Method and data-based assistance system for an optimal adjustment of a textile machine

Abstract

The invention relates to a method and a data-based assistance system for an optimal adjustment of a textile machine for producing a textile product According to the invention, input parameters are received by means of a receiving unit, then at least one suitable adjustment recommendation is automatically determined for at least one specific machine component and / or for production parameters of the textile machine according to the at least one received input parameter; and then selectable output parameters are output, by means of an output unit, which is data-transmittingly coupled to the determining unit, and the data-based assistance system is designed for carrying out the method

Description

[0001] Process and data-based assistance system for optimal adjustment of a textile machine

[0002] The invention relates to a method and a data-based assistance system for optimal adjustment of a textile machine for producing a textile product.

[0003] The production of a defined textile product is complex and involves a multitude of settings on a textile machine. The raw materials used, such as fibers, fiber slivers, yarns, and fabrics, can exhibit significant variation in their properties due to natural fluctuations and the use of multiple blends. Almost all steps in the textile process chain require a high level of process expertise, and almost all textile machines offer the operator a wide variety of process parameters and machine components to cover the material requirements. Furthermore, the complexity of the materials to be processed, for example, in the form of dual- and triple-core yarns or recycled materials, is increasing from year to year, making textile machine settings even more difficult.

[0004] To optimally adjust a textile machine, the settings must be selected to suit the raw material and the production goal, such as maximum productivity or the highest quality. This adjustment is usually carried out by process experts. The settings encompass a multitude of individual parameters. These parameters influence the productivity of both the textile machine and other textile machines in the process chain, as well as the quality of the textile product produced by the textile machine or the other textile machine. Furthermore, the individual parameters exhibit interdependencies and interactions that affect the production outcome.

[0005] Adjusting a textile machine typically involves selecting the specific machine components required for the production process, such as clothings, rotors, splicing devices, bobbin holders, and other machine components. This selection depends, among other things, on the raw material and the type of further processing of the textile product. Following the component selection, the production parameters are usually adjusted, such as production speed, air pressure, draft, tension, and rotational speeds. However, the service manuals for the textile machine usually only provide a machine operator with a general guide to machine adjustment.

[0006] The quality of machine settings therefore depends to a large extent directly on the expertise of the machine operator. It is particularly difficult for inexperienced machine operators to achieve good machine settings. However, training machine operators is very complex and time-consuming. Furthermore, more and more experienced machine operators and service employees of machine manufacturers are retiring. As a result, more and more machine operators and service employees with little experience are operating the machines and are having difficulty finding good machine settings. Accordingly, on the one hand, the best possible quality of the manufactured textile product is often no longer achieved, and on the other hand, maintenance and repair costs increase due to the operation of textile machines that are not optimally adjusted.

[0007] The invention is therefore based on the object of providing a means which allows a machine operator to optimally adjust a textile machine without extensive prior knowledge, which thus also enables an inexperienced machine operator to reliably produce a high-quality textile product and which also reduces the maintenance and repair costs of the textile machine as best as possible.

[0008] The object is achieved according to the invention by a method according to claim 1 and a data-based assistance system according to claim 14. Advantageous developments of the invention are specified in the dependent claims.

[0009] The method according to the invention for obtaining a setting recommendation for a textile machine for producing a textile product initially carries out the following method steps: receiving input parameters by means of a receiving unit. The input parameter(s) is / are at least information about

[0010] (i) a raw material from which the textile product is manufactured,

[0011] (ii) a type of textile machine,

[0012] (iii) a production target of the textile machine or of a further textile machine downstream of the textile machine in the processing chain of the textile product, in particular with regard to the textile product to be produced by the textile machine or the further textile machine,

[0013] (iv) a type of further processing for the textile product produced following the manufacture of the textile product,

[0014] (v) climatic data prevailing in the production hall housing the textile machine and / or the other textile machine, and / or

[0015] (vi) at least one machine component of the further textile machine upstream and / or downstream of the textile machine in the processing chain of the textile product.

[0016] All this information corresponds to conditions which, either individually or in a combination of at least two of the conditions, can have an influence on the production of the textile product by the textile machine.

[0017] Subsequently, by means of a determination unit, at least one suitable setting recommendation for at least one specific machine component and / or for production parameters of the textile machine is automatically determined based on the received input parameters by means of a determination unit, for the production of the textile product by the textile machine and / or by the further textile machine, in particular stored in a readable data storage unit or newly generated by the determination unit and more preferably stored in the data storage unit after generation. The determination unit is coupled to the receiving unit and in particular to the data storage unit in a data-transmitting manner. A data-transmitting coupling can be implemented in the sense of the present invention in a conventional manner, preferably wirelessly and / or wired.At least the receiving unit, the detection unit, and / or the data storage unit can furthermore preferably be embodied as a computing unit. For the purposes of the present invention, a unit in the usual sense is understood to mean a unit that consumes electrical energy.

[0018] Subsequently, according to the invention, selectable output parameters containing information about the at least one determined setting recommendation are output by means of an output unit, wherein the output unit is coupled at least to the determination unit in a data-transmitting manner.

[0019] This allows a desired production target to be achieved or a desired textile product to be manufactured based on the recommended settings for the textile machine, tailored to the raw material used. The inventors recognized that optimized settings for a textile machine are only possible with many years of experience and are becoming increasingly complex due to the increasing number of settings to be made, the available machine components, and the process chains (i.e., the processing chain related to the textile product).Furthermore, the inventors recognized that only an electronic system can determine the optimal settings without extensive and time-consuming testing among the multitude of possible combinations of individual components and parameters, particularly due to the diverse interactions and dependencies between the individual components and parameters. This is the only way to achieve consistently high quality in the textile product or process product, for example, a fiber sliver material, a thread, or a textile fabric such as a fabric. The method according to the invention advantageously enables the textile machine to be adjusted with little to no prior knowledge. The machine operator is provided with setting recommendations that enable the optimal production of a desired textile product.

[0020] According to a further aspect of the present invention, a data-based assistance system is provided for implementing the method according to the invention, in particular according to one of the described embodiments. Corresponding components of the data-based assistance system can preferably have corresponding device-side configurations in order to be able to carry out or execute the described method-side steps.

[0021] The data-based assistance system can be a data storage unit comprising application software for a computing unit for carrying out the method or process steps and / or a device, in particular with at least one computing unit and / or a data storage unit. The data-based assistance system generally has the function of providing a setting recommendation for a machine operator based on data inputs and / or stored data. A setting recommendation, within the meaning of the present invention, is any recommendation that provides a selection of at least one parameter, a process sequence, and / or at least one machine component. Such selection options can also be understood as a recommendation for action.The data-based assistance system particularly supports the machine operator in processing any starting material, and especially complex starting materials such as, for example, dual- or triple-core yarns and / or recycled materials, in order to produce a desired textile product. Even starting materials with fluctuating material quality can be easily accommodated in this way.

[0022] The method and / or the assistance system can preferably be operated fundamentally by integrating at least one platform and preferably simultaneously on at least two, i.e., several, different platforms. The possible platforms can preferably be implemented, among other things, by machine controllers, human-machine interfaces, smartphones, handheld devices, computers, servers, data watches, data glasses, laptops, and any other computer and data processing systems. General provision as an internet page or via a web server is also preferred. The data-based assistance system can, for example, preferably be implemented separately from a textile machine and, in particular, separately from a machine controller of a textile machine as an independent and / or stand-alone unit.

[0023] Possible applications of the method and the data-based assistance system include, for example, use in splicing, winding, ring spinning, rotor spinning, air-jet spinning, friction spinning, and in further yarn processing, such as weaving, knitting, dyeing, or the like. Accordingly, the textile machine is preferably a machine for performing one or more of these methods. Particularly preferably, the textile machine is a spinning machine or a dishwasher with numerous identical workstations, wherein the method or the data-based assistance system can most preferably recommend setting recommendations for each, a specific number, or all of the workstations, for the machine components, or for at least one service unit operating the textile machine.

[0024] The method or the data-based assistance system provides optimized settings for the textile machine in order to produce the textile product as required. The textile product can be a final product, such as a piece of clothing or a fabric, or an intermediate product for further processing, in particular for industrial processing, such as a fiber ribbon, a thread, or a flat textile such as a piece of fabric. According to the invention, the input parameter(s) are received, whereby in this context, receiving is understood to mean any supply of corresponding data to the receiving unit.According to a preferred embodiment, at least one input parameter can be entered manually by a user at an input unit, and / or at least one input parameter can be automatically sent for receipt by the receiving unit, in particular in conjunction with another computer system, at least one control unit of the textile machine, and / or by means of a higher-level controller. Preferably, the receipt of the at least one input parameter is followed by a diagnosis of the input parameter, wherein particularly preferably the at least one input parameter is checked for possible inconsistencies, conflicting production targets, incompleteness, values ​​outside a normal range, and / or generally for possible errors.

[0025] The input parameter can be any data information regarding the raw material used to manufacture the textile product, in particular the material properties, and / or the type of textile machine to be used to manufacture the textile product. The input parameters of the raw material can be, for example, the size, dimension, material, mechanical and / or chemical properties of the raw material. Other input parameters can be, for example, a yarn type, a material composition, a twist direction, a fineness, strength properties, fiber length distribution, or the like.In addition, input parameters, for example climatic information such as temperature or humidity, can be at least one machine component used to manufacture the textile product, a type of further processing of the textile product following the manufacture of the textile product or at least one further textile machine upstream and / or downstream of the textile machine in the processing chain of the textile product. In addition, a production target of the textile machine or of a further textile machine downstream of the textile machine in the processing chain of the textile product can be taken into account within the framework of the input parameters. For example, the textile machine can be a flyer or a draw frame whose textile product is a defined fiber sliver. The fiber sliver assigned to the flyer or draw frame in the processing chain is defined as the fiber sliver.The subsequent textile machine following the draw frame can be a ring spinning machine for the roving frame, and a rotor spinning machine or air-jet spinning machine for the draw frame, each of which produces a yarn as a textile product. For example, a production target of the textile machine, i.e., the roving frame or the draw frame, with respect to the fiber sliver, can be used as an input parameter. Alternatively or additionally, a production target of the subsequent textile machine, i.e., the ring spinning machine, the rotor spinning machine, or the air-jet spinning machine, with respect to the yarn to be produced, can be used as an input parameter.

[0026] For the purposes of the present invention, a production objective, particularly with regard to the textile product to be manufactured, is to be understood as an objective for production, a requirement of the textile machine and / or a desired property of the resulting textile product.

[0027] The automatic determination of at least one setting recommendation for at least one specific machine component and / or for production parameters of the textile machine, which is stored readably in a data storage unit for the manufacture of the textile product by the textile machine and / or by the further textile machine, as a function of the received input parameter(s), is carried out according to the invention by a determination unit which is particularly designed to be able to carry out an independent calculation and a selection of the setting recommendation. Within the scope of the automatic determination, a calculation is preferably carried out on the basis of at least one received input parameter, which calculation optimizes available production parameters and in particular variable production parameters and then, based thereon and as a function of the at least one received input parameter, determines a recommendation for a preferred setting.During automatic determination, previously recorded and / or stored data can also be taken into account. During automatic determination, a setting recommendation stored in a data storage unit can be determined, or a new setting recommendation can be generated or created, which is then preferably stored in the data storage unit in a readable format.

[0028] A specific machine component is understood, in particular, to be an interchangeable, variable, adjustable, and / or optionally usable component, part, and / or assembly of the textile machine or the further textile machine. Production parameters are understood to mean at least some of the settings of the textile machine and preferably all settings that must be made to manufacture the textile product and / or are variable, i.e., can be varied by a machine operator.The setting recommendation can be assigned directly to a determined production parameter or to values ​​derived from it. The setting recommendation is preferably adapted to the respective inputs and / or values ​​required by the textile machine for operation, so that these can only be output to the textile machine for selection by a machine operator of one or more output parameters corresponding to the setting recommendation or, alternatively, automatically. When output for selection by the machine operator, they only have to accept or confirm the output parameter(s) corresponding to the setting recommendation. The output parameter(s) can generally refer to all parameters that can be set on the respective textile machine, purely for example air pressure settings, process flow settings and / or mechanical settings.

[0029] The output parameter(s) particularly preferably correspond to a setting recommendation and particularly preferably to several setting recommendations, in particular in the form of several possible sets of preferred settings for the production of the textile product, taking into account the input parameter(s). Very particularly preferably, the output parameter(s) is / are output together with explanatory information to the machine operator, so that the operator can make a decision and appropriate selection based thereon. Overall, the output parameter(s) can in particular be preferred production or target parameters, settings, defined processes, and / or component recommendations for the production of the textile product.

[0030] The output of the output parameter(s) represents a suggestion, particularly for the machine operator of the textile machine, for achieving optimal production of the textile product taking into account the input parameter(s). It is also preferred that the output parameter or the underlying setting recommendation be checked before output, particularly for possible inconsistencies, values ​​that conflict with the production target, incompleteness, values ​​outside a normal range, and / or generally for possible errors. In addition, it is particularly preferred that the machine operator or a control device be notified if values ​​or recommended components do not correspond to a standard recommendation and / or deviate significantly from established standard values.

[0031] A preferred embodiment of the method provides that the automatic determination step is carried out using a database-based approach. This involves a direct assignment of the at least one input parameter to at least one specific output parameter. The direct assignment can be determined or calculated completely automatically or, in particular, specified by a machine operator. Furthermore, it is also conceivable to have the assignment calculated automatically and subsequently checked and, if necessary, corrected by a machine operator, and only then stored in a data storage unit with fixed assignments.

[0032] Furthermore, according to a preferred embodiment, in a case where there is no assignment of an output parameter to an input parameter in the data storage unit, it is also conceivable to search for data records with the most similar input parameter and to make one or more setting recommendations based on the similarity and output them accordingly. In this case, it is conceivable to weight the recommendation or to save the suggestion accepted by the machine operator as a future direct assignment and / or to weight this suggestion selected by the machine operator. Furthermore, it is conceivable to record feedback from the machine operator after the start of production of the textile product and / or as part of a quality control of the textile product in order to improve the quality of future recommendations and / or to rule out unsuitable assignments in the future.

[0033] In general, it is preferred that the output of the output parameter(s) be saved and, in particular, stored as recipes that can be retrieved later. Furthermore, an exchange of the outputs and, in particular, of saved recipes between machine operators and / or between different textile machines or devices on which the method according to the invention is executed is preferably possible. Storage can, or preferably generally, be carried out in any manner and at any storage location, for example, locally, at the backend, centrally, or decentrally.

[0034] In a further preferred development, the automatic determination step is carried out in addition to or alternatively to a database-based approach using a model-based approach, which further preferably takes into account a relationship between the at least one input parameter and the production goals, the at least one output parameter from optimized or preferred settings, and / or which likewise preferably further optimizes or improves the output parameter(s) using machine learning. In principle, various models and methods can be used in the model-based approach. For example, simple decision tree models can be applied directly based on the input parameter(s) or on parameters derived therefrom in order to obtain at least one output parameter.

[0035] A particularly preferred embodiment of the data-based assistance system provides that the automatic determination step is performed in addition to or alternatively to a database-based approach based on statistical models and / or machine learning models. The statistical model(s) can be, for example, regressions, random forests, or support vector machines. The machine learning models are preferably deep learning models, and neural networks are particularly preferred.

[0036] To enable continuous improvement of the method, in a preferred embodiment, data sets comprising input parameters and output parameters, in particular optimal production parameters, optimized settings, and / or component recommendations, are stored automatically and / or by a user and subsequently used continuously or intermittently to improve the automatic determination and, in particular, to improve existing prediction models or to generate new prediction models. Generally, it is preferred that the automatic determination step be based on one or more prediction models. Furthermore, a learning capability and the associated continuous improvement based on the received data, feedback from a machine operator, inputs from the manufacturer and / or the operator of the textile machine, and / or from any other sources is generally preferred.It is particularly preferred that this ensures continuous or periodic learning.

[0037] A textile machine can, in principle, be any machine that manufactures and / or processes a textile product, although a yarn-manufacturing or bobbin-manufacturing textile machine is preferred. Depending on the type of textile machine, the production objectives can vary considerably. For example, the production objectives for a yarn-manufacturing textile machine can be maximum yarn uniformity, maximum productivity, a defined count, a defined twist, piecing that is as uniform as possible, and / or the highest possible yarn quality. For a bobbin-manufacturing textile machine, the production objectives can be a specifically defined or maximum bobbin density, maximum productivity, splice that is as uniform as possible, and / or the highest possible quality.For other textile machine types, such as weaving machines, a production objective can be, for example, the uniformity or the high basis weight. For roving machines, cards, and draw frames, a production objective can be, in particular, the uniformity or fineness of the fiber sliver.

[0038] Preferably, the setting recommendations issued via output parameters for textile machine components include specific clothings, rotors, spinnerets, drafting system components, ring traveler systems, tube formats, take-off units, splicing devices, bobbin holders, and / or weaving machine type, reed, knitting machine type, and knitting needle type. Recommendations can also be issued for components of other textile machines that can be considered during further processing of the textile product. These recommendations can be considered manually or automatically, for example, the latter being particularly important when the textile machine and the other textile machine are linked to each other for data transmission.

[0039] Further preferably, recommended production parameters may include, for example, the production speed, the air pressure, the draft, the tension and / or the speeds of the textile machine and / or the further textile machine.

[0040] Finally, a preferred embodiment is one in which the input parameter(s) are entered manually by the user of the textile machine and / or can be read directly from the textile machine. Alternatively or additionally, it is preferred that the setting recommendations are entered manually into the textile machine, in particular into a human-machine interface, and / or transmitted directly to the textile machine. According to a preferred embodiment, input parameters can be read from the textile machine and / or from the receiving unit and / or setting recommendations can be transmitted in any desired manner, in particular wired or wirelessly, for example, using NFC, WLAN, USB, or CAN.As part of an automatic and / or continuous improvement of the process, particularly the setting recommendation to be issued and / or the underlying models, it is also conceivable to integrate a material analysis test machine into the process or at least to connect the receiving unit to such a machine for data exchange. This allows the component and setting to be directly assigned to a material measurement, and the result of the material measurement can be returned directly to the receiving unit.

[0041] An embodiment of a method and data-based assistance system according to the invention is described in more detail below.

[0042] To ensure optimal selection of machine components and the best possible settings for a textile machine, especially a dishwasher, and thus produce an optimal textile product, the machine operator first logs into a data-based assistance system, for example, using a tablet computer. This user identification helps access data from previous uses, retrieve user-specific settings, and / or adapt the assistance system's functionality to the user or their skill level. Furthermore, previously saved favorites by or for this user can be retrieved.

[0043] In the next step, the user is prompted to enter the parameters of the raw material and the textile machine used. The textile machine is identified by its type designation or serial number. It is also conceivable that the data-based assistance system is provided only for a specific textile machine type, meaning that the detailed parameters of the associated textile machine are already stored and therefore do not need to be entered.

[0044] As parameters for the starting material, information about the yarn component used as the starting material is first entered, particularly the type and / or material of the yarn used, as well as the respective proportions of the materials. The yarn properties of the starting material are then either retrieved from memory or entered by the user. For example, the yarn type, the twist direction of the yarn, and the yarn count can be specified.

[0045] The data-based assistance system then automatically determines the ideal machine components, suggesting an optimal combination of splicing components. This includes, among other things, the type of splicer, the design of the opening tube, the prism to be used, the design of the distribution plate, and the shear spacing. Alternatively, the data-based assistance system also offers manual selection of machine components. However, only splicing components that are compatible with the source material according to the recorded input parameters of the source material are suggested and / or selectable. Finally, the user confirms which machine components will be used in the data-based assistance system.

[0046] The textile product is manufactured based on the received input parameters and the machine components recommended and output by the assistance system, which are then selected or confirmed by the user. In particular, machine learning models predict opening and splicing settings for the dishwasher. These optimal settings can then be manually entered by the user at the dishwasher's control panel or the winding unit, or they can be wirelessly transmitted directly from the data-based assistance system to the dishwasher and / or the winding unit. With these optimized settings and the selected optimal machine components, the best possible production of a textile product is then possible.

[0047] Another version of a data-based assistance system differs from the previous version only in that, as part of the input parameters, the user is also asked to specify a production goal. Here, the user can, for example, select the best possible quality for the textile product or a particularly high efficiency and / or speed for the production of the textile product. This selection is then taken into account when recommending optimized settings and / or optimal components.

[0048] In order to improve the result of the recommendation of optimized settings and / or optimal machine components over time, the result of the recommendation can also be entered into the data-based assistance system. This can be done based on user information about the resulting textile product. The data-based assistance system queries various quality characteristics, such as the uniformity of the yarn, deviations in yarn thickness, the surface quality of the yarn, and the occurrence of defects in the yarn path. Furthermore, the data-based assistance system can also be linked to a quality control device or exchange data with it on the quality of the textile product and / or on any defects that have occurred. Based on this feedback, the quality and accuracy of the recommendations can then be improved using machine learning models to obtain an even better textile product.

Claims

Claims Procedure for obtaining a setting recommendation for a textile machine for the manufacture of a textile product comprising the steps: Receiving input parameters by means of a receiving unit, wherein the input parameter(s) contain at least one piece of data information about (i) a raw material from which the textile product is manufactured, (ii) a type of machine and / or at least one machine component of the textile machine required for the production of the textile product, (iii) a production target of the textile machine or of a further textile machine downstream of the textile machine in the processing chain of the textile product, in particular with regard to the textile product to be produced by the textile machine or the further textile machine, (iv) a further processing method for the manufactured textile product following the manufacture of the textile product, (v) Climate data prevailing in the production hall housing the textile machine and / or the other textile machine, and / or (vi) include at least one machine component of a further textile machine located upstream and / or downstream of the textile machine in the processing chain of the textile product, and subsequently Automatic determination of at least one setting recommendation suitable for the production of the textile product by the textile machine and / or by the further textile machine for at least one specific machine component and / or for production parameters of the textile machine as a function of the at least one received input parameter by means of a determination unit which is coupled to the receiving unit for data transmission, in particular forming a computing unit with the receiving unit, and subsequently Output of at least one selectable output parameter, which contains data information about the at least one determined setting recommendation, by means of an output unit which is coupled to the determination unit for data transmission. A method according to claim 1, characterized in that the setting recommendation is read from or regenerated by the determination unit from a data storage unit, and in particular, is stored in the data storage unit after generation. A method according to claim 1 or 2, characterized in that the step of automatic determination is carried out using a database-based approach in which at least one of the input parameters is automatically assigned to at least one of the output parameters. A method according to any of the preceding claims, characterized in that the step of automatic determination is carried out using a model-based approach in which a specific relationship between at least one of the input parameters and at least one output parameter is defined.A method according to claim 4 in conjunction with claim 3, characterized in that a selection step for choosing the database-based or model-based approach takes place before the automatic determination step, wherein the selection is made manually by an operator or automatically based on predefined decision processes. A method according to any one of claims 1 to 5, characterized in that the automatic determination step is based on statistical models and / or on machine learning models.A method according to at least one of the preceding claims, characterized in that at least one input parameter and, in particular, at least one output parameter selected based on the input parameter are stored readably in the or a further data storage unit and are subsequently used continuously or intermittently in the step of automatically determining the improvement of existing prediction models or the generation of new prediction models. A method according to at least one of the preceding claims, characterized in that the information about the production goal with regard to the textile. The method according to at least one of the preceding claims, characterized in that the step of receiving input parameters is preceded by a step of manually entering at least one of the input parameters at an input unit which is coupled to the receiving unit for data transmission.A method according to at least one of the preceding claims, characterized in that the output parameter(s) include information about components of the textile machine and / or the further textile machine, such as, in particular, specific yarn sets, rotors, spinnerets, drafting unit components, ring runner system, core formats, take-up units, splicing materials, bobbin holders, weaving machine type, reed, knitting machine type, knitting needle type. A method according to at least one of the preceding claims, characterized in that the output parameter for the setting recommendation for the production parameter is information about the production speed, air pressure, warpage, tension, and / or rotational speed of the textile machine.A method according to at least one of the preceding claims, characterized in that the input parameter(s) are read from the textile machine by means of a readout unit before the receiving step and transmitted to the receiving unit coupled to the readout unit for data transmission. A method according to at least one of the preceding claims, characterized in that the output step is followed by a step of manually entering at least one selected output parameter at an input unit of the textile machine or a step of selecting at least one output parameter at the output unit, followed by a step of transmitting the at least one selected output parameter to a control unit of the textile machine. The following is a data-based assistance system for carrying out the method according to at least one of the preceding claims, wherein the assistance system comprises the receiving unit for receiving the input parameter(s), the determination unit for automatically determining at least one setting recommendation for specific machine components and / or production parameters, stored in a data storage unit and readable for the manufacture of the textile product, depending on the received input parameters, and the output unit for outputting the selectable output parameters, wherein the data storage unit is coupled to the assistance system for data transmission or is included by the assistance system.