{"id":265,"date":"2025-01-17T16:44:55","date_gmt":"2025-01-17T08:44:55","guid":{"rendered":"http:\/\/www.1.com\/?p=238"},"modified":"2025-01-19T15:25:04","modified_gmt":"2025-01-19T07:25:04","slug":"about-detail-8","status":"publish","type":"post","link":"https:\/\/www.hexinmusu.com\/en\/about-detail-8.html","title":{"rendered":"Determination of machining allowances for CNC machine tools"},"content":{"rendered":"
1. Refers to the machining thickness reserved for processing the required products, and after removing the reserved thickness can get the size, shape and positional accuracy of the workpiece that meets the requirements.<\/p>\n\n\n\n
2. The size of the machining allowance directly affects the machining efficiency and machining quality, so the reasonable determination of the machining allowance is an important part of the CNC machine tool processing.<\/p>\n\n\n\n
Workpiece materials<\/strong><\/p>\n\n\n\n The hardness, strength, toughness and other physical properties of the workpiece material have a greater impact on the size of the machining allowance.<\/p>\n<\/div>\n\n\n\n Tool performance<\/strong><\/p>\n\n\n\n Properties such as tool sharpness, wear resistance, and rigidity affect the determination of machining allowances.<\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n Machine accuracy<\/strong><\/p>\n\n\n\n The positioning accuracy of the machine tool, the repeatability of the positioning accuracy, and the stability of the transmission system all affect the determination of the machining allowance.<\/p>\n<\/div>\n\n\n\n Processing<\/strong><\/p>\n\n\n\n Different machining processes (e.g. roughing, semi-finishing, finishing) require different machining allowances.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n Determined on the basis of experience<\/strong> Depth of cut<\/strong> Material hardness<\/strong> Tool wear level<\/strong> Optimization goals<\/strong><\/p>\n\n\n\n Minimize machining allowance and improve machining efficiency under the premise of meeting machining accuracy and surface quality.<\/p>\n\n\n\n restrictive condition<\/strong><\/p>\n\n\n\n Cutting forces, cutting heat, tool wear and other factors during machining need to be within tolerable limits, while ensuring the stability and reliability of the machining process.<\/p>\n<\/div>\n<\/div>\n\n\n\n genetic algorithm<\/strong><\/p>\n\n\n\n Global search for optimal solutions by modeling the genetic mechanism in biological evolution. Applicable to multivariate, nonlinear, discrete optimization problems.<\/p>\n<\/div>\n\n\n\n particle swarm algorithm<\/strong><\/p>\n\n\n\n Simulate the foraging behavior of biological groups such as bird flocks and fish schools to find the global optimal solution through information sharing and collaboration among individuals. Applicable to continuous type optimization problems.<\/p>\n<\/div>\n\n\n\n simulated annealing algorithm<\/strong><\/p>\n\n\n\n Drawing on the principle of solid annealing, avoiding falling into local optimal solutions through stochastic search and probabilistic acceptance of inferior solutions. Applicable to multi-constraint, nonlinear optimization problems.<\/p>\n<\/div>\n<\/div>\n\n\n\n Example 1<\/strong> Real-time data collection<\/strong> System Architecture Design<\/strong><\/p>\n\n\n\n According to the demand of CNC machine tool machining allowance control, design a reasonable system architecture, including hardware and software parts.<\/p>\n<\/div>\n\n\n\n Data processing algorithms<\/strong><\/p>\n\n\n\n Research and development of data processing algorithms applicable to real-time monitoring and early warning systems to improve data processing speed and accuracy.<\/p>\n<\/div>\n\n\n\n System Integration and Commissioning<\/strong><\/p>\n\n\n\n Integration of individual modules into the system, debugging and optimization of the<\/p>\n<\/div>\n<\/div>\n\n\n\n intellectualize<\/strong> Technological innovations<\/strong><\/figure>\n\n\n\n
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CNCMethod of determining machining allowances<\/strong>:<\/h2>\n\n\n\n
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Determine the size of the machining allowance based on actual machining experience and in conjunction with similar cases.
experimental method<\/strong>
By means of test cutting, we observe the change of cutting force, cutting temperature and other parameters to determine the reasonable machining allowance.
the analytic method<\/strong>
Through the establishment of mathematical models or simulation models, analyze the influence of workpiece materials, tools, machine tools and other factors on the machining allowance, so as to determine a reasonable machining allowance.<\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\nCalculation of machining allowances for CNC machine tools<\/h2>\n\n\n\n
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Depending on the workpiece material and machining requirements, the depth of cut is determined so that the machining allowance can be calculated.
cutting speed<\/strong>
Different cutting speeds affect the magnitude of the cutting forces, which in turn affects the determination of the machining allowances.
Feed rate<\/strong>
The size of the feed rate affects the roughness of the cutting surface and thus the determination of the machining allowance.<\/p>\n<\/div>\n<\/div>\n\n\n\nMachining allowance calculation based on workpiece material<\/strong><\/h2>\n\n\n\n
Harder materials may require larger machining allowances.
Material toughness<\/strong>
Tougher materials tend to generate heat and cutting forces during machining and therefore require larger machining allowances.
Material heat treatment status<\/strong>
Materials in different states of heat treatment will have different hardnesses and toughnesses, which will affect the determination of machining allowances.<\/p>\n<\/div>\n\n\n\n<\/figure>\n<\/div>\n<\/div>\n\n\n\n
Machining allowance calculation based on tool wear<\/strong><\/h2>\n\n\n\n
A tool with a high degree of wear affects the roughness of the cutting surface and thus the determination of the machining allowance.
Tool life<\/strong>
When tool life is short, larger machining allowances are required to avoid tool breakage.
Tool Type<\/strong>
Different types of tools have different cutting properties, so it is necessary to determine the appropriate machining allowance according to the type of tool.<\/p>\n<\/div>\n<\/div>\n\n\n\nOptimization objectives and constraints<\/strong><\/h2>\n\n\n\n
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Selection and Application of Optimization Algorithms<\/strong><\/h2>\n\n\n\n
Machining allowance optimization case study<\/strong><\/h2>\n\n\n\n
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For the machining allowance optimization of a complex surface part, genetic algorithm is used to optimize the machining parameters, which achieves a significant reduction of machining allowance and improves the machining efficiency.
Example 2<\/strong>
For the machining allowance optimization of an aero-engine blade, the particle swarm algorithm is used to plan the cutting path, which effectively reduces the machining allowance and reduces the tool wear under the premise of ensuring the machining accuracy.
Example 3<\/strong>
For the optimization of machining allowance of a mold cavity, the cutting parameters are optimized by simulated annealing algorithm, which achieves the minimization of machining allowance and improves the machining quality and efficiency.<\/p>\n<\/div>\n<\/div>\n\n\n\nControl of machining allowances on CNC machine tools<\/h2>\n\n\n\n
Through sensors and monitoring equipment, real-time acquisition of CNC machine tool machining data, such as cutting force, cutting temperature, tool wear and so on.
Data analysis and processing<\/strong>
The collected real-time data is processed and analyzed to assess the stability of the machining process and to predict margin variations.
Abnormality Detection and Alarm<\/strong>
Through the real-time monitoring system, abnormalities in the machining process, such as excessive tool wear, abnormal cutting force, etc., are detected in a timely manner and alarms are issued.<\/p>\n<\/div>\n\n\n\n<\/figure>\n<\/div>\n<\/div>\n\n\n\n
CNC machiningEarly warning system in case of insufficient margin<\/strong><\/h2>\n\n\n\n
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Design and realization of margin control system<\/strong><\/h2>\n\n\n\n
Trends in margin determination techniques<\/strong><\/h2>\n\n\n\n
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Utilizing artificial intelligence and machine learning technology to realize automatic identification and prediction of machining allowances to improve machining accuracy and efficiency.
refinement<\/strong>
Realize precise control of machining allowances to meet the demand for high precision machining through high precision measurement and data processing technology.
integration<\/strong>
Integration of margin determination technology with process planning, machining simulation, etc., to achieve comprehensive optimization of the machining process.<\/p>\n<\/div>\n<\/div>\n\n\n\nInnovative directions in margin optimization technology<\/strong><\/h2>\n\n\n\n
Research new machining processes and methods to reduce machining allowance and improve machining efficiency.
Material Innovation<\/strong>
Development of new materials to reduce the influence of materials on machining allowances and improve machining quality.
Algorithmic Innovation<\/strong>
Research new algorithms and technologies to optimize the calculation and control of machining allowances and improve machining accuracy.<\/p>\n<\/div>\n\n\n\n