Research on the Programming Method Based Process Planning and Kinematics for Mill-Turn Machine

2012 ◽  
Vol 472-475 ◽  
pp. 2100-2106 ◽  
Author(s):  
Zhuang Yao ◽  
Dong Yu ◽  
Jun Feng Tian ◽  
Liao Mo Zheng ◽  
Yi Hu
Keyword(s):  
Process Planning ◽  
Manufacturing Industry ◽  
Tool Path ◽  
Kinematic Chain ◽  
Milling Process ◽  
Programming Method ◽  
Machining Process ◽  
Cylindrical Blank ◽  
Nc Data ◽  
Mill Machining

With manufacturing industry tending to high-mix low-volume production, the turn-mill machining technology has recently received much attention. This research proposes the programming method using process planning and kinematic based on the existing problems during the course of the programming for the mill-turn machine. Firstly, through computing the volume of removal shape on the cylindrical blank shape, dividing the machining process for the spindles. Then recognizing the turning and milling process and computing their removal shape for obtaining tool path. According to complex configuration of the mill-turn machine, the machine kinematic chain is created to convert cutter location data generated into the NC data. Finally the effectiveness of the programming method is confirmed by machining experiment.

An accurate instantaneous uncut chip thickness model combining runout effect in micro-milling using cutters with the non-uniform helix and pitch angles

2019 ◽  
Vol 234 (5) ◽  
pp. 859-870 ◽  
Author(s):  
Qiang Guo ◽  
Yan Jiang ◽  
Zhibo Yang ◽  
Fei Yan
Keyword(s):  
Tool Path ◽  
Chip Thickness ◽  
Milling Process ◽  
Machining Process ◽  
Micro Milling ◽  
Cutter Runout ◽  
Model Combining ◽  
Key Factor ◽  
Cutting Point ◽  
Instantaneous Uncut Chip Thickness

As a key factor, the accuracy of the instantaneous undeformed thickness model determines the force-predicting precision and further affects workpiece machining precision in the micro-milling process. The runout with five parameters affects the machining process more significantly compared with macro-milling. Furthermore, modern industry uses cutters with non-uniform pitch and helix angles more and more common for their excellent properties. In this article, an instantaneous undeformed thickness model is presented regarding cutter runout, variable pitch, and helix angles in the micro-milling process. The cutter edge with the cutter runout effect is modeled. Then, the intersecting ellipse between the plane vertical to the spindle axis and the cutter surface which is a cylinder can be gained. Based on this, the points, which are used to remove the material, on the ellipse as well as cutter edges are calculated. The true trochoid trajectory for each cutting point along the tool path is built. Finally, the instantaneous undeformed thickness values are computed using a numerical algorithm. In addition, this article analyzes runout parameters’ effects on the instantaneous undeformed thickness values. After that, helix and pitch angles’ effects on the instantaneous undeformed thickness are studied. Ultimately, the last section verifies the correctness and validity of the instantaneous undeformed thickness model based on the experiment conducted in the literature.

The Effect of Machining Toolpath on Surface Roughness and Dimensional Accuracy for High-Speed Micro Milling

2017 ◽  
Vol 261 ◽  
pp. 69-76
Author(s):  
Amin Dadgari ◽  
De Hong Huo ◽  
David Swailes
Keyword(s):  
Surface Roughness ◽  
Process Planning ◽  
Tool Path ◽  
Dimensional Accuracy ◽  
Machining Process ◽  
Micro Milling ◽  
Geometric Features ◽  
Machining Parameters ◽  
Machining Performance ◽  
Planning Stage

This paper investigates different machining toolpath strategies on machining efficiency and accuracy in the micro milling of linear and circular micro geometric features. Although micro milling includes many characteristics of the conventional machining process, detrimental size effect in downscaling of the process can lead to excessive tool wear and machining instability, which would, in turn, affects the geometrical accuracy and surface roughness. Most of the research in micro milling reported in literature focused on optimising specific machining parameters, such as feed rate and depth of cut, to achieve lower cutting force, better surface roughness, and higher material removal rate. However, there was little attention given to the suitability and effect of machining tool path strategies. In this research, a tool path optimisation method with respect to surface roughness and dimensional accuracy is proposed and tested experimentally. Various toolpath strategies, including lace(0°), lace(45°), lace(90°), concentric and waveform in producing linear and circular micro geometric features were compared and analysed. Experimental results show that the most common used strategies lace(0°) and concentric reported in the literature have provided the least satisfactory machining performance, while waveform toolpath provides the best balance of machining performance for both linear and circular geometries. Hence, at process planning stage it is critical to assign a suitable machining toolpath strategy to geometries accordingly. The paper concludes that an optimal choice of machining strategies in process planning is as important as balancing machining parameters to achieve desired machining performance.

Modular CNC Design for Intelligent Machining, Part 2: Modular Integration of Sensor Based Milling Process Monitoring and Control Tasks

1996 ◽  
Vol 118 (4) ◽  
pp. 514-521 ◽  
Author(s):  
Y. Altintas¸ ◽  
W. K. Munasinghe
Keyword(s):  
Process Control ◽  
Real Time ◽  
Process Monitoring ◽  
Tool Path ◽  
Position Control ◽  
Milling Process ◽  
Machining Process ◽  
Monitoring And Control ◽  
Process Monitoring And Control ◽  
And Control

Modular integration of sensor based milling process monitoring and control functions to a proposed CNC system architecture is presented. Each sensor based process control algorithm resides in a dedicated processor in the AT bus with a modular software. The CNC system’s motion control module has been designed to accomodate rapid manipulation of feeds, cutting conditions and NC tool path which may be demanded by machining process control modules in real time. Modular integration of adaptive control of cutting forces, tool condition monitoring, chatter detection and suppression tasks are illustrated as examples. The process control and monitoring modules are serviced in the real-time multi-tasking environment within one millisecond time intervals without disturbing the position control system. The paper present constraints and guidelines in designing CNC systems which allow modular integration of user developed real time machining process control and monitoring applications.

Machining Process Evaluation Indices for Developing a Computer Aided Process Planning System

2017 ◽  
Vol 11 (2) ◽  
pp. 242-250 ◽  
Author(s):  
Kenta Koremura ◽  
◽  
Yuki Inoue ◽  
Keiichi Nakamoto
Keyword(s):  
Process Evaluation ◽  
Process Planning ◽  
Manufacturing Industry ◽  
High Efficiency ◽  
Machining Process ◽  
Planning System ◽  
Machining Features ◽  
Computer Aided Process Planning ◽  
Study Results ◽  
Computer Aided

In the manufacturing industry, there is an urgent need to shorten the manufacturing lead time of products. Therefore, optimizing process planning is essential to realize high efficiency machining. In this study, in order to develop a computer aided process planning (CAPP) system using previously proposed machining features, a prediction method for some process evaluation indices is proposed. Many candidates for the machining process exist, depending on the recognized machining features in a previous study. Therefore, by using these indices, operators can select a suitable process from among these candidates according to their ideas. Case studies of process planning are conducted to confirm that the operator’s strategy affects the selection of the machining process candidates. From the case study results, it is found that the proposed process evaluation indices have potential use in determining the machining process utilized, and are suitable for a flexible CAPP system of multi-tasking machine tools.

The Generation of Machining Process Plans Using a Haptic Virtual Reality System

2012 ◽  
Author(s):  
C. A. Fletcher ◽  
J. M. Ritchie ◽  
T. Lim
Keyword(s):  
Process Planning ◽  
Mental Workload ◽  
Limited Range ◽  
Research Area ◽  
Milling Process ◽  
Machining Process ◽  
Shop Floor ◽  
Computer Aided Process Planning ◽  
Process Plans ◽  
Wide Range

Computer Aided Process Planning (CAPP) links the design and manufacture of a machined product defining how the product itself will be manufactured. Decisions made during this phase can have a significant impact on product cost, quality and build time; therefore, it is important that process planners have intuitive tools to aid them in effectively creating process plans. However, in spite of being a strong research area, the actual application of CAPP systems in industry is limited and new modern 3D digital tools in this area have not been researched to any real degree. Traditional process planning is carried out either manually or via a CAPP interface and, from this activity, a set of instructions are generated for the shop floor. However, these CAPP processes can be time consuming and subject to inconsistencies. Current research seeks to automate the generation of work instructions by using previous designs and/or artificial intelligence. However, due to the complexity of manufacturing a wide range of products, the limited range of tools available and differing skills of the workforce, it is difficult to reach a generic solution for practical application. The novel pilot study given in this paper presents one of the first pieces of research comparing and contrasting a traditional manual approach to machined part process planning with an alternative haptic virtual environment. Within this, an operator can simulate the machining of a simple part using a virtual drilling and milling process via a haptic routing interface. All of the operator input is logged in the background with the system automatically generating shop floor instructions from this log file. Findings show that users found the virtual system to be more intuitive and required less mental workload than traditional manual methods. Also their perceptions for the future were that they would need less support for learning and would progress to final planning solutions more quickly.

scholarly journals MTS supported programming method for solid carbide end mill machining process

Mechanik ◽  
2016 ◽  
pp. 468-469
Author(s):  
Jan Burek ◽  
Marcin Sałata ◽  
Jarosław Buk ◽  
Paweł Sułkowicz
Keyword(s):  
Programming Method ◽  
Machining Process ◽  
End Mill ◽  
Solid Carbide ◽  
Mill Machining

Comparison of minimum quantity lubrication and wet milling based on energy consumption modeling

2021 ◽  
pp. 095440892110144
Author(s):  
Masuod Bayat ◽  
Mohammad Mahdi Abootorabi
Keyword(s):  
Energy Consumption ◽  
Manufacturing Industry ◽  
Minimum Quantity Lubrication ◽  
Milling Process ◽  
Numerical Control ◽  
Machining Process ◽  
Wet Milling ◽  
Total Energy Consumption ◽  
Minimum Quantity ◽  
Energy Consumption Modeling

Estimating the energy consumed by machining process is substantial because it has a large share of environmental effects in the manufacturing industry. In this paper, a generic energy consumption model was developed for milling processes that is able to be applied in all milling machine tools. Energy consumption of each segment was estimated according to power characteristics and parameters extracted from numerical control (NC) codes, then the total energy consumption was estimated by adding energy consumption of the machine components. Energy consumption of milling process was measured and compared in conventional (wet) and minimum quantity lubrication (MQL) conditions. The developed method was verified by comparing the estimated values of energy consumption with experimental results. Various studies have suggested different types of energy consumption modeling with machining, however; only a few studies have focused on the use of these modeling techniques. Thus, the MQL method has been rarely compared with the wet milling in terms of energy consumption. In the proposed model, energy consumption for workpiece adjustment, accounting for a major part of the costs in machining economics was considered for the first time. The results showed that the proposed method is efficient and practical for predicting energy consumption, with the possibility of occurring 5% error. Analysis of the results revealed that using the MQL method in milling process leads to 33% lower power consumption than wet milling and therefore, the MQL method can reduce the cost of production.

scholarly journals Deep Stacked Auto-Encoder Network Based Tool Wear Monitoring in the Face Milling Process

2020 ◽  
Vol 66 (4) ◽  
pp. 227-234
Author(s):  
VanThien Nguyen ◽  
VietHung Nguyen ◽  
VanTrinh Pham
Keyword(s):  
Tool Wear ◽  
Manufacturing Industry ◽  
Cutting Parameters ◽  
Milling Process ◽  
Machining Process ◽  
The Face ◽  
Wear Monitoring ◽  
Spindle Vibration ◽  
Deep Learning Network ◽  
Different Levels

Tool wear identification plays an important role in improving product quality and productivity in the manufacturing industry. The actual tool wear status with input cutting parameters may cause different levels of spindle vibration during the machining process. This research proposes an architecture comprising a deep learning network (DLN) to identify the actual wear state of machining tool. Firstly, data on spindle vibration signals are obtained from an acceleration sensor. The data are then pre-processed using the fast Fourier transform (FFT) method to reveal the relevant outstanding features in the frequency domain. Finally, the DLN is constructed based on stacked auto-encoders (SAE) and softmax, which is trained with the input data on the vibration features of the respective tool wear state. This DLN architecture is then used to identify the actual wear statuses of machining tool. The experimental results from the collected data show that the proposed DLN architecture is capable of identifying actual tool wear with high accuracy.

A reliable process planning approach based on fuzzy comprehensive evaluation method incorporating historical machining data

2019 ◽  
Vol 234 (5) ◽  
pp. 900-909 ◽  
Author(s):  
Wenping Mou ◽  
Xin Gao
Keyword(s):  
Process Planning ◽  
Evaluation Method ◽  
Tool Path ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Machining Process ◽  
Prototype System ◽  
Machining Parameters ◽  
Entropy Weight ◽  
Structural Parts

The quality of process planning could directly affect product quality, machining efficiency and cost. In small batch production such as machining aircraft structural parts, human experience is dominant in the process planning of those parts with great variability. Inferior planning of the machining process directly leads to low efficiency and quality, which has serious impact on the lead time of aircraft structural parts. To address these problems, different from the existing process knowledge reuse method by estimating the geometric similarity, a more reliable process planning method based on fuzzy comprehensive evaluation via historical machining data is proposed in this article. As long as machining resources are determined, a feature-based historical machining data model can be built, and the similarities between new machining features and the features in the database are estimated accordingly. Machining strategy, which contains tool path strategy and machining parameters, can then be identified according to the evaluation results of the similar features based on entropy weight method. A prototype system is developed and successfully applied to the typical aircraft structural parts.

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