Abstract: A learned model generation method involves: outputting, when it is determined that the sequence of the positions of a first end surface of a first sheet material indicated by first data intersects with the sequence of the positions of a second end surface of a second sheet material indicated by second data, information indicating that a roll is defective and that the defect is caused by a first feed reel or a first affixing roller; and generating a facility state diagnosis model by using the first data and the second data read before preservation of the first feed reel when it is determined that a first difference between a first defect rate of the roll before the preservation of the first feed reel and a second defect rate of the roll after the preservation of the first feed reel is equal to or larger than a prescribed value.

Abstract: First data indicating a position of a first end surface of a first sheet material and second data indicating a position of a second end surface of a second sheet material are acquired from an inspection machine, and information indicating that a winding body has a defect and a cause of the defect is any of a plurality of winding cores is output to a display for maintenance in a case where continuous positions of the first end surface indicated by the first data and continuous positions of the second end surface indicated by the second data are tilted with respect to reference lines.

Abstract: A notification determinator determines whether or not an inspection result of a winding body indicates defective on the basis of whether or not continuous positions of a first end surface and a second end surface indicated by first group data and second group data are separated from reference positions by a predetermined distance or more. In a case where the inspection result of the winding body indicates defective, a notification determinator performs a notification that inspection in an inspection machine is not performed normally, and outputs information indicating that a cause of the defect is a take-out chuck of an inspection machine or any of a plurality of winding cores to a display for maintenance.

Abstract: A shape data group that is shape data of each of a predetermined number or more of winding bodies correlated with time information is acquired, a first defect ratio before maintenance is calculated on the basis of each shape data group of the predetermined number of winding bodies read before the maintenance, a second defect ratio after the maintenance is calculated on the basis of each shape data group of the predetermined number of winding bodies read after the maintenance, and a facility state diagnosis model is generated by using each shape data group of the predetermined number of winding bodies read before the maintenance in a case where a difference between the first defect ratio and the second defect ratio is greater than or equal to a predetermined value.

Abstract: A learned model generation method involves: outputting, when it is determined that the sequence of the positions of a first end surface of a first sheet material indicated by first data intersects with the sequence of the positions of a second end surface of a second sheet material indicated by second data, information indicating that a roll is defective and that the defect is caused by a first feed reel or a first affixing roller; and generating a facility state diagnosis model by using the first data and the second data read before preservation of the first feed reel when it is determined that a first difference between a first defect rate of the roll before the preservation of the first feed reel and a second defect rate of the roll after the preservation of the first feed reel is equal to or larger than a prescribed value.

Abstract: First group data indicating a position of a first end surface of a first sheet material and second group data indicating a position of a second end surface of a second sheet material are acquired from an inspection machine, and information indicating whether or not a winding body has a defect, and which constituent of a sheet material supplier is a cause of the defect in a case where the winding body has the defect, on the basis of a positional relationship among continuous positions of the first end surface indicated by the first group data, continuous positions of the second end surface indicated by the second group data, and reference lines, is output to a display for maintenance.

Abstract: A facility state diagnosis model generator generates a shape data group in which any of a plurality of winding cores is correlated with any of a plurality of pieces of group data, and generates a replacement data group in which correspondence relationships between the winding cores and the group data are replaced with each other in all combinations of the plurality of winding cores and the plurality of pieces of group data, and generates or updates a plurality of learned models indicating that a cause of a defect is any of the plurality of winding cores by using the replacement data group.

Abstract: A notification determinator determines whether or not an inspection result of a winding body indicates defective on the basis of whether or not continuous positions of a first end surface and a second end surface indicated by first group data and second group data are separated from reference positions by a predetermined distance or more. In a case where the inspection result of the winding body indicates defective, a notification determinator performs a notification that inspection in an inspection machine is not performed normally, and outputs information indicating that a cause of the defect is a take-out chuck of an inspection machine or any of a plurality of winding cores to a display for maintenance.

Abstract: A shape data group that is shape data of each of a predetermined number or more of winding bodies correlated with time information is acquired, a first defect ratio before maintenance is calculated on the basis of each shape data group of the predetermined number of winding bodies read before the maintenance, a second defect ratio after the maintenance is calculated on the basis of each shape data group of the predetermined number of winding bodies read after the maintenance, and a facility state diagnosis model is generated by using each shape data group of the predetermined number of winding bodies read before the maintenance in a case where a difference between the first defect ratio and the second defect ratio is greater than or equal to a predetermined value.

Abstract: First data indicating a position of a first end surface of a first sheet material and second data indicating a position of a second end surface of a second sheet material are acquired from an inspection machine, and information indicating that a winding body has a defect and a cause of the defect is any of a plurality of winding cores is output to a display for maintenance in a case where continuous positions of the first end surface indicated by the first data and continuous positions of the second end surface indicated by the second data are tilted with respect to reference lines.