Intelligent control of metal cutting chip breakers
A chip breaking apparatus is provided. The chip breaking apparatus includes a robotic arm including a gripper, a cutter, an inspection element to produce an output indicative of machining tool operations and a processor receptive of the output from the inspection element. The processor is configured to analyze the output, determine from analysis results whether a chip is being generated from a surface by the machining tool operations and whether to cut the chip away from the surface and control the robotic arm and the gripper to grip the chip and control the cutter to cut the chip away from the surface based on an affirmative determination.
1 . A chip breaking apparatus, comprising:
a robotic arm comprising a gripper;
a cutter;
an inspection element to produce an output indicative of machining tool operations; and
a processor receptive of the output from the inspection element and providing a convolutional neural network (CNN) that is configured to:
analyze the output,
determine from analysis results whether a chip is being generated from a surface by the machining tool operations and whether to cut the chip away from the surface, and
control the robotic arm and the gripper to grip the chip and control the cutter to cut the chip away from the surface based on an affirmative determination.
2 . The chip breaking apparatus according to claim 1 , wherein the chip breaking apparatus is provided for use with a machining tool that comprises a cutting edge for machining the surface.
3 . The chip breaking apparatus according to claim 1 , wherein the robotic arm comprises a first end anchored to the machining tool and a second end, which is opposite the first end, to which the gripper is connected.
4 . The chip breaking apparatus according to claim 1 , wherein the robotic arm has at least two degrees of freedom of movement.
5 . The chip breaking apparatus according to claim 1 , wherein:
the chip breaking apparatus further comprises a collection bin, and
the processor is further configured to control the robotic arm and the gripper to transfer a chip having been cut away from the surface to the collection bin.
6 . The chip breaking apparatus according to claim 1 , further comprising:
a collection bin; and
an urging system to urge a chip having been cut away from the surface toward the collection bin.
7 . The chip breaking apparatus according to claim 1 , wherein the cutter comprises a laser beam.
8 . The chip breaking apparatus according to claim 1 , wherein the inspection element comprises a visual inspection element disposable with a line-of-sight to the machining tool.
9 . The chip breaking apparatus according to claim 1 , wherein the processor comprising one or more machine learning models for improving one or more capabilities of the processor to:
analyze the output,
determine from the analysis results whether the chip is being generated from the surface by the machining tool operations and whether to cut the chip away from the surface, and
control the robotic arm and the gripper to grip the chip and control the cutter to cut the chip away from the surface based on an affirmative determination.
10 . A chip handling assembly, comprising:
a machining tool comprising a cutting edge for machining a surface; and
a chip breaking apparatus comprising:
a robotic arm comprising a gripper;
a cutter;
an inspection element to produce an output indicative of machining tool operations; and
a processor receptive of the output from the inspection element and providing a convolutional neural network (CNN) that is configured to:
analyze the output,
determine from analysis results whether a chip is being generated from the surface by the machining tool operations and whether to cut the chip away from the surface, and
control the robotic arm and the gripper to grip the chip and control the cutter to cut the chip away from the surface based on an affirmative determination.
11 . The chip handling assembly according to claim 10 , wherein the robotic arm comprises a first end anchored to the machining tool and a second end, which is opposite the first end, to which the gripper is connected.
12 . The chip handling assembly according to claim 10 , wherein the robotic arm has at least two degrees of freedom of movement.
13 . The chip handling assembly according to claim 10 , wherein:
the chip breaking apparatus further comprises a collection bin, and
the processor is further configured to control the robotic arm and the gripper to transfer a chip having been cut away from the surface to the collection bin.
14 . The chip handling assembly according to claim 10 , wherein the chip breaking apparatus further comprises:
a collection bin; and
an urging system to urge a chip having been cut away from the surface toward the collection bin.
15 . The chip handling assembly according to claim 10 , wherein the cutter comprises a laser beam.
16 . The chip handling assembly according to claim 10 , wherein the inspection element comprises a visual inspection element disposable with a line-of-sight to the machining tool.
17 . The chip handling assembly according to claim 10 , wherein the processor comprising one or more machine learning models for improving one or more capabilities of the processor to:
analyze the output,
determine from the analysis results whether the chip is being generated from the surface by the machining tool operations and whether to cut the chip away from the surface, and
control the robotic arm and the gripper to grip the chip and control the cutter to cut the chip away from the surface based on an affirmative determination.
18 . A method of operating a chip handling assembly, the method comprising:
anchoring a robotic arm comprising a gripper to a machining tool comprising a cutting edge for machining a surface;
positioning a cutter and an inspection element proximate to the machining tool;
producing an output indicative of machining tool operations by the inspection element;
analyzing the output; and
providing a convolutional neural network (CNN) for:
determining from results of the analyzing whether a chip is being generated from the surface by the machining tool operations and whether to cut the chip away from the surface, and
controlling the robotic arm and the gripper to grip the chip and the cutter to cut the chip away from the surface based on the determining being affirmative.
19 . The method according to claim 18 , further comprising collecting the chip in a collection bin.
20 . The method according to claim 18 , wherein the determining and the controlling comprise training one or more machine learning models to improve the determining and the controlling.