention of process parameters of the drying or crosslinking can advantageously result in a reduction in waste, an increase in application throughput and a considerable saving in energy and reduced emissions of pollutants.
  • a particular advantage is that, by means of the self-learning synchronization module, parameters of the predictive analysis technology, which are conventionally defined as static, can be optimized continuously or at regular intervals using current measurement data, and as a result the process parameters that are relevant for drying and crosslinking can be adjusted according to current circumstances.
  • control system is designed or programmed in such a way that, based on a predictive analysis of input data and/or based on information stored in the memory unit about a printed product and the reference value obtained in this way, process parameters for drying or crosslinking are continuously or at least periodically updated and readjusted at intervals.
  • a drying unit such as a UV lamp can only be set to the power required for optimal drying. If the energy consumption of drying units such as thermal air dryers and UV lamps is reduced to the required value, the drying units also produce less waste heat and/or pollutants. At the same time, there is less heating of machine elements or the entire machine, so that the service life of the printing press is increased and/or a controlled pressroom temperature can be achieved, or an existing air conditioning system in the pressroom can also be operated with less energy or electricity.
  • Another advantage is that the required or maximum crosslinking of radiation-curing printing inks or varnishes on the printed substrate can be ensured through optimized drying and curing control.
  • an overall migration for printed paper or printed cardboard that comes into contact with food can be optimized in such a way that the overall migration has a limit value of 10 mg/dm 2 , as well as the specific limit values for individual components in accordance with the EU plastics regulation No.
  • the central processing unit preferably has an operating unit such as a software-based user interface that can show the user, such as the operator at the printing press, the drying or curing quality to be expected or the drying or curing quality resulting from the set drying parameters.
  • an operating unit such as a software-based user interface that can show the user, such as the operator at the printing press, the drying or curing quality to be expected or the drying or curing quality resulting from the set drying parameters.
  • the status of the optimization options can then be pointed out via the operating unit.
  • the optimization options and the associated control instructions can either take place after manual approval by the operator or automatically.
  • the optimized control system can be preset in such a way that the control instructions for process optimization are output directly to the printing machine via the interface, in order to be able to intervene quickly in the printing process to correct and/or optimize it.
  • the central processing unit processes all incoming data and/or accesses stored data, which can be stored input data on the one hand and stored information on the other.
  • Stored information is understood to mean historical data about at least one printed product, i.e. information based on experience and/or the results of previous order data and/or operating data. If no such empirical knowledge is stored when the optimized control system is initialized, it can be reconstructed from comparable production scenarios, for example by providing information from printing machine manufacturers, from suppliers of the printing materials (inks, varnishes, primers, lamination adhesives, substrates) and/or from the customer will. Alternatively or additionally, information on production times and/or production volumes of the print jobs related to the respective printing press can be used, with all the information obtained being stored in the central storage unit.
  • Predictive analytics techniques use historical data to predict future outcomes or outcomes.
  • the predictive analysis technology can integrate measurement methods, statistical and mathematical processes, a large number of models such as state space models as well as artificial intelligence and combinations thereof.
  • the predictive analysis technique comprises one or more of the following techniques: Theoretical and/or experimental system analysis, measurement analysis using measurement data recorded by sensors and/or measuring instruments, empirical models, statistical models, stochastic models, mathematical methods, analyzes based on machine learning or an AI module (artificial intelligence module), a Big data analysis or a deep data analysis.
  • AI module artificial intelligence module
  • Empirical models according to the present invention mean any type of approximation of empirical observations by a mathematical function. This means that, based on one or more data sets, an attempt is made to determine a functional relationship that reproduces the data sufficiently well.
  • An empirical model can fall back on linear models or models of the 2nd or higher order. For example, to find a regression line (linear or first-order model) that best fits the measurement data, stochastic or statistical methods such as the least squares method can be used.
  • An empirical model can preferably be obtained for printing processes by performing a statistical design of experiments.
  • the statistical design of experiments is based on a systematic experimental design and evaluation of the measurement results obtained.
  • the experiments can include all conceivable experimental setups or just a part (optimal design, D-optimal design, partial factorial design).
  • test plans are implemented that result in the smallest scope.
  • reference is made to statistical textbooks such as " Statistics for Experiments” by George EP Box et al., ISBN-13: 978-0471718130 .
  • the parameters varied in the experiment can be one or more process parameters selected from the group consisting of: type and number of superimposed coatings, area coverage of each individual layer of printing ink, varnish, primer and / or laminating adhesive, color density or weight per unit area dry printing ink, varnish, etc., type of substrate/printing material, printing speed, for UV curing: type of UV lamp, UV lamp power and UV dose, for heat drying: temperature, airflow speed and other parameters relevant to drying and crosslinking.
  • the self-learning synchronization module can lead to more precise results than conventional control methods and the process parameters for the relevant components of the Optimizing the printing machine, such as drying units.
  • the arithmetic, testing and comparison operations that run automatically in an AI module can contain ever more precise trial and error test runs in which deviations from the specified product that may occur due to continuous self-documentation, i.e. the use of stored information about the printed product Target state, such as a desired drying and crosslinking quality can be eliminated better and better.
  • Continuous or intermittent measurement analyzes for mapping the "actual" status can support the control system, for example by using the resulting measurement data as training data for an AI module. In this way, possible deviations from the target state can be recognized and corrected promptly in order to ensure consistent drying and crosslinking quality.
  • So-called inline sensors are suitable for continuous measurement, which are positioned in the printing press and can output measurement signals directly or indirectly to the central processing unit for further processing and/or storage.
  • the inline sensors are located directly in the production line.
  • external measurement data from so-called offline sensors which can also be called out-of-line sensors or sensors outside the production line, can be used.
  • the sensors and measurement analysis methods used depend, among other things, on the curing or crosslinking process. In the following sections on inline and offline sensors, examples of the known measurement methods are given. With all measuring methods, it should be noted that the measurements should preferably be taken on so-called test or calibration areas and/or fields of the individual colors, e.g.
  • “Worst case areas” should take into account critical single or multi-layer areas where, depending on the print job, either the highest layer thicknesses are applied or the layer structure places the highest demands on chemical and/or physical curing.
  • the measurements are advantageously carried out under the real printing machine conditions, ie inline or intermittently offline with currently printed test fields.
  • so-called synchronization proofs are carried out, which are used to synchronize or calibrate a print job under real conditions. This allows current measurement data to be compared to calibration curves or empirical models from the ink manufacturer or other tests previously performed in a laboratory.
  • the central processing unit can select a predictive analysis technique either automatically or as specified by an operator and, using an empirical model in combination with the print job-related data, for example, can calculate a "worst case area" and a corresponding reference value, preferably with a tolerance band.
  • the predictive analysis technique is designed to predict the drying or curing quality or to determine it with the help of a reference value. This reference value can then be compared with the current measured values of the same test area (here "worst case area"). For example, depending on a comparison with a previously specified minimum limit value of the drying or crosslinking quality, the control system can adjust the process parameters with a significant influence on drying, migration and/or crosslinking.
  • the process parameters with a significant influence on drying and/or crosslinking include a printing speed and/or type and/or number and/or position and/or power and/or geometry of a radiation or a thermal airflow drying unit.
  • control system for acquiring measurement data comprises at least one sensor, the at least one sensor being selected from a group comprising: an inline sensor, an offline sensor and a virtual sensor and combinations thereof.
  • a virtual sensor can be provided based on a predictive analysis technique such as a simulation model.
  • a virtual sensor can be trained using data generated by a model and/or measurement data from real measurement sensors.
  • So-called offline sensors or external analysis methods can be used to determine the current measurement data. These include a simple scratch test, for example with a fingernail or a fixed needle, to determine scratch resistance.
  • the following additional offline tests which are carried out either manually or with the help of measurement-analytical devices such as spectrometers can be used to determine measurement data for typical properties of the drying or crosslinking quality: Tape test (adhesion), solvent test (resistance to surface swelling), extraction of extractable components and spectroscopic quantity determination, e.g. by measuring the UV/VIS spectrum or IR spectrum on the extracted sample, spectroscopic determination of the concentration of relevant molecules or groups of atoms to determine the degree of conversion (e.g.
  • an offline measuring device such as an RFA (X-ray fluorescence analysis) hand-held spectrometer from Bruker (S1 Titan Series, TRACER 5 Family) can be used.
  • the printed substrate can be extracted with a solvent (e.g. ethanol) or aqueous solutions of complexing agents (e.g. ethylenediaminetetraacetate (EDTA) solution) and then the extract can be measured with the XRF scanner.
  • a solvent e.g. ethanol
  • aqueous solutions of complexing agents e.g. ethylenediaminetetraacetate (EDTA) solution
  • EDTA ethylenediaminetetraacetate
  • the amount of metal-containing components can be determined, which can be used in particular for the analysis of metal-containing drying substances in oxidatively drying systems or with cationic photoinitiators.
  • Radiation-curing printing inks or coatings contain, for example, onium salts as cationic photoinitiators.
  • Suitable onium salts can include, for example, triphenylsulfonium salts, diazonium salts, diaryliodonium salts, as well as ferrocenium salts and various other metallocene compounds.
  • the structure of two known onium salts, namely diphenyliodonium and triphenylsulfonium salt are shown below.
  • the smear resistance and the carbonation can be tested with the WIKAT test device from the Fogra Research Institute for Media Technologies eV. Carbonation is understood to be an examination of micro-scrubbing of ink against a white reverse sheet or an adjacent surface under high pressure with a minimal stroke, as occurs, for example, when cutting with staple cutters. If drying is insufficient, the printed color or the applied varnish will be transferred more or less strongly to the backing paper.
  • the force required for delamination can be measured offline with suitable testing machines such as a zwickiLine Z5.0 material testing machine and compared with target values.
  • suitable testing machines such as a zwickiLine Z5.0 material testing machine
  • Other offline measurement analysis methods not listed here are conceivable as long as they are directly related to drying and/or curing, are easily reproducible and can be used with sufficient accuracy for synchronization or adaptation.
  • inline sensors which can supply current measurement data inline in the ongoing production process or in the production line almost in real time, is particularly advantageous for continuous and efficient cooperation with the self-learning synchronization module.
  • some of the above-mentioned offline methods can be automated by installing a measuring sensor, for example, in a (pressure) roller located opposite a drying unit or a radiator.
  • a measuring sensor for example, in a (pressure) roller located opposite a drying unit or a radiator.
  • a permanently installed needle in the printing machine can be used together with a camera sensor for automated visual evaluation by the central processing unit.
  • a printed sheet or section can also be extracted automatically when the stack or roll is changed, after which, for example, an automated extraction test, tape test and/or carbonation test can be carried out.
  • an automated measurement can be carried out close to the process in a so-called bypass and online measurement data can be provided for process optimization.
  • a first UV/VIS or IR sensor can be placed before the UV dryer unit and a second sensor of the same type after the UV dryer unit.
  • the measured UV absorptions in a defined area e.g. a test field
  • measurement methods and possible measurement sensors mentioned above do not represent an exhaustive list.
  • Other measurement sensors such as conductivity sensors, which are usually used in the field of printing technology, can be used for measurements in the control system or control method according to the invention.
  • the central processing unit serves as a process optimization tool and can be designed as a server or in the form of a plurality of central processing units, so-called server clusters, or microservices.
  • Other computing systems such as a personal computer, tablet or the like can be connected to the central processing unit in a wireless or wired manner via networks or buses.
  • control system comprises a plurality of printing presses, the central processing unit being able to be connected to the printing presses by means of a network if the printing presses provide for this type of communication or this option can be retrofitted.
  • the network can be a communications network such as the Internet, or it can be a non-public network.
  • the various printing machines must be clearly identifiable, as is usually the case with unique machine identifiers.
  • the central processing unit can be connected to at least one printing machine or to an operating unit of one or more printing machines by wire or wirelessly via data connections, for example in order to receive current operating data and on the other hand to output the optimized process parameters of drying, migration and/or networking to one or more printing machines to control.
  • the operating unit is preferably assigned directly to the central processing unit and is preferably designed as a keyboard, mouse, trackball and/or touch-sensitive user interface and allows the operator quick access.
  • the synchronization module is configured to determine adjustment factors or interpolation factors for variable parameters as a function of the order data or changing operating data.
  • the synchronization module as part of the central processing unit, can determine necessary adjustment or interpolation factors in order to compensate for parameters that fluctuate or change from job to job, e.g. print job to print job (e.g. substrate type (e.g. cardboard, matt or glossy coated paper, uncoated paper , film, etc.), substrate manufacturers or product lines (e.g. satin-coated papers such as MultiArtSilk, MagnoSatin, etc.), ink type (e.g. oxidatively drying or radiation-curing), ink series based on ink manufacturers (e.g. from hubergroup GmbH: Resista 250, MGA Natura, UEH5000, etc.), paint type (e.g.
  • print job to print job e.g. substrate type (e.g. cardboard, matt or glossy coated paper, uncoated paper , film, etc.), substrate manufacturers or product lines (e.g. satin-coated papers such as MultiArtSilk, MagnoSatin, etc.), ink type (e.g
  • the synchronization module is configured to carry out an order analysis in advance based on the order data in order to optimize an order and/or print motif sequence per printing press and/or the process parameters in relation to the process steps.
  • optimization can take place according to the total layer thicknesses or surface coverage of the individual colors, varnishes, primers or laminating adhesives to be printed, so that, for example, the printing of jobs and/or print motifs with low total layer thicknesses or surface coverage can be started and then the printing of Orders and/or print subjects with higher total layer thicknesses or surface coverage follows.
  • the energy consumption can be optimized, since the radiation power can be adjusted depending on the order in the case of radiation-curing printing inks and coatings.
  • the input data can be recorded and stored automatically via the input unit and/or manually via the operating unit.
  • the measurement data from inline sensors can be recorded and saved in real time and then used for further calculations.
  • manual input of data is necessary for offline measurements, for example, in order to make the measurement results available to the control system that can be optimized.
  • Storage can take place on standard computer-readable storage media, if necessary on server computers and/or use a cloud system in order to be able to store the large number of data.
  • the input data for the central processing unit includes both operational data and order data, which are listed below.
  • the operating data are selected from a group comprising: printing process, machine type, machine parameters (e.g. roller type, rubber blanket, dampening solution, alcohol, etc.), environmental parameters, substrate or substrate types, substrate series, coating materials (ink series, ink types, additives, primers, varnishes, laminating adhesive ), dampening solution (fountain solution type, dampening solution dosage), process water values (e.g. conductivity, pH value), layer structure and the quantities of ink, varnish, primer or laminating adhesive to be transferred, and combinations thereof.
  • machine parameters e.g. roller type, rubber blanket, dampening solution, alcohol, etc.
  • environmental parameters e.g., environmental parameters, substrate or substrate types, substrate series, coating materials (ink series, ink types, additives, primers, varnishes, laminating adhesive ), dampening solution (fountain solution type, dampening solution dosage), process water values (e.g. conductivity, pH value), layer structure and the quantities of ink, varnish, primer or laminating
  • Ambient parameters include the temperature in the pressroom or at predetermined locations in the printing press or the humidity.
  • Printing processes can be understood to mean the following in particular: gravure printing processes, relief printing processes including, inter alia, the flexographic printing process, offset printing processes, inkjet printing processes and toner-based digital printing processes.
  • the machine parameters can depend on the one hand on the machine type or manufacturer and on the other hand on the printing process.
  • the order data are selected from a group comprising: Print data based on an analysis of the digital print data, preferably using a page description language comprising a pdf analysis or order-related data, with the respective surface coverage of printing ink, varnish, primer and/or laminating adhesive being based on at least part of the print area or on the entire application area the order data or the order-related data can be calculated.
  • Order-related data preferably also includes further processing data, which are selected from a group comprising: Die-cutting, creasing, cutting, folding, stitching, laminating, gluing, hot foil stamping, cold foil stamping, embossing, heat sealing and stacking.
  • the method preferably also includes the following method step: providing the current measurement data by means of measurement methods using at least one of the following sensors: an offline sensor, an inline sensor, a virtual sensor and combinations thereof.
  • a measurement method using an offline sensor is selected, this is preferably done from the group comprising atomic absorption spectrometry (AAS), ICP-OES (optical emission spectrometry with inductively coupled plasma), ICP-MS (mass spectrometry with inductively coupled plasma) and UV-VIS spectrometry to metal ions cationic photoinitiators such as onium salts from radiation-curing coating materials or metal ions from oxidative dryers from oxidatively drying coating materials.
  • AAS atomic absorption spectrometry
  • ICP-OES optical emission spectrometry with inductively coupled plasma
  • ICP-MS mass spectrometry with inductively coupled plasma
  • UV-VIS spectrometry to metal ions cationic photoinitiators such as onium salts from radiation-curing coating materials or metal ions from oxidative dryers from oxidatively drying coating materials.
  • the method preferably also includes the following method step: providing a synchronization module that is designed to determine adjustment factors or interpolation factors for variable parameters as a function of the order data or changing operating data in order to automatically adjust the variable parameters.
  • the synchronization module preferably carries out an order analysis based on the order data in order to optimize an order sequence per printing press and/or the process parameters as a function of the process steps.
  • a computer-readable medium is provided on which instructions for controlling at least one printing machine are stored in order to carry out the above-mentioned method for controlling drying or crosslinking parameters.
  • a computer program which comprises instructions which, when the program is executed, cause a computer to carry out the method steps mentioned above.
  • a central processing unit 120 is provided for receiving input data from an input unit 110 .
  • the central processing unit 120 processes all incoming data and calculates optimal settings or process parameters for the drying, migration or crosslinking.
  • These optimal process parameters are output by control instructions from an output unit 170 to the respective printing press (not shown here).
  • the central processing unit 120 takes into account data and results from earlier measurements and application jobs or information from printed products, insofar as this is possible at the beginning of a printing process, as well as job data.
  • the input unit 110 is designed for the automatic or manual acceptance of input data including operating data and order data of a printing press.
  • the central processing unit 120 has a memory unit 121 or a database for storing data and in particular input data and information about at least one printed product. Furthermore, the central processing unit 120 has a synchronization module 122 .
  • the synchronization module 122 of the central processing unit 120 is designed to be self-learning by predicting drying or crosslinking parameters be optimized 422 by current measurement data from measurement methods or sensors 150.
  • the machine learning can take place, for example, via a self-learning, artificial intelligence (AI) module 145.
  • the AI module 145 can be configured to learn based on the data stored in the storage unit 121, comprising input data and/or stored information, using algorithms by means of recursive self-improvement.
  • the algorithms of the AI module 145 can, among other things, create a statistical model 142 which is based on training data such as empirical data or measurement data from inline sensors 152 or offline sensors 151 .
  • the recording of current parameters, eg machine parameters, the comparison with order data, measurement data, historical data such as empirical data (information about at least one printed product) and reference values obtained from predictive analysis techniques takes place constantly and during production.
  • the synchronization module 122 can optimize predictions of drying or crosslinking quality with current measurement data continuously and/or at regular intervals in the case of offline measurements. This preferably takes place without interrupting the print production.
  • the self-learning synchronization module 122 is designed to select at least one predictive analysis technique 140 in order to be able to determine at least one reference value for the drying or crosslinking quality based on the selected model or method.
  • Analysis techniques 140 include one or more of the following models, methods, or analysis: theoretical and/or experimental system analysis 141, science-based theoretical model 148, empirical model 147, measurement analysis using measurement data collected by sensors 150, statistical model 142, stochastic model 143, mathematical method 144, analysis based on machine learning or an AI module (artificial Intelligence Module) 145, Big Data Analysis and Deep Data Analysis 146.
  • the in 1 illustrated predictive analysis techniques 140 do not rule out an interaction of the individual methods or models.
  • a combination of the analysis techniques can be chosen depending on which parts of a process can be obtained which information most easily.
  • empirical models 147 can be used, for example, to Data reduction in combination with stochastic models 143 or statistical methods 142 can be formed.
  • the system analyzes 141 based on a scientific basis can be divided into theoretical modeling 148 and experimental or empirical modeling 147 .
  • the principles of the process to be predicted (here drying, curing, crosslinking and migration potential of the applied coating materials) and also the parameters simplifying the system can usually be obtained by way of the theoretical system analysis148.
  • Theoretical system analyzes or models are based in particular on theoretical knowledge such as physical or chemical laws. Since some process sequences are not precisely known or purely physical/chemical modeling is too complex, experimental system analysis 147 or empirical modeling is often added to the theoretical system analysis 148 .
  • measured signals are used, i.e.
  • the so-called state space model can represent all relationships between the input, output and state variables of a dynamic system in the form of differential equations and with matrices and/or vectors. Measurements, for example at the system output, can be used to predict unknown parameters.
  • the state of a dynamic system such as the degree of drying at a point in time t, can be predicted or estimated by a series of state variables.
  • a valid model such as a state space model can be used to predict and thus optimize and control drying or curing in the printing process. It is an advantage of the control system that that depending on the available data, different predictive analysis techniques or methods 140 can be selected or combined.
  • the measurement data required for the experimental system analyzes or the empirical models 147 are obtained by suitable measurement sensors 150 or measurement methods.
  • a large number of parameters such as process parameters or machine parameters can be recorded or determined by means of measuring sensors 150 .
  • the current measurement data can be taken directly from the inline measurement sensors built into the printing machine (152 see 2 ) be transmitted. In this way, the incoming measurement data are recorded directly via the input unit 110, ie automatically and without delay. Alternatively or additionally, the measurement data can be input via manual input.
  • FIG. 2 shows a schematic detailed view of the central processing unit (CPU) 120 with the synchronization module 122 and interfaces 111, for example for receiving measurement data 115 from measurement sensors 150, or input data from a user interface, which is designed as an operating unit 125.
  • the sensors 150 are divided into what are known as off-line sensors 151 and in-line sensors 152 . They can be arranged both externally and internally in relation to the printing press.
  • measurement data 115 from inline sensors 152 which can be transmitted in real time to the synchronization module 122 via a suitable interface 111, are data from the measurement of operating data 118 of the printing press and/or measurement data 115, which are used to optimize a process parameter for drying - and curing quality can be used.
  • This data includes, for example, IR/NIR data, color measurement data from control colors, radiation power and/or intensity from integrated radiation dose sensors, visual data from camera sensors from integrated scratch test results, measurement data from spectroscopic or spectrometric investigations, conductivity measurement data, measurement data from magnetic investigations and luminescence measurement data.
  • Other known inline sensors or virtual sensors can also be used if the measurement data 115 obtained are suitable for determining or optimizing the process parameters relevant to the drying or curing quality.
  • the measurement data 115 mentioned above can also be obtained discontinuously with the aid of offline sensors 151 and offline measurement methods.
  • Such so-called external measurement data such as results of scratch tests, tape tests, solvent resistance tests, extraction tests, spectroscopic investigations, conductivity measurements, magnetic investigations, luminescence measurements can be entered manually via a user interface such as an operating unit 125 .
  • this measurement data can be transmitted wirelessly or wired using known transmission technologies such as Bluetooth, WLAN and/or NFC (Near Field Communication). be received by a suitable interface 111 of the central processing unit (CPU) 120.
  • the operating unit 125 can be designed as a software-based user interface and/or as a mobile unit with a display or screen.
  • the computing unit 120 does not necessarily have to be on site, but can also be a global infrastructure such as the Internet of Things (Internet of Things IoT) or cloud-based.
  • the input data can be stored in the storage unit 121, with the data being able to be stored locally or in a cloud 128.
  • FIG. 3 shows a schematic data flow diagram for a control method and control system for at least one printing press 180, with data flows between the interfaces 111 and components such as sensors 150 being shown, among other things.
  • the central processing unit 120 is designed to process data, ie to carry out analyzes of raw data, and for this purpose receives data from various sources.
  • order data 114 should be mentioned as source data, which is in the form of pdf (Portable Document Format) or other suitable description languages such as in bitmap format or Postscript (trade name of Adobe Systems USA), or in the form of proprietary file formats of the respective manufacturer, e.g. Adobe Photoshop ® , Adobe Illustrator ® , Adobe Acrobat Pro DC ® , Esko Art Pro or QuarkXpress.
  • Order data 114 such as digital print data or image data can be analyzed in the central processing unit 120 with the aid of a raw data or order analysis 124 .
  • An analysis of pdf files is preferred.
  • the process parameters 181 can be optimized in detail for the respective order and in relation to the process steps.
  • Measurement data 115 can be obtained from various sources.
  • a possible external data source is a sample 164 such as an extraction sample, where the amount of extractable components from the printed substrate can be determined spectroscopically.
  • These external or manual tests can be carried out once, in certain maintenance cycles, or per order, preferably in so-called “live” or “inline” tests and/or in bypass during the current order.
  • the measurement data 115 obtained in the tests or test methods can be transmitted to the central processing unit 120 either directly from measurement sensors 150 or manually via suitable interfaces 111 .
  • operating data can be received directly from the printing press 180 via the interface 111 by the central processing unit 120 .
  • the operating data can be transmitted via sensors 150, which are located outside of the printing press 180 in a press room (external sources) or in the vicinity of or on the printing press 180, measurement data 115 and operating data such as environmental parameters 165 via the interface 111 to the central processing unit 120 for further analysis (see vertical box of sensors 150 and environmental parameters 165 with horizontal data flow arrow towards interface 111).
  • Typical environmental parameters 165 are the temperature (T [°C]), such as the temperature in the application machine, or the relative humidity (RH [%]).
  • the machine parameters 168 also include actuator data 169 such as a speed or feed, application/printing speed, roller settings, roller types and settings, and type, power and geometry of the dryer unit(s).
  • Process parameters 181 for drying that can be set via control instructions 171 are, in particular, the printing speed and the performance of the dryer units. Depending on the dryer type (UV, ESH, IR, microwave, hot air, etc.), either the Radiator output or temperature and air speed for heat dryers can be controlled as process parameters. In the case of laser dryers, control instructions 171 can be given with regard to power and/or wavelength. In the case of the dryer units, the drying should be set with the lowest possible performance with the required drying quality.
  • Other machine parameters are: pick-up volumes, rubber blanket (type), printing form parameters (printing form type), screen frequency of the printing form, printing form quality, print subject and color assignment, gluing of printing forms (substructure), cliché structure (concentricity with several repeats, avoidance of vibration), printing cylinder parameters such as the printing cylinder roughness (gravure printing) , ink fountain and settings, squeegee type and squeegee quality, with inkjet printers, among other things, droplet size, nozzle type and print head (type).
  • the central processing unit 120 uses a predictive analysis technique 140 for optimization.
  • This analysis technique can be science-based and can comprise an empirical model 147 and/or a theoretical system analysis 148 .
  • statistical methods 142 such as statistical optimization methods such as least-squares estimation can be used to determine a regression line that best fits the measured values, or stochastic models 143 based on probability calculations, as well as mathematical methods 144 used for predictive analysis.
  • Artificial intelligence modules are preferably used to determine the process parameters 181 for controlling a printing press.
  • Such AI modules translate input data such as order data 114, operating data 118 and/or measurement data 115 through an internal processing chain into output variables such as control instructions 171, optimal process parameters 181, machine target values 168′ and/or optimal order sequences for all outstanding orders.
  • the internal processing chain can be trained by presenting a large number of learning values, for example measurement data 115 for the input variables and the internal processing chain is successively adjusted such that these learned values for the input variables are mapped as well as possible to the associated learned values for the output variables.
  • the AI module is preferably designed to be dynamic and can continue to improve automatically through continuous learning.
  • Such a dynamic AI module can also automatically adjust itself to changes during the current print job that lead to deviations from the optimal drying settings and associated process parameters 181 . For example, manual intervention, ie manual synchronization and/or order-related cross-checking and the resulting adjustments, are no longer necessary, or at least less and less necessary.
  • control system is designed to be self-learning and serves as an interface that links and evaluates the results and measurement data 115 of a wide variety of drying and curing analyzes and subsequently optimizes the process parameters relevant to the drying setting.
  • manual optimization effort can be significantly reduced and job interruptions, long makeready times and waste, i.e. prints that have become unusable due to insufficient drying, for example, or are otherwise faulty or damaged (migration values too high), can be avoided.
  • the central processing unit 120 can call up a big data analysis 146 or deep data analysis that corresponds to a specific printing press or can be associated with multiple printing machines and defines data that is important and relevant to the operator of the printing machine(s).
  • a big data analysis technique can use the collected data in a self-learning manner to identify indicators of waste and thus predict and solve problems. By collecting as much data as possible and evaluating it, a more precise predictive analysis or prediction can be carried out with an increasing learning curve before the start of production. In this way, problems such as excessive migration or insufficient drying/crosslinking can be avoided in the printed product.
  • Figure 4a shows a first exemplary embodiment of a method 400 according to the invention for controlling process parameters relevant to drying, migration and crosslinking.
  • a current print job is to be printed on a known printing machine with a known ink series and a known substrate.
  • Control begins with method steps 410 through 414 relating to the entry of input data into the input unit 110. Even if Figure 4a represents the method steps in a specific order, it is pointed out that this order of the method steps is not mandatory and other orders are possible. Individual method steps can also be omitted if parameters cannot be entered at the beginning because they only become known, or are calculated or estimated, at a later point in time.
  • the input unit 110 (in Figure 4a not shown see Figure 4b ) an input 410 of operating data 118 of a known printing press 180.
  • This operating data 118 can include the manufacturer and type.
  • a flexographic printing machine 481 with web-fed rotary printing is shown as an exemplary printing machine 180 .
  • Other printing presses, such as sheet-fed offset printing presses, can also be controlled using method 400.
  • Further operating data 118 are entered in steps 412 to 414 using the input unit 110 .
  • the input can be manual or, if necessary, partially automated or fully automated.
  • the order data 114 is entered, the order data 114 being made available by way of example in the form of pdf (portable document format).
  • the order data 114 such as digital print data or image data, are processed by the central processing unit 120 in the method step 418 received and processed in the central processing unit 120 with the aid of a raw data or order analysis 124 .
  • the known boundary conditions such as the known color series or the coating material 161 used, are entered in method step 412 .
  • the colors used can be selected from commercially available color series.
  • step 413 a known substrate 160, which can also be called printing material, is entered.
  • step 414 depending on the known printing machine 180, machine parameters 168 such as the number and type of dryer units and the printing speed v(print) can be entered.
  • All input data including the aforementioned operating data 118, order data 114 and information about a printed product are received by the central module 120 in step 418 from the central processing unit 120 and stored in the memory unit 121 in step 419 .
  • measurements can be carried out continuously or discontinuously in method step 421 or measurement data 115 can be determined using suitable methods and measurement methods 421 .
  • the measured measurement data 115 are received by the central processing unit 120 via a suitable interface 111 or input unit 110 in method step 418 .
  • a predictive analysis technique 140 is selected in the central processing unit 120 (CPU) based on the input data (118, 114) and/or stored information. In method step 420 , the selected analysis technique 140 determines at least one reference value for the drying or crosslinking quality.
  • a state space model or an empirical model 147 can be used as a possible predictive analysis method 140, which can depict the basic behavior of the drying or crosslinking and can thus determine a suitable reference value for the degree of drying or curing.
  • the model used or the predictive analysis technique 140 can be parameterized and adjusted in order to achieve a sufficiently precise match between the predictive model used and reality.
  • measurement data 115 can be measured in method step 480 , i.e. when the print job is printed on the printing press, using measurement methods in method step 421, or at least initially based on historical measurement values based on experience or data from a database stored in memory unit 121.
  • the measured values 115 can be calculated or estimated by at least one selected predictive analysis technique 140 in order to be able to depict the degree of drying or crosslinking and in particular the reference value specific for the degree of drying and crosslinking even without carrying out real measurements. If an artificial intelligence module 145 is available as analysis technique 140, measured values 115 from measurement methods 421 of both a real and a virtual sensor can serve as training data for the AI module.
  • the synchronization module 122 of the central processing unit 120 is used to calculate optimized process parameters 181 and process settings for approximating the reference value using current measurement data 115 .
  • the synchronization module 122 is preferably optimized or learned 422 with at least one value determined by measurement or a large number of measurement data 115. These measurement data 115 can be obtained continuously or discontinuously and optionally come from a virtual sensor.
  • the measurement data of a real or virtual sensor can use, for example, AI module 145 algorithms or machine learning algorithms of a predictive analysis technique 140 in order to optimize the drying or curing-relevant process parameters for a maximum approximation to the reference value.
  • the process parameters relevant to drying or curing are adjusted or optimized. If, on the other hand, the reference value or a predetermined tolerance band around the reference value has already been reached and the relevant process parameters for drying, crosslinking or migration are thus already optimally set, the feedback from the synchronization module 122 is that no adjustments or changes to the relevant process parameters need to be made.
  • At least one process parameter 181 is calculated in method step 425 on the basis of the at least one reference value. In this way, to control the printing process, one or more process parameters 181 can be sent to the output unit (see reference number 170 in Figure 4b ) are transmitted.
  • the control instructions 171 relating to at least one process parameter 181 are output to the printing press 180 in method step 470 .
  • process parameters of the drying units such as UV lamps (see 485 in Figure 4b ) or heat dryer units (see 486 in Figure 4b ) can be controlled, for example by increasing the power if curing is too low and reducing the power if curing is too high.
  • the process parameter 181 printing speed (vPrint) can also be increased or reduced.
  • a flexographic printing machine 481 with web-fed rotary printing is shown as an exemplary printing machine 180, which can be used with the method 400, which is described in Figure 4a is shown schematically, is controllable.
  • Figure 4b shows as substrate 160 a so-called printing material web, such as paper, metal or plastic foil, which is unrolled from the unwinding cylinder 463 and at the end of the printing process is rolled up onto the winding cylinder 462 and associated roll stand (not shown).
  • the substrate 160 is conveyed in the direction 469, with higher printing speeds v(print) being able to be achieved in the rotary-fed printing mode in comparison to the processing of individual sheets in sheet-fed printing presses.
  • the printing speed v(print) can be determined, for example, by actuator data 169, i.e. by the rotational speed of the reeling cylinder 462, and can be automatically received by the input unit 110 in method step 418 via suitable data transmission means or data lines (represented schematically by the arrow between the reeling cylinder 462 and arrow 418) and are processed in the central processing unit 120.
  • Important machine parameters 168 for drying such as the printing speed v(print), as well as performance parameters and/or geometries of the dryer units 487 can be entered into or received from input unit 110 (see also step 414 Figure 4a ).
  • the type of dryer systems such as UV lamps 485 or heat dryer units 486, which dry with thermal air or hot air up to 250 °C, and/or the number and output of the dryer units 487 of the printing press 180 can be entered or received.
  • machine parameters 168 of the chamber doctor blade system such as the doctor blade type, parameters of the anilox roller(s) 466 or the respectively associated printing forme cylinder 467 and the at least one impression cylinder 465 can be recorded.
  • a dryer unit such as a heat dryer unit 486 or a UV radiator 485 is positioned behind each printing unit 461 or inking unit.
  • another dryer unit 487 for complete curing or crosslinking which is preferably designed as a drying channel. All dryer units are connected to the printing machine control in the central processing unit 120 .
  • UV dryers 485 or other dryer units 486, 487 can be selected by means of an operating unit (not shown). In order to ensure controlled drying, it can be set that the print is only started when each dryer unit required for the respective print job has reported back to the central processing unit 120 that it is ready for operation. This measure prevents waste from being produced with insufficiently dried or non-crosslinked printing inks or coatings.
  • UV-curing inks can be used as the coating material 161 .
  • radiation-curing inks are used in the last three inking units with downstream UV emitters 485.
  • the UV flexographic printing machine 481 shown has, for example, 6 inking or printing units. Configurations other than the machine configuration shown, for example with more or fewer printing units, are also conceivable.
  • At least one cooling roller can follow after the last drying unit 487 for complete curing or drying.
  • the curing of the coating material 161 should be optimal Settings of the process parameters 181 largely completed.
  • a measuring system is permanently installed in the printing machine 481 for a continuous scratch test, which comprises a scratch needle 452 and a camera sensor 450.
  • the camera sensor 450 forwards the measurement data 115 in the form of image data to the central processing unit 120 in order to carry out an automated visual evaluation to check the degree of curing or the scratch resistance.
  • This measurement data 115 can be used inline without interrupting the printing process via the data line (see arrow to input unit 110) in order, with the help of synchronization module 122 and/or data stored in memory unit 121, to calculate the process parameters relevant to drying and crosslinking and thus also predictive analysis technology 140 to optimize.
  • proofs with test fields are preferably printed at the level of the camera position, which have so-called order-specific “worst case areas” or critical multi-layer areas. If the measurement methods 421 are carried out in such critical areas, it can be assumed that, with sufficient drying or curing of such critical areas of the print subject, areas that are easier to dry with, for example, fewer layers or lower layer thicknesses also have sufficient polymerization or drying.
  • the synchronization module 122 can create interpolation factors or an adapted model that specifies at least one optimized process parameter for the current measurement data 115 that leads to a maximum approximation of the reference value.
  • a possible synchronization method for optimizing the at least one process parameter is to minimize a difference between the target values and the measured actual values of the respective measured variable and to draw conclusions about the optimal setting of the at least one process parameter for maximum approximation to the reference value.
  • control instructions 171 or 172 are output to a UV emitter 485 or a dryer unit 487 (470).
  • the output of control instructions to the heat dryer units 486 is also possible, but not shown here. In this way, the emitter output and intensity of the dryer units can be adjusted and set individually for each print job in order to achieve an optimal print result in terms of drying.
  • the type of printing machine and the type of UV lamp and the number of UV lamps are known, but this example 500 is a printing machine 180 that is several years old (eg 10 years) and the age of the UV lamps is unknown. It is well known that classic UV lamps such as mercury vapor lamps change their lamp output over time with longer operating times, especially at the lamp ends. In addition, the performance of UV radiators usually decreases over long periods of operation due to dirt or the reflectors becoming tarnished.
  • the procedure is 500 designed to adapt the relevant process parameters of drying and crosslinking, such as the actually required UV intensity, to the current operating conditions with the help of the synchronization module 122 by means of current measurements on a calibration field.
  • the exemplary control method 500 begins with the method steps 510 to 515 and each includes the inputting 510 of input data comprising operating data 118 and order data 114.
  • the KBA Rapida 106 is a 6-color sheetfed offset press with an integrated coating unit.
  • Advantageous with this machine type KBA RA 106-6+L are high Printing speeds with v(print) up to 20000 sheets/h.
  • a variety of substrates such as thick cardboard, paper, foil and much more can be printed with the KBA RA 106.
  • the Invercote® G used in Example 500 is board for the graphics sector or for high-quality packaging and is commercially available with basis weights between 180 and 380 g/m 2 .
  • a number of dryer units here 2 Hg UV lamps
  • additional dryer units can optionally be positioned as intermediate dryers between the offset printing units (cf. positions of the UV dryer 785 or dryer unit 486 on the 781 or 782 of 7 ).
  • step 511 the order data 114 is entered, the order data 114 being made available by way of example in the form of pdf (Portable Document Format) and having a calibration field for the measuring 553 method step.
  • the order data 114 such as digital print data or image data, and the above-mentioned operating data 118 are received by the central processing unit 120 in method step 418.
  • measurement data 115 are received by the central processing unit 120 .
  • method steps 550 to 554 are carried out.
  • the printing form is proofed with a calibration field stored in the pdf and with the known boundary conditions such as color series, substrate and number or type of UV lamps.
  • This proofing can also be called synchronization proofing, since the calibration or test field can be used to synchronize or calibrate the print job defined by the order data 114 to real conditions.
  • step 551 the calibration field or a part of the calibration field with an area of approximately 20 cm 2 is cut out.
  • other areas of the calibration field between 1 and 50 cm 2 can be selected, as long as the sample extracts a sufficient amount of at least one soluble component, such as photoinitiators, from the printing ink and can be measured in the linear measuring range of the spectrometer.
  • Photoinitiators can be, for example, cationic onium salts such as diphenyliodonium and triphenylsulfonium salts, or photoinitiators for free-radically curing systems, or combinations of both.
  • the next step 552 the extraction of at least one soluble component of the calibration field on the printed coating material 161, takes place in a solvent bath, preferably in 10 mL ethanol, with the cut-out sample remaining in this solvent bath for a predetermined minimum time (e.g. 10 s).
  • the solvent can also contain alcohols other than ethanol or water-alcohol mixtures, or mixtures of the substances mentioned. Other solvent types, mixtures and amounts are also possible as long as the solvent to sample area ratio is preferably between 0.25 and 20 mL per cm 2 sample.
  • suitable cationic photoinitiators are extracts that contain polydentate ligands such as EDTA (ethylenediaminetetraacetate) or EDTE (ethylenediaminetetraacetic acid).
  • a solvent extract is obtained.
  • the extinction of the alcoholic extract or the extract containing complexing agent is measured with a measuring sensor 150, namely a UV/VIS spectrometer such as Lambda II from Perkin Elmer.
  • the measurement 553 takes place offline with a resolution of 1 nm, a scan rate of 240 nm/min and a gap of 2 nm at a wavelength of 310 nm.
  • Other wavelengths in the range of 190 nm and 4000 nm are also suitable as long as the soluble component to be measured the sample absorbs or emits radiation in the selected wavelength range.
  • a solvent-resistant 1.0 mL disposable cuvette from Rotilabo, which is permeable in this wavelength range, can be used as the measuring cell for this measurement. In this way, measured values 115 of the spectroscopic characteristics of the each dissolved components are obtained depending on the existing drying conditions.
  • step 554 the measurement data 115 or the measurement value of the calibration field are entered into the input unit. Since this is an offline measurement method, this input can be made manually by an operator using a suitable control unit.
  • predictive analysis techniques 140 and in particular empirical models 147 are stored in a database or in the storage unit 121 of the central processing unit 120.
  • an empirical model 147 for the printing machine type KBA RA 106, for the known coating material 161, namely the low-migration and low-odor ink series (NewVPack MGA) and for the known substrate 160 is selected.
  • At least one reference value is determined on the basis of the selected empirical model 147 (see reference number 420).
  • a plurality of reference values for different areas of the printed substrate or print subject can also be calculated.
  • the empirical model 147 is preferably of the 2nd order and has the following fixed parameters in particular: Printing machine and its configuration, substrate, ink series (manufacturer and type), dampening solution (manufacturer and type), solid density of the individual printing inks as well as printing speed and lamp parameters, sample area, extraction agent and time and parameters of the spectrometer used.
  • step 521 reference values are compared with measured actual values with the aid of the measurement data 115, and a possible deviation is then calculated in step 522 . If there is a deviation ⁇ in step 522 , the empirical model 147 is adjusted in method step 523 . This can be done by otherwise fixed parameters of the empirical model 147 being adjusted using adjustment factors or interpolation factors using the synchronization module 122 . The new or adapted empirical model 147' is stored in the memory unit 121 and used for further calculations.
  • step 523 can be skipped (illustrated by the dot-dashed arrow between method steps 522 and 524) and the analysis 124 of the pdf file can be carried out in step 524 with the model 147 originally selected in step 520.
  • the "worst case areas" are calculated on the basis of the order data 114 and using the adapted or selected empirical model 147' or 147, respectively.
  • the "worst case areas" are critical color areas of the respective print subject consisting, for example, of the multi- or single-layer areas most critical to drying, which place the highest demands on the drying settings.
  • step 425 at least one process parameter 181 relevant to drying or crosslinking is calculated, wherein a maximum approximation to the reference value is to be achieved with the adapted model 147'.
  • the UV lamp intensity required for sufficient drying or full curing is calculated.
  • the lamp intensity can be less than 100%, such as 75%. If the calculation results in a lamp intensity of more than 100%, another process parameter must be adjusted, for example by increasing the number of UV lamps used or by reducing the printing speed.
  • the control instructions 171 relating to at least one process parameter 181, such as the UV lamp intensity required for adequate drying, are output to the printing machine 180 via the output unit 170 and optionally displayed to an operator. If there is no automatic control, the displayed UV lamp intensity can be released via a control unit for sufficient drying as a control instruction to the printing machine. In this way, for example, process parameters of the drying units such as UV emitters (see 785 in 7 ) can be optimally controlled.
  • step 480 the print job is printed in the printing machine 180 on the basis of the at least one reference value and the calculated process parameters 181.
  • FIG. 6 shows a schematic of another embodiment of the method 600 according to the invention, which is also suitable for offset printing presses of the KBA Rapida 106+6+L type.
  • the method 600 is essentially comparable to the method 500, in particular with regard to the input of input data and the measurement methods.
  • the predictive analysis technique 140 namely the substrate 160 is unknown.
  • two calibration fields are printed instead of just one calibration field and each test field is measured analogously to example 500.
  • example 500 instead of only one calibration field in example 600, 2 calibration fields are printed, cut out and measured in step 553 after extraction in a solvent.
  • the measurement method is carried out using an offline sensor 151, since measurements are taken out of line or outside of the production line.
  • the measurement data 115 determined discontinuously by the offline measurement method using a spectrometer are received by the central processing unit 120 for further processing.
  • the input data and measurement data can be stored in the memory unit 121 or used directly in a selected predictive analysis technique 140.
  • empirical models 147 for the known press type and the known NewV Pack MGA ink series are selected from the memory unit as predictive analysis techniques. Since there is still no empirical model 147 for the substrate series used, at least 2 empirical models 147 are selected from the database with substrates that come closest to the NilklaSelect substrate or are comparable with it. The empirical models 147 are then used to calculate target values for the respective measured variable and the target values from the empirical models 147 are compared with the actual values from the measurement results 115. It is then analyzed which empirical model 147 the difference between the Target values and the measured actual values 115 can be minimized in order to select the empirical model 147 with the best fit in step 621. At least one reference value for the drying and crosslinking quality is determined with the aid of steps 620, 521 and 621 (see bracket 420).
  • a possible deviation from the at least one reference value is calculated in step 522 , as in example 500. If there is a deviation ⁇ in step 522, constants and/or static Parameters and/or factors of the empirical model 147, such as ink/water balance, ink layer thickness, substrate quality (same type, paper but different characteristics), optimized with the help of adjustment factors or interpolation factors based on the measurement data 115 and thereby the empirical model 147 in the method step 523 adjusted.
  • the new or adapted empirical model 147' is stored in the memory unit 121 and the order analysis 124 in particular is used in step 524 for the further calculations.
  • step 523 can be skipped (illustrated with the aid of a dashed box and an arrow between method steps 522 and 524). and the order analysis 124 of the pdf file with the exception of the 2 calibration fields is carried out in step 524 with the model 147 originally selected in step 621 .
  • the process parameters 181 are calculated in step 425 on the basis of the "worst case areas" calculated in step 524 using the optimal empirical model 147 ′. In this way, the process parameters 181 can be set in the best possible way.
  • step 470 relates to the output of control instructions relating to process parameters 181 .
  • the required intensity of UV lamps see 485 in 7
  • a heat dryer unit see 486 in 7
  • the print job is printed in step 480 on the basis of the output process parameters 181 .
  • FIG. 7 shows schematically an embodiment of a control system 700 for a plurality of printing machines 180, 781 and 782.
  • the printing machine 180 and the offset printing machines 781 and 782 are connected to a network 788 via the central processing unit 120 and suitable interfaces 111.
  • each printing machine can be configured analogously to the in figure 5 or 6 control methods shown in connection with the memory unit 121 and/or the synchronization module 122 can be controlled.
  • the offset printing machine 781 has, for example, 4 offset printing units 701-704 and a coating unit 705 connected downstream.
  • 6 printing units can be provided as with the Rapida 106 sheetfed offset press (KBA RA 106-6+L, Koenig and Bauer Radebeul, Germany), or printing presses with more than 6 printing units, additional coating units or upstream printing units for the application of primers.
  • Paper or cardboard in sheet format 760 is used as the substrate 160.
  • a variety of other substrates 160, such as plastic or metal foil, may be used so long as the substrate 160 is available in the appropriate sheet format.
  • printing press 781 Since printing press 781 is designed for UV sheetfed offset with UV varnish as the coating material, printing press 781 has a plurality of UV dryer units 485, which are arranged at different points and are each connected to the controller of central processing unit 120 via lines (not shown). . On the one hand, intermediate dryers are arranged between the printing units (701 and 702 or 702 and 703) and on the other hand, there are a number of UV dryers 485 behind the last coating unit and before the delivery, before the printed product 163 is placed on the stack of sheets.
  • the printing press 782 represents an example of conventional sheet-fed offset with UV coating, with a heat dryer unit 486 being arranged in front of the coating unit and three UV emitters 485 being positioned after the coating unit and in front of the stack of printed sheets 763.
  • other components that are not shown, such as signal lines or measuring sensors 150, for example for measuring the temperature or humidity (not in 7 shown) attached.
  • the examples shown are not limiting, since a variety of inks or primers and/or varnishes and associated dryer units 487 can be used individually depending on the print jobs and the respective printing units.
  • the central processing unit 120 serves as a process optimization tool for each individual printing press and can be embodied as a server or in the form of a plurality of central processing units 120 .
  • Other computing systems such as a personal computer (not shown) or the like, may communicate with central processing unit 120 via network 788, either wirelessly or by wire.
  • a particular advantage of the control system and method is that by means of the self-learning synchronization module, parameters of the predictive analysis technology, which are usually entered as static or fixed parameters, can be adjusted and optimized continuously or at regular intervals using current measurement data, and the process parameters that are relevant for drying and crosslinking can thus be adjusted according to the current conditions .

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EP20195498.9A 2020-09-10 2020-09-10 Système et procédé de commande pour machines d'impression permettant de régler et de surveiller les paramètres relatifs au séchage, à la migration et/ou à la réticulation Withdrawn EP3967495A1 (fr)

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CN115284733A (zh) * 2022-08-31 2022-11-04 西门子（中国）有限公司 凹版印刷机启动控制系统及方法
CN116843421A (zh) * 2023-07-05 2023-10-03 深圳市泰安达纸品包装有限公司 一种印刷品报价表的生成方法
EP4344876A1 (fr) * 2022-09-28 2024-04-03 Uteco Converting S.p.A. Système d'impression
US11966640B1 (en) 2022-09-22 2024-04-23 Hewlett-Packard Development Company, L.P. Adjust print settings using machine learning
CN118042053A (zh) * 2024-04-12 2024-05-14 四川汇利实业有限公司 一种印刷品质量在线检测方法和系统

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* Cited by examiner, † Cited by third party
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CN115284733A (zh) * 2022-08-31 2022-11-04 西门子（中国）有限公司 凹版印刷机启动控制系统及方法
CN115284733B (zh) * 2022-08-31 2023-10-03 西门子（中国）有限公司 凹版印刷机启动控制系统及方法
US11966640B1 (en) 2022-09-22 2024-04-23 Hewlett-Packard Development Company, L.P. Adjust print settings using machine learning
EP4344876A1 (fr) * 2022-09-28 2024-04-03 Uteco Converting S.p.A. Système d'impression
CN116843421A (zh) * 2023-07-05 2023-10-03 深圳市泰安达纸品包装有限公司 一种印刷品报价表的生成方法
CN116843421B (zh) * 2023-07-05 2024-02-23 深圳市泰安达纸品包装有限公司 一种印刷品报价表的生成方法
CN118042053A (zh) * 2024-04-12 2024-05-14 四川汇利实业有限公司 一种印刷品质量在线检测方法和系统

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