Device and method for detecting a fault in a spinning mill and for estimating one or more sources of the fault

A method for detecting a fault in a spinning mill and for estimating possible sources of the fault, the spinning mill including:

• a plurality of textile machines that sequentially process textile materials;
• a plurality of electronic sensors located at different locations along the textile machines, the electronic sensors located and configured to detect parameter information related to:
• (a) operating characteristics of the textile machines and (b) characteristics of the textile materials produced by the textile machines;
• an electronic storage source of configuration information related to the textile machines such that, for any of the textile materials, a sequence and particular ones of the textile machines involved in producing the textile material is identifiable from the configuration information;
• an electronic storage source of knowledge-based information related to faults in the spinning mill, the knowledge-based information including one or more of:
• knowledge based on experience of spinning mill experts, knowledge generated by computer algorithms or artificial intelligence related to the spinning mill, spinning mills of a similar or same configuration, or spinning mills of a different configuration;
• and
• an electronic device in communication with the electronic sensors, the electronic storage source of configuration information, and the electronic storage source of knowledge-based information;
• the electronic device further configured to receive parameter information related to (c) laboratory-analyzed findings for the textile materials;
• the method comprising:
• with the electronic device, receiving and comparing the parameter information related to (a), (b), and (c) to reference values, wherein the fault is defined when the parameter information related to one or more of (a), (b), and (c) exceeds a respective threshold reference value;
• with the electronic device, applying the parameter information related to (a), (b), and (c), the configuration information, and the knowledge-based information to one or more machine-learning algorithms;
• with the electronic device and the one or more machine-learning algorithms, estimating possible sources and a location of the fault;
• and
• with the electronic device, receiving feedback information indicating if maintenance work on the textile machines or the components of the textile machines related to the possible sources of the fault resulted in correction of the fault, and updating the knowledge-based information accordingly.