New generation band saw metal cutting system

Abstract

The invention relates to a next-generation band saw metal cutting system, which involves transferring data obtained by visually inspecting the band saw used in strip sawing metal cutting machines to a database and processing the data here using artificial intelligence and image processing techniques, thereby enabling the pre-determination of any deformations (such as cutting-edge wear, cracking, fracturing, etc.) that may occur on the band saw. These determinations obtained from the visuals, torque and current data from the motor, temperature, vibration, curve cutting sensor data according to the strip rotation speed, cutter head movement control, predictive maintenance planning, and similar controls are automatically monitored, enabling necessary precautions to be taken in advance either automatically or manually.

Description

[0001] NEW GENERATION BAND SAW METAL CUTTING SYSTEM

[0002] TECHNICAL FIELD OF INVENTION

[0003] The invention relates to a next-generation band saw metal cutting system, which involves transferring data obtained by visually inspecting the band saw used in blade sawing metal cutting machines to a database and processing the data here using artificial intelligence and image processing techniques, thereby enabling the pre-determination of any deformations (such as cutting-edge wear, cracking, fracturing, etc.) that may occur on the band saw. These determinations obtained from the visuals, torque and current data from the motor, temperature, vibration, curve cutting sensor data according to the blade rotation speed, cutter head movement control, predictive maintenance planning, and similar controls are automatically monitored, enabling necessary precautions to be taken in advance either automatically or manually.

[0004] PRIOR ART

[0005] The band saw metal cutting machine is a cutting tool specially designed to cut metal materials in desired dimensions and quantities using a band saw. The band saw consists of a toothed blade wound around two rotating pulleys. The machine performs the cutting operation by rotating the band saw through a motor and moving it over the work piece. The fundamental components of the band saw metal cutting machine can be defined as the band saw, motors, support frame, cutting head, work piece feeding system, electrical, hydraulic, and cooling system.

[0006] In conventional band saw metal cutting operations, operating parameters such as cutting speed, feed rate, cooling, etc., which significantly affect product efficiency, energy efficiency, and cutting quality, are determined by the operator based on factors such as the type of material, size of the cutting area, and the condition of the band saw (type, model, tooth count, wear, etc.). Determining the most suitable parameters for the cutting process requires careful evaluation of factors such as the correct cutting speed and feed rate. These parameters vary depending on factors such as the type and dimensions of the material, the geometry of the part to be cut, the targeted geometric accuracy, and surface quality objectives. The diversity of materials to be cut and the variety of band saw blade types, along with wear of the band saw due to usage, lead to the differentiation of appropriate cutting parameters for each cutting operation. At this point, the competence of operators emerges as a challenge.

[0007] Conventional band saw metal cutting machines commonly operate in a mass production and 24 / 7 systematic manner in industry. Therefore, it is crucial for businesses to have traceable cutting processes and accessible historical data. Conventional band saw machines provide users and businesses with very limited and instantaneous data regarding cutting processes. This situation results in the inability to evaluate the machine in terms of traceability and predictability. In conventional band saw metal cutting machines, efficiency and product quality are entirely determined by the competence of operators.

[0008] In today's industrial sector, the inability to produce products within a specific efficiency and quality standard is a significant problem. Predictive maintenance is a commonly used technique in the industry to reduce machine downtime, lower operating costs, and ensure planning and resource management. The most crucial step in implementing this technique is collecting and analyzing data related to the machine's operating processes. Conventional band saw metal cutting machines pose a problem in predictive maintenance planning as they provide users and businesses with limited data in this regard.

[0009] In the existing technology, various imaging and image evaluation systems can be used for the visual inspection of band saw blades. In document CN109269425, for test purposes, visual changes such as breakage, cracking, and wear at the tip of a band saw blade are detected through a camera. However, the developed system aims to increase the sensitivity of quality control by determining the location of deformations occurring on the band saw blade. No solution is provided for the band saw metal cutting system. BRIEF DESCRIPTION OF THE INVENTION

[0010] A new generation of band saw metal cutting system has been developed, which involves transferring data obtained from the visual inspection of the band saw used in band saw metal cutting machines to a database and processing the data using artificial intelligence and image processing techniques. This enables the advance detection of any deformations (such as cutting-edge wear, cracking, fracturing, etc.) that may occur on the band saw blade. The determinations obtained from these visuals, torque and current data from the motor, temperature, vibration, curve cutting sensor data, etc., are used to automatically monitor parameters such as band rotation speed, cutter head movement control, predictive maintenance planning, and similar controls. This allows necessary precautions to be taken in advance, either automatically or manually.

[0011] The developed band saw metal cutting system integrates camera equipment onto the band saw machine, allowing for continuous visual inspection of the band saw blade during the cutting process. This enables monitoring of potential deformations such as wear, cracking, and fracturing at the cutting edge of the band saw blade.

[0012] In the developed band saw metal cutting system, the visual inspection of the band saw blade is achieved by using preferably an RGB camera, thermal camera, and laser profile sensor, either individually or in combination, which are mounted on the band saw metal cutting machine.

[0013] In the developed band saw metal cutting system, images of the band saw blade recorded through the cameras mounted on the machine are processed using image processing / deep learning approaches supported by artificial intelligence. As a result, fault conditions such as wear, cracks, and breaks that may occur on the band saw blade can be easily detected during the operation of the machine. The collected data is utilized to monitor cutting performance, identify abnormalities, and optimize cutting parameters. This enables automatic monitoring of parameters such as band saw blade rotation speed, cutter head movement control, predictive maintenance planning, and similar controls, ensuring that necessary precautions are taken in advance, either automatically or manually. DETAILED DESCRIPTION OF THE INVENTION

[0014] The subject of the invention is a band saw metal cutting system; comprising at least one image recording equipment integrated on the band saw metal cutting machine to continuously display the cutting edge of the band saw blade during operation, control of the rotation speed of the band saw blade, control of the vertical movement of the cutting head in the cutting direction, and transfer of the images obtained as a result of this display to an artificial intelligence-supported database for predictive maintenance checks of the band saw metal cutting machine, and processing the images here in terms of detecting wear, cracks, and fractures that may occur on the band saw blade, for use on the band saw metal cutting machine.

[0015] The subject of the invention is a band saw metal cutting system, comprising at least one image recording equipment preferably selected as an RGB camera, thermal camera, or laser profile sensor, integrated on the band saw blade metal cutting machine to ensure recording of the cutting edge portion images of the band saw blade for artificial intelligence-supported processing using image processing / deep learning approaches, enabling easy detection of fault conditions such as wear, cracks, and fractures that may occur on the band saw blade during machine operation.

[0016] Through the developed image recording device in the band saw metal cutting system, any wear, crack, or fracture detected in the cutting edge portion of the band saw blade is processed via artificial intelligence supported by the computerized control system connected to the machine. The rotational speed of the band saw blade can be automatically controlled depending on the deformation condition of the band saw blade. Thus, the cutting process can be continued at the desired speed or stopped depending on the physical condition of the band saw blade, preventing potential machine malfunctions or faulty cutting issues.

[0017] Through the developed image recording device in the subject invention of the band saw metal cutting system, any wear, crack, or fracture detected on the cutting edge of the band saw blade is processed via artificial intelligence- supported computerized control system connected to the machine, and the vertical movement of the cutting head in the cutting direction is automatically controlled depending on the deformation condition of the band saw blade. Thus, by determining the movement and working angle of the cutting head on the material to be cut according to the physical condition of the band saw blade, potential machine malfunctions or errors in cutting can be prevented effectively.

[0018] Through the developed image recording device in the band saw metal cutting system, any wear, crack, or fracture detected in the cutting-edge portion of the band saw blade is processed via artificial intelligence supported by the computerized control system connected to the machine. Predictive maintenance checks are automatically performed to detect signs of malfunction associated with the band saw blade, enabling the planning of maintenance processes accordingly. Thus, preventive maintenance measures can be taken before any negative occurrences arise, prolonging the machine's lifespan and keeping maintenance costs at low levels.

Claims

CLAIMS1. The next-generation band saw metal cutting system, characterized by the integration of at least one image recording equipment on the band saw metal cutting machine, enables visual inspection of the band saw blade used in band saw metal cutting machines, transferring the obtained data to a database, and processing the data using artificial intelligence and image processing techniques; which enables the early detection of any deformations (such as cutting-edge wear, cracking, breaking, etc.) that may occur on the band saw blade and further allows for automatic or manual implementation of necessary measures based on the determinations obtained from these images, torque and current data from the motor, as well as temperature, vibration, and curve cutting sensor data, thereby automatically monitoring parameters such as band rotation speed, control of the vertical movement of the cutting head, predictive maintenance planning, and similar controls; and also includes controlling the rotational speed of the band saw blade, controlling the vertical movement of the cutting head in the cutting direction, and continuously displaying the cutting edge portion of the band saw blade during operation of the band saw metal cutting machine for predictive maintenance checks, transferring the obtained images to an artificial intelligence-supported database, and processing the images for detection of wear, cracks, and fractures that may occur on the band saw blade.

2. According the Claim 1 , the next-generation band saw metal cutting system is characterized by the integration of at least one image recording equipment, preferably selected as an RGB camera, thermal camera, or laser profile sensor, on the band saw metal cutting machine ensuring the recording of images of the cutting-edge portion of the band saw blade, which will be processed via artificial intelligence using image processing / deep learning approaches; which enables easy detection of fault conditions such as wear, cracks, and fractures that may occur on the band saw blade during the operation of the machine.