Method for optimally adjusting textile machine and data-based assistance system

Abstract

The invention relates to a method and a data-based assistance system for optimally adjusting a textile machine for producing textile products. According to the invention, input parameters are received by means of a receiving unit, and then at least one suitable adjustment suggestion with respect to at least one specific machine component of the textile machine and / or with respect to production parameters of the textile machine is automatically ascertained on the basis of the at least one received input parameter, and subsequently outputting the selectable output parameter by means of an output unit which is coupled at least to the ascertaining unit in a data-transmitting manner, and the data-based auxiliary system is designed to carry out the method.

Description

[0001] The invention relates to a method and a data-based assistance system for optimally adjusting a textile machine for producing textile products.

[0002] The production of defined textile products is complex and involves a large number of adjustments to the textile machines. The raw materials used, such as fibers, fiber strands, threads and flat textiles, can have a high degree of variation in their properties, for example due to natural deviations and the use of multiple mixtures. Almost all steps in the textile process chain require a high degree of process know-how, and almost all textile machines offer the operator a wide variety of process parameters and machine components in order to cover the material requirements. In addition, the complexity of the materials to be processed, for example in the form of double and triple cores or recycled materials, increases year by year, which makes the adjustment of the textile machines even more difficult.

[0003] In order to optimally adjust the textile machine, the adjustment must be selected to match the raw material and the production target, such as, for example, the maximum productivity or the highest quality. This adjustment is usually performed by a process expert. The adjustment includes a large number of individual parameters. These parameters influence not only the productivity of the textile machine but also the productivity of other textile machines that follow in the process chain, and the quality of the textile products produced by the textile machine or other textile machines. In addition, the individual parameters are interdependent and mutually influential, and they all influence the production result.

[0004] The adjustment of a textile machine typically includes the selection of production-specific machine components of the textile machine, such as, for example, the selection of card clothing, spinning rotors, splicing elements, bobbin receivers and other machine components. This selection depends, among other things, on the raw materials and the type of further processing of the textile product. Following the selection of the components, production parameters such as, for example, production speed, air pressure, draft, tension and rotational speed are usually adjusted. However, the service manuals of textile machines usually only provide the machine operator with general points for adjusting the machine.

[0005] The quality of the machine setting is thus directly dependent to a high degree on the expertise of the machine operator. It is particularly difficult for inexperienced machine operators to perform a good machine setting. However, the training of machine operators is very expensive and time-consuming. In addition, 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 less experience operate the machines and it is difficult to find a good machine setting. On the one hand, the best possible quality of the manufactured textile products is accordingly often no longer achieved, and on the other hand, the maintenance and repair costs are increased due to the operation of textile machines that are not optimally adjusted.

[0006] The object of the present invention is therefore to provide a measure which allows a machine operator to optimally adjust a textile machine without extensive basic knowledge, which measure thus enables even inexperienced machine operators to reliably produce high-quality textile products and which measure furthermore reduces the maintenance and repair costs of the textile machine in particular as best as possible.

[0007] This 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 described in the dependent claims.

[0008] The method according to the invention for obtaining a setting proposal for a textile machine for producing textile products firstly carries out the reception of input parameters by means of a receiving unit as a method step. The input parameters are at least information about:

[0009] (i) raw materials from which the textile products are manufactured;

[0010] (ii) the type of textile machine;

[0011] (iii) the production objectives of a textile machine or of another textile machine which follows it in the processing chain of the textile product, in particular with regard to the textile product to be manufactured by the textile machine or by the other textile machine;

[0012] (iv) the further processing of the manufactured textile product immediately after its manufacture;

[0013] (v) data on the climate existing in the production room housing the textile machine and / or another textile machine; and / or

[0014] (vi) at least one machine component of another textile machine which is arranged upstream and / or downstream of the textile machine in the processing chain of the textile product.

[0015] All of this information corresponds to conditions which, either alone or in combination of at least two of these conditions, can have an influence on the process of producing a textile product by means of a textile machine.

[0016] Next, at least one suitable adjustment suggestion for at least one specific machine component of the textile machine and / or for production parameters of the textile machine, which is stored readablely in a data storage unit or regenerated by the ascertainment unit and preferably to be stored in the data storage unit after generation, is automatically ascertained by means of an ascertainment unit depending on the received input parameters for a process for manufacturing a textile product by a textile machine and / or by another textile machine, wherein the ascertainment unit is coupled to the receiving unit and in particular the data storage unit for data transmission. The coupling for data transmission can be realized in a conventional manner, preferably wirelessly and / or wiredly, in the sense of the present invention. In addition, at least the receiving unit, the ascertainment unit and / or the data storage unit can preferably be formed by a computing unit. In the sense of the present invention, a "unit" refers to a unit that consumes electrical energy in the conventional sense.

[0017] According to the invention, a selectable output parameter is then outputted, which contains information about at least one ascertained adjustment proposal, by means of an output unit, wherein the output unit is coupled at least to the ascertainment unit for data transmission.

[0018] Thus, on the basis of the determined control proposals for the textile machine which are adapted to the raw materials used, desired production targets can be achieved or desired textile products can be produced.

[0019] The inventors have recognized that an optimized adjustment of a textile machine can only be achieved with years of experience and becomes increasingly complex due to the increasing number of adjustments to be made and available machine components and process chains, that is, processing chains for textile products. In addition, the inventors have recognized that only one electronic system is capable of finding the corresponding optimal adjustment under a large number of possible combinations of individual components and parameters, especially based on the various mutual influences and dependencies between the individual components and parameters without extensive and very time-consuming attempts, and only in this way can the same high quality of textile products or process products, such as fiber strip materials, yarns or textile flat structures, such as fabrics, be achieved. In this regard, the method according to the invention allows the adjustment of a textile machine in an advantageous manner with little basic knowledge or even without basic knowledge. For this purpose, adjustment suggestions are provided to the machine operator, with which the desired textile product can be manufactured in the best possible way.

[0020] According to another aspect of the 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. The corresponding components of the data-based assistance system can preferably have a corresponding design in terms of the device in order to be able to implement or execute the steps of the described method.

[0021] The data-based auxiliary system can be a data storage unit including application software for a computing unit for implementing method steps or process steps and / or a device having at least one computing unit and / or data storage unit in particular. The data-based auxiliary system has in principle the function of providing adjustment suggestions to the machine operator based on data input and / or stored data. "Adjustment suggestions" can be understood in the sense of the present invention as any of the following suggestions: the suggestion provides a selection for at least one parameter, process and / or at least one machine component. Such selection options can also be understood as processing suggestions. The data-based auxiliary system particularly preferably supports the machine operator when processing any raw materials and particularly preferably complex raw materials, such as double or triple core yarns (Dual-oder Tripple-Core-Garnen) and / or recycled materials, so as to be able to produce the desired textile products. Even raw materials with fluctuating material qualities can be easily taken into account in this way.

[0022] Here, the method and / or the auxiliary system can preferably be run in principle in conjunction with at least one platform and preferably simultaneously on at least two, i.e. a plurality of different platforms. Possible platforms can preferably be formed here by machine control mechanisms, human-machine interfaces, smartphones, laptops, computers, servers, smart watches, smart glasses, notebook computers and any other computer systems and data processing systems. It is also preferred to provide them as web pages or by means of a web server. The data-based auxiliary system can be configured as an independent and / or autonomous unit, for example, separately from the textile machine and in particular separately from the machine control mechanism of the textile machine.

[0023] Possible applications of the method and the data-based assistance system are, for example, use in splicing, winding, ring spinning, rotor spinning, open-end spinning, friction spinning and use in further processing of yarn, such as weaving, knitting, dyeing, etc. The textile machine is preferably a machine for carrying out one or more of these methods. It is particularly preferred that the textile machine is a spinning machine or a winding machine with a large number of mutually identical working positions, wherein the method or the data-based assistance system can very particularly preferably recommend the adjustment proposal for each working position, a specific number of working positions or for all working positions, for a machine component or for at least one service component operating the textile machine.

[0024] The method or the data-based auxiliary system provides optimized control of the textile machine in order to be able to produce textile products according to demand. The textile products can be end products, such as clothing or fabrics, or intermediate products for further processing, in particular for industrial further processing, such as fiber strips, yarns or flat fabrics, such as cloth.

[0025] According to the invention, the input parameters are received, wherein in this context "receiving" means "arbitrarily supplying the corresponding data to a receiving unit". In this case, according to a preferred embodiment, at least one input parameter can be manually input by a user at the input unit and / or at least one input parameter is automatically transmitted, in particular in conjunction with another computer system, at least one control unit of the textile machine and / or by means of a superordinate control device, in order to be received by the receiving unit. Preferably, immediately after receiving the at least one input parameter, a diagnosis of the input parameter is performed, wherein the at least one input parameter is particularly preferably checked for possible contradictions, opposing production targets, imperfections, values ​​outside the usual range and / or in general for possible errors.

[0026] The input parameters can be any data information related to the raw materials used for manufacturing textile products, especially material properties and / or the type of textile machine to be used for manufacturing textile products. The input parameters of the raw materials can be, for example, the specifications, dimensions, materials, mechanical and / or chemical properties of the raw materials. Other input parameters can be, for example, the type of thread, material composition, twist direction, fineness, strength properties, fiber length distribution, etc. In addition, the input parameters can be, for example, climate information such as temperature or air humidity, at least one machine component for manufacturing textile products, the further processing method of the textile product immediately after the manufacture of the textile product, or at least one other textile machine that is placed before or after the textile machine in the processing chain of the textile product. In addition, within the scope of the input parameters, the production objectives of the textile machine or another textile machine that is placed after the textile machine in the processing chain of the textile product can be taken into account. For example, the textile machine can be a roving frame or a drawing frame, and its textile product is a defined fiber strip. As a further textile machine following the roving frame or the draw frame in the processing chain, a ring spinning machine can be considered for the roving frame and a rotor spinning machine or an open-end spinning machine can be considered for the draw frame, which each produce a thread as a textile product. Thus, for example, a production target of a textile machine, i.e. a roving frame or a draw frame, with respect to the fiber strand can be used as an input parameter. As an alternative or supplement, in particular a production target of another textile machine, i.e. a ring spinning machine, a rotor spinning machine or an open-end spinning machine, with respect to the thread to be produced can be used as an input parameter.

[0027] In the sense of the present invention, “production targets, in particular with regard to the textile product to be produced” refer in principle to target settings for production, requirements for textile machines and / or desired properties of the resulting textile product.

[0028] Automatically ascertaining at least one adjustment suggestion for at least one specific machine component of a textile machine and / or for production parameters of a textile machine, which is readable and stored in a data storage unit for manufacturing a textile product by a textile machine and / or by another textile machine, depending on the received input parameters, according to the invention, by an ascertaining unit, which is particularly designed to be able to perform independent calculations and selections of adjustment suggestions. Within the scope of the automatic ascertainment, preferably based on at least one received input parameter, a calculation is performed, which optimizes the available production parameters and in particular variable production parameters, and then on this basis, depending on at least one received input parameter, a suggestion for an adjustment variable to be optimized is ascertained. In the automatic ascertainment, for example, previously recorded data and / or stored data can also be taken into account. In the process of the automatic ascertainment, the adjustment suggestions stored in the data storage unit can be ascertained or new adjustment suggestions can be generated or produced, which new adjustment suggestions are then preferably stored readable in the data storage unit.

[0029] "Specific machine components" are in particular replaceable, changeable, adjustable and / or preferably usable components, components and / or structural units of the textile machine or of another textile machine. "Production parameters" are at least part of the adjustments of the textile machine and preferably all adjustments that have to be set for the production of textile products and / or are variable, i.e. can be changed by the machine operator.

[0030] The adjustment suggestions can be assigned not only directly to the production parameters ascertained or also to values ​​derived therefrom, wherein the adjustment suggestions are preferably matched to the corresponding inputs and / or values ​​required for the future operation of the textile machine, so that they can only be output to the textile machine by the machine operator or, as an alternative, automatically output to the textile machine corresponding to the selection of one or more of the adjustment suggestions. In the case of output by the machine operator for selection, the operator only has to accept or confirm the output parameters corresponding to the adjustment suggestions. The output parameters outputted can in principle relate to all parameters that can be adjusted on the corresponding textile machine, in the case of purely exemplary examples, to air pressure control, process control and / or mechanical control.

[0031] The output parameter particularly preferably corresponds to a setting proposal, taking into account the input parameter, and particularly preferably corresponds to a plurality of setting proposals, particularly in the form of a plurality of possible groups of settings to be preferred for the production of textile products. Very particularly preferably, the output parameter is output together with the interpreted information to the machine operator so that he can make a decision and a corresponding selection on this basis. Overall, the output parameter is particularly a production parameter or a target parameter, a setting, a defined process and / or a component proposal that is preferred for the production of textile materials.

[0032] The output of the output parameters is a suggestion, in particular for a machine operator of a textile machine, in order to achieve an optimal production of the textile product taking into account the input parameters. It is also preferred that the output parameters or the underlying adjustment suggestion are checked before the output, in particular for possible contradictions, values ​​that are contrary to production targets, imperfections, values ​​outside the usual range and / or generally for possible errors. In addition, if the values ​​or the recommended components do not correspond to the standard suggestions and / or differ significantly from the established standard values, this is particularly preferably notified to the machine operator or the control.

[0033] A preferred embodiment of the method provides that the step of automatic ascertainment is performed by means of a database-based approach. In this case, at least one input parameter is directly assigned to at least one specific output parameter. In this case, the direct assignment can not only be ascertained or calculated completely automatically, but can also be predefined in particular by the machine operator. In addition, it is also conceivable that the assignment can be calculated automatically and then monitored by the machine operator and, if necessary, corrected and only then recorded in the data storage unit with a fixed assignment.

[0034] Furthermore, according to a preferred embodiment, it is also conceivable that, in the case of no assignment of output parameters to input parameters in the data storage unit, a data record with input parameters that is as similar as possible can be searched for and one or more adjustment suggestions can be completed on the basis of the similarity and output accordingly. In this case, not only the weighting of the suggestions or the storage of the suggestions assumed by the machine operator can be conceived as a future direct assignment and / or for weighting this suggestion selected by the machine operator. Furthermore, it is conceivable to record the feedback of the machine operator after the start of the production of the textile product and / or within the scope of the quality monitoring of the textile product in order to improve the quality of future suggestions and / or to exclude inappropriate assignments in the future.

[0035] It is generally preferred that the output of the output parameters is stored and in particular saved as a processing method which can be called up again later. Furthermore, it is preferably possible to exchange the outputs and in particular the stored processing methods between machine operators and / or between different textile machines or devices on which the method according to the invention is run. The storage can be carried out here or preferably in general in any desired manner and at any desired storage location, for example locally, centrally or decentrally in a back-end.

[0036] In a further preferred development, as a supplement or alternative to the database-based approach, the step of automatically determining is performed with the aid of a model-based approach, which further preferably takes into account the connection between at least one input parameter and the production target from at least one output parameter that is optimized or preferably adjusted, and / or which further optimizes or improves the output parameter, preferably also with the aid of machine learning. In principle, different models and methods can be used in the model-based approach. Thus, for example, a simple decision tree model can be used directly based on the input parameters or based on parameters derived therefrom in order to obtain at least one output parameter.

[0037] A particularly preferred embodiment of the data-based auxiliary system provides that, as a supplement or alternative to the database-based approach, the step of automatically determining is performed based on a statistical model and / or a machine-learning model. The statistical model can be, for example, a regression, a random forest or a support vector machine. The machine-learning model is preferably a deep learning model and particularly preferably uses a neural network.

[0038] In order to enable continuous improvement of the method, in a preferred embodiment, data records from input parameters and output parameters, in particular data records of optimal production parameters, optimized adjustments and / or component recommendations are automatically and / or by the user and are subsequently used continuously or intermittently to improve the automatic ascertainment and in particular to improve existing forecast models or to generate new forecast models. It is generally preferred that the step of automatic ascertainment is based on one or more forecast models. In addition, it is generally preferred that the learning capability and the continuous improvement based on the recommended data, feedback from the machine operator, inputs from the manufacturer and / or operator of the textile machine and / or inputs from any other source are also preferred. It is very particularly preferred that continuous or periodic joint learning is ensured in this way.

[0039] In principle, a textile machine can be any machine for manufacturing and / or processing textile products, of which a design as a textile machine for manufacturing thread or for manufacturing bobbins is preferred. Depending on the type of textile machine, the production goals can be clearly distinguished from each other. Therefore, the production goal of a textile machine for manufacturing thread can be the highest thread uniformity, the highest productivity, a defined fineness, a defined twist, as uniform a spinning head as possible and / or the greatest possible thread quality. For a textile machine for manufacturing bobbins, the production goal can be a specifically defined or maximum bobbin density, the maximum productivity, as uniform a twist as possible and / or the greatest possible quality. For other types of textile machines, such as looms, the production goal can be, for example, the uniformity or level of weight per unit area. For roving frames, carding machines and drawing frames, the production goal can be in particular the uniformity or fineness of the fiber strips.

[0040] The setting suggestions for components of the textile machine outputted by means of the output parameters are preferably, for example, specific card clothings, rotors, spinning nozzles, drafting device components, ring-tireurette systems, bobbin forms, drawing units, splicing devices, bobbin receivers and / or loom types, reeds, knitting machine types, needle types. It is also possible to output suggestions for components of other textile machines, which suggestions can be taken into account during the further processing of the textile product. These suggestions can be taken into account, for example, manually or automatically, in the latter case in particular by coupling the textile machine to another textile machine for data transmission.

[0041] Furthermore, the recommended production parameters can preferably include, for example, the production speed, air pressure, draft, tension and / or rotational speed of the textile machine and / or of another textile machine.

[0042] Finally, a design is preferred in which the input parameters can be manually input by a user of the textile machine and / or read directly from the textile machine. As an alternative or in addition, it is preferred that the adjustment suggestion is manually input into the textile machine, in particular into a human-machine interface and / or is directly transmitted to the textile machine. Here, according to a preferred embodiment, the reading of the input parameters from the textile machine and / or from the receiving unit and / or the transmission of the adjustment suggestion can in principle be carried out in any manner, in particular wired or wirelessly, for example by means of NFC, WLAN, USB or CAN.

[0043] Within the scope of the automatic and / or continuous improvement of the method, in particular of the control proposals to be output and / or the basic model, it is also conceivable to integrate a material analysis and testing machine into the method or at least to connect the receiving unit to such a material analysis and testing machine for data exchange. Thus, the components and controls can be directly assigned to the material measurement and the results of the material measurement can be directly returned to the receiving unit.

[0044] An exemplary embodiment of the method and the data-based assistance system according to the present invention will be described in detail below.

[0045] In order to select the best possible machine component or the best possible setting for a textile machine, in particular a winding machine, and thus be able to produce the best textile product, the machine operator first logs in to the data-based assistance system, for example using a tablet computer. This identification of the user helps to call up data on previous usage, to call up user-dependent settings and / or to adapt the functions of the assistance system to the user or his level of competence. In addition, preferences previously stored by or for this user can be called up.

[0046] In the next step, the user is asked to enter the parameters of the raw material and the textile machine used. The textile machine is identified by a model or serial number. It is also conceivable that the data-based auxiliary system is only provided for specific textile machine types, and the detailed parameters of the associated textile machine are thus already stored and do not need to be entered accordingly.

[0047] As parameters of the raw material, the thread composition used as raw material is first specified, and in particular the type and / or material of the thread used and the corresponding quantity proportions of the material are entered. The thread properties of the raw material are then either called up from a memory or entered by the user, wherein for example the thread type, the twist direction of the thread and the thread fineness can be specified.

[0048] Next, the ideal machine components are automatically identified by a data-based auxiliary system, wherein the program recommends the best combination of splicing components. This also involves the type of splicer, the design of the opening tube, the can to be used, the design of the distribution plate and the shearing distance. As an alternative, the data-based auxiliary system also provides for the manual selection of machine components, but only the following splicing components are recommended and / or can be selected: the splicing components are compatible with the raw materials according to the recorded input parameters of the raw materials. The user finally confirms which machine components to use in the data-based auxiliary system.

[0049] The textile product is manufactured based on the recommended input parameters and the machine components recommended, outputted and subsequently selected or confirmed by the user by the auxiliary system on this basis. In particular for the winding machine, the opening and splicing control is predicted by a machine learning model. These optimal controls can then be manually input by the user at the control of the winding machine or the winding station, or directly transmitted wirelessly to the winding machine and / or the winding station by the data-based auxiliary system. The textile product can then be manufactured in the best possible manner using these optimized controls and the selected optimal machine components.

[0050] Another embodiment of the data-based assistance system differs from the previous embodiments only in that, within the scope of recording the input parameters, the user is also additionally queried for production targets, wherein the user can here, for example, select the best possible quality of the textile product or a particularly high efficiency and / or speed of the production of the textile product. This selection is then taken into account when recommending the optimized settings and / or when recommending the best components.

[0051] In order to improve the recommendations of the optimized adjustment and / or optimal machine components over time, the data-based assistance system can also input the recommendations. This can be done based on the user's specifications about the obtained textile product, wherein the data-based assistance system queries different quality characteristics, such as thread uniformity, deviations in thread thickness, thread surface quality and the occurrence of errors in thread direction. In addition, the data-based assistance system can also be coupled to a device for quality supervision or exchange data about the quality of the textile product and / or about the errors that occur. Then, based on such feedback, the quality and accuracy of the recommendations can be improved with the help of machine learning models in order to obtain even better textile products.

Claims

1. A method for obtaining a recommendation for adjusting a textile machine for manufacturing a textile product, comprising the following steps: - receiving an input parameter by means of a receiving unit, wherein the input parameter contains at least one piece of data information about: (i) raw materials from which the textile products are manufactured; (ii) the machine type of a textile machine and / or at least one machine component necessary for producing said textile product; (iii) the production objectives of the textile machine or of another textile machine that follows it in the processing chain for the textile product, in particular with regard to the textile product to be manufactured by the textile machine or the other textile machine; (iv) the further processing of the manufactured textile product immediately after its manufacture; (v) data on the climate prevailing in the production hall housing the textile machine and / or another textile machine; and / or (vi) at least one machine component of another textile machine which is arranged upstream and / or downstream of the textile machine in the processing chain of the textile product; And then - automatically determining, as a function of at least one received input parameter, at least one adjustment proposal for at least one specific machine component of the textile machine and / or for a production parameter of the textile machine, which is suitable for producing a textile product by means of the textile machine and / or by means of another textile machine, by means of an ascertainment unit, which is coupled to a receiving unit for data transmission, in particular forms a calculation unit with the receiving unit; and subsequently Outputting at least one selectable output parameter by means of an output unit coupled at least to the ascertaining unit for data transmission, said output parameter containing data information about at least one ascertained control proposal.

2. The method according to claim 1, characterized in that The adjustment proposal is read out or regenerated from the data storage unit by the ascertaining unit and is stored in the data storage unit, in particular after generation.

3. The method according to claim 1 or 2, characterized in that: The step of automatically ascertaining is performed with the aid of a database-based approach in which at least one of the input parameters is automatically assigned to at least one of the output parameters.

4. The method according to any one of the preceding claims, characterized in that The step of automatically ascertaining is performed with the aid of 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.

5. The method according to claim 4 in combination with claim 3, characterized in that: The step of automatic ascertainment is preceded by a selection step for selecting a database-based or model-based approach, wherein the selection is performed manually by an operator or automatically based on a predeterminable decision process.

6. The method according to any one of claims 1 to 5, characterized in that The step of automatically ascertaining is performed based on a statistical model and / or a model based on machine learning.

7. The 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 in a readable manner in the or a further data storage unit and subsequently used in an automatic ascertainment step continuously or intermittently to improve an existing forecast model or to generate a new forecast model.

8. The method according to at least one of the preceding claims, characterized in that Information about production targets relevant to textile products is uniformity, weight, maximum productivity, defined fineness, defined twist, threading with as many threads as possible, defined quality targets, specifically defined or maximum density or twisting with as many threads as possible.

9. The method according to at least one of the preceding claims, characterized in that The step of receiving the input parameters is preceded by the step of manually inputting at least one of the input parameters at an input unit coupled to the receiving unit in a data transmission manner.

10. The method according to at least one of the preceding claims, characterized in that The output parameters contain information about components of the textile machine and / or another textile machine, such as particularly specific card clothings, spinning cups, spinning nozzles, drafting device components, ring-tireur system, bobbin gauge, drawing unit, splicing device, bobbin receiver, loom type, reed, knitting machine type, needle type.

11. The method according to at least one of the preceding claims, characterized in that Output parameters for production-parameter-dependent control recommendations are information about the production speed, air pressure, draft, tension and / or rotational speed of the textile machine.

12. The method according to at least one of the preceding claims, characterized in that Prior to the receiving step, the input parameters are read out from the textile machine by means of a readout unit and transmitted to the receiving unit, which is coupled to the readout unit for data transmission.

13. The method according to at least one of the preceding claims, characterized in that The output step is followed by a step of manually inputting 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 device of the textile machine.

14. A data-based assistance system for implementing the method according to at least one of the preceding claims, wherein the assistance system comprises: - a receiving unit for receiving said input parameters; an ascertainment unit for automatically ascertaining, as a function of received input parameters, at least one adjustment proposal for the production of textile products, in particular stored readable in a data storage unit, regarding a specific machine component and / or production parameter; and - an output unit for outputting a selectable output parameter; The data storage unit is coupled to the auxiliary system for data transmission, or is included by the auxiliary system.