Intelligent machining system

An intelligent machining system for automatically determining machining conditions and for controlling a numerically controlled machine tool to machine a workpiece in accordance with the machining conditions, said intelligent machining system comprising:

• attribute data storage means for storing attribute data indicating characteristics of at least one of said workpiece and machining requirements;
• a first neural network for determining, on the basis of the attribute data, elementary values used in determining the machining conditions;
• and
• machining condition calculating means for calculating the machining conditions on the basis of the attribute data stored in the attribute data storage means and the elementary values determined by the first neural network and for outputting said machining conditions to said machine tool to machine said workpiece;
• wherein the machining condition calculating means has predetermined calculating expressions which are used in calculating the machining conditions,
• the elementary values determined by said first neural network are coefficients for the predetermined calculating expressions used in calculating the machining conditions on the basis of the attribute data, and
• said machining condition calculating means calculates the machining conditions on the basis of the attribute data by using the predetermined calculating expressions and the coefficients determined by the first neural network.

An intelligent machining system for automatically determining machining conditions and for controlling a numerically controlled machine tool to machine a workpiece in accordance with the machining conditions, said intelligent machining system comprising:

• attribute data storage means for storing attribute data indicating characteristics of at least one of said workpiece and machining requirements;
• and
• machining condition calculating means for calculating the machine conditions on the basis of the attribute data, said machining condition calculating means comprising:
• reference value calculating means for calculating reference machining conditions on the basis of the attribute data by the use of predetermined calculating expressions;
• and
• a first neural network responsive to the attribute data and associated with said reference value calculating means so that the reference machining conditions calculated by the reference value calculating means are corrected by said first neural network so as to output the corrected machining conditions from said machining condition calculating means to said machine tool to machine said workpiece;
• wherein said intelligent machining system further comprises:
• machining condition storage means for storing the machining conditions determined by said machining condition calculating means;
• error data storage means for storing machining errors relative to values representing desired machining results;
• a second neural network which receives the machining errors stored in the error data storage means and provides corrections for the machining conditions;
• control means for controlling said second neural network so as to receive the machining errors and to provide the corrections;
• and
• correction storage means for storing the corrections provided by said second neural network, for use in subsequently correcting the machining conditions stored in said machining condition storage means.

An intelligent machining system for automatically determining machining conditions and for controlling a numerically controlled machine tool to machine a workpiece in accordance with the machining conditions, said intelligent machining system comprising:

• attribute data storage means for storing attribute data indicating characteristics of at least one of said workpiece and machining requirements;
• reference value calculating means operable in accordance with predetermined calculating expressions for calculating reference machining conditions on the basis of the attribute data stored in said attribute data storage means;
• a first neural network responsive to the attribute data for correcting the reference machining conditions calculated by said reference value calculating means so as to provide the machining conditions and for outputting said machining conditions to said machine tool to machine said workpiece;
• machining condition storage means for storing the machining conditions corrected by said first neural network;
• error data storage means for storing machining errors relative to desired machining results;
• a second neural network which receives the machining errors stored in the error data storage means and provides corrections for further correcting the machining conditions stored in the machining condition storage means;
• control means for controlling the second neural network so as to receive the machining errors and to provide the corrections;
• and
• correction storage means for storing the corrections provided by the second neural network, for use in subsequently further correcting the machining conditions stored in said machining condition storage means.

An intelligent machining system for automatically determining machining conditions and for controlling a numerically controlled machine tool to machine a workpiece in accordance with the machining conditions, said intelligent machining system comprising:

• attribute data storage means for storing attribute data indicating characteristics of at least one of said workpiece and machining requirements;
• and
• machining condition calculating means for calculating the machining conditions on the basis of the attribute data, said machining condition calculating means comprising:
• reference value calculating means for calculating reference machining conditions on the basis of the attribute data by the use of predetermined calculating expressions;
• and
• a first neural network responsive to the attribute data and associated with said reference value calculating means so that the reference machining conditions calculated by the reference value calculating means are corrected by said first neural network so as to output the corrected machining conditions from said machining condition calculating means to said machine tool to machine said workpiece;
• wherein said intelligent machining system further comprises:
• sensor means for detecting at least one of instantaneous machining phenomena such as sparks, sound and force produced in machining a workpiece by the numerically controlled machine tool;
• a second neural network which receives time-series data in a predetermined time interval provided by the sensor means and provides machining circumstance data in the corresponding time interval;
• and
• feed control means for controlling the feed of a tool of the numerically controlled machine tool according to the machining circumstance data provided by said second neural network.

An intelligent machining system for automatically determining machining conditions and for controlling a numerically controlled machine tool to machine a workpiece in accordance with the machining conditions, said intelligent machining system comprising:

• attribute data storage means for storing attribute data indicating characteristics of at least one of said workpiece and machining requirements;
• and
• machining condition calculating means for calculating the machining conditions on the basis of the attribute data, said machining condition calculating means comprising:
• reference value calculating means for calculating reference machining conditions on the basis of the attribute data;
• and
• a first neural network responsive to the attribute data and associated with said reference value calculating means so that the reference machining conditions calculated by the reference value calculating means are corrected by said first neural network so as to output the corrected machining conditions from said machining condition calculating means to said machine tool to machine said workpiece;
• wherein said intelligent machining system further comprises:
• sensor means for detecting at least one of instantaneous machining phenomena such as sparks, sound and force produced in machining a workpiece by the numerically controlled machine tool;
• a second neural network which receives time-series data in a predetermined time interval provided by the sensor means and provides machining circumstance data in the corresponding time interval;
• and
• feed control means for controlling the feed of a tool of the numerically controlled machine tool according to the machining circumstance data provided by said second neural network;
• wherein said feed control means has fuzzy inference means for calculating the respective adaptations of fuzzy rules by using values representing the grades of machining circumstances so as to infer a manipulated variable for controlling the controlled variable of the feed, whereby said feed control means controls the feed of the tool also in accordance with the manipulated variable.

An intelligent machining system for automatically determining machining conditions and for controlling a numerically controlled machine tool to machine a workpiece in accordance with the machining conditions, said intelligent machining system comprising:

• attribute data storage means for storing attribute data indicating characteristics of at least one of said workpiece and machining requirements;
• and
• machining condition calculating means for calculating the machining conditions on the basis of the attribute data, said machining condition calculating means comprising:
• reference value calculating means for calculating reference machining conditions on the basis of the attribute data;
• and
• a first neural network responsive to the attribute data and associated with said reference value calculating means so that the reference machining conditions calculated by the reference value calculating means are corrected by said first neural network so as to output the corrected machining conditions from said machining condition calculating means to said machine tool to machine said workpiece;
• wherein said intelligent machining system further comprises:
• sensor means for detecting at least one of instantaneous machining phenomena such as sparks, sound and force produced in machining a workpiece by the numerically controlled machine tool;
• a second neural network which receives time-series data in a predetermined time interval provided by the sensor means and provides machining circumstance data in the corresponding time interval;
• and
• feed control means for controlling the feed of a tool of the numerically controlled machine tool according to the machining circumstance data provided by said second neural network;
• and
• wherein said feed control means has fuzzy inference means for calculating the adaptations of fuzzy rules by using values representing the grades of machining circumstances, so as to infer a manipulated variable for controlling the controlled variable of the feed, whereby said feed control means controls the feed of the tool also in accordance with the manipulated variable.

An intelligent machining system for automatically determining machining conditions and for controlling a numerically controlled machine tool to machine a workpiece in accordance with the machining conditions, said intelligent machining system comprising:

• attribute data storage means for storing attribute data;
• automatic machining condition determining means including a first neural network and capable of automatically determining machining conditions on the basis of the attribute data stored in the attribute data storage means;
• correcting means for correcting the machining conditions determined by the automatic machining condition determining means, according to instructions given thereto by an operator to provide corrected machining conditions;
• machining control means for controlling the machining operation of the numerically controlled machine tool according to the machining conditions or the corrected machining conditions;
• diagnostic means including a second neural network, which receives machining errors corresponding to deviations of machined results from desired machined results and provides corrections for correcting the machining conditions, and capable of correcting the machining conditions by using the corrections to determine corrected machining conditions;
• learning means for performing the learning of the first neural network for determining machining conditions according to the corrected machining conditions determined by at least one of the correcting means and the diagnostic means so that the corrected machining conditions are provided for the same input attribute data as that initially applied to the automatic machining condition determining means;
• sensor means for detecting at least one of instantaneous machining phenomena such as sparks, sound and force produced in machining the workpiece;
• and
• adaptive control means for dynamically correcting the machining conditions by receiving time-series data provided by said sensor means by a third neural network, and by recognizing average machining circumstances in a time interval on the basis of the output of the third neural network.