Machine learning device including a state variable acquisition unit, a teaching data acquisition unit and a learned model generation unit that generates a first learned model by performing machine learning based on a first state variable dataset and first teaching data and generates a second learned model by performing machine learning based on a second state variable dataset and second teaching data
A machine learning device according to an embodiment may include: a state variable acquisition unit that acquires first and second state variable datasets including print results performed at first and second printing speeds respectively by an image formation apparatus; a teaching data acquisition unit that acquires first and second teaching data corresponding to the first and second printing speeds; and a learned model generation unit that generates a first learned model by performing machine learning based on the first state variable dataset and the first teaching data, and generates a second learned model by performing machine learning based on the second state variable dataset and the second teaching data. Each of the first and second state variable datasets includes: feature value information; medium information; and first control information. Each of the first and second teaching data includes: second control information; and a print defect value.
1. A machine learning device comprising a processor configured with a program to perform operations comprising:
operation as a state variable acquisition unit that acquires a first state variable dataset including a print result at a first printing speed by an image formation apparatus, and a second state variable dataset including a print result at a second printing speed by the image formation apparatus, wherein the image formation apparatus is capable of printing at a plurality of printing speeds including the first printing speed and the second printing speed;
operation as a teaching data acquisition unit that acquires first teaching data corresponding to the first printing speed and second teaching data corresponding to the second printing speed; and
operation as a learned model generation unit that generates a first learned model by performing machine learning based on the first state variable dataset and the first teaching data, and generates a second learned model by performing machine learning based on the second state variable, dataset and the second teaching data, wherein
each of the first state variable dataset and the second state variable dataset includes: feature value information in an actual printout in which printing is actually made; medium information, which is information of a print medium used to output the actual printout; and first control information, which is control information of the image formation apparatus when the image formation apparatus outputs the actual printout, and
each of the first teaching data and the second teaching data includes: second control information, which is control information such that the feature value information become less than or equal to a predetermined threshold when the printing is made at a corresponding one of the first and second printing speeds; and a print defect value in a case of printing at the corresponding one of the first and second printing speed using the second control information.
2. The machine learning device according to claim 1 , wherein
the feature value information includes information about a print defect in the actual printout.
3. The machine learning device according to claim 1 , wherein
the medium information includes information on a presence or absence of coating, a material, a thickness, a weight, and a density of the print medium.
4. The machine learning device according to claim 1 , wherein
the image formation apparatus is an electrophotographic image formation apparatus, and the first control information includes information about a toner fixing temperature and a transfer voltage in the image formation apparatus.
5. The machine learning device according to claim 1 , wherein,
the image formation apparatus is an electrophotographic image formation apparatus, and the second control information includes information about a toner fixing temperature and a transfer voltage in the image formation apparatus.
6. The machine learning device according to claim 1 , wherein
the image formation apparatus is an electrophotographic image formation apparatus, and each of the first control information and the second control information includes information about a toner fixing temperature and a transfer voltage in the image formation apparatus.
7. The machine learning device according to claim 1 , wherein,
each of the first state variable dataset and the second state variable dataset further includes environmental information around the image formation apparatus.
8. The machine learning device according to claim 7 , wherein,
the environmental information includes information about a temperature and a humidity around the image formation apparatus.