scholarly journals Stochastic Modeling and Diagnosis of Leak Areas for Surface Assembly

2018 ◽  
Vol 140 (4) ◽  
Author(s):  
Jie Ren ◽  
Chiwoo Park ◽  
Hui Wang
Keyword(s):  
Functional Performance ◽  
Training Data ◽  
Manufacturing Processes ◽  
Machining Processes ◽  
Surface Machining ◽  
Root Cause ◽  
Surface Assembly ◽  
Surface Flatness ◽  
Automotive Powertrain ◽  
Color Tracking

Assembly through mating a pair of machined surfaces plays a crucial role in many manufacturing processes such as automotive powertrain production, and the mating errors during the assembly (i.e., gaps between surfaces) can cause significant internal leakage and functional performance problems. The surface mating errors are difficult to diagnose because they are not measurable. Current in-plant quality control for surface mating focuses on controlling the surface flatness of each individual part before they are mated, and the mating errors are indirectly evaluated by a pressurized sealing test to check whether any pressure drop occurs. However, it does not provide any clue to engineers about the origins and the root cause of the internal leakage. To address these limitations, this paper presents a pressurized color-tracking method to directly measure internal leak areas. By using the measurements of leak areas and the profiles of surfaces mated as training data along with Hagen–Poiseuille law, this paper develops a novel diagnostic method to predict potential leak areas (leakage paths) given the measurements on the profiles of mating surfaces. The effectiveness and robustness of the proposed method are verified by a simulation study and an experiment. The approach provides practical guidance for the subsequent assembly process as well as troubleshooting in surface machining processes.

scholarly journals Improving the Performance of Steel Machining Processes through Cutting by Vibration Control

Materials ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 5712
Author(s):  
Mihaela Oleksik ◽  
Dan Dobrotă ◽  
Mădălin Tomescu ◽  
Valentin Petrescu
Keyword(s):  
Fourier Transformation ◽  
Vibration Analysis ◽  
Cutting Tool ◽  
Cutting Process ◽  
Manufacturing Processes ◽  
Machining Processes ◽  
Short Time ◽  
Short Time Fourier Transformation ◽  
Dynamic Phenomena

Machining processes through cutting are accompanied by dynamic phenomena that influence the quality of the processed surfaces. Thus, this research aimed to design, make, and use a tool with optimal functional geometry, which allowed a reduction of the dynamic phenomena that occur in the cutting process. In order to carry out the research, the process of cutting by front turning with transversal advance was taken into account. Additionally, semi-finished products with a diameter of Ø = 150 mm made of C45 steel were chosen for processing (1.0503). The manufacturing processes were performed with the help of two tools: a cutting tool, the classic construction version, and another that was the improved construction version. In the first stage of the research, an analysis was made of the vibrations that appear in the cutting process when using the two types of tools. Vibration analysis considered the following: use of the Fast Fourier Transform (FFT) method, application of the Short-Time Fourier-Transformation (STFT) method, and observation of the acceleration of vibrations recorded during processing. After the vibration analysis, the roughness of the surfaces was measured and the parameter Ra was taken into account, but a series of diagrams were also drawn regarding the curved profiles, filtered profiles, and Abbott–Firestone curve. The research showed that use of the tool that is the improved constructive variant allows accentuated reduction of vibrations correlated with an improvement of the quality of the processed surfaces.

Surface Generation by Material Removal in Manufacturing Processes from Machine Building

2014 ◽  
Vol 659 ◽  
pp. 112-117
Author(s):  
Laurenţiu Slătineanu ◽  
Margareta Coteaţă ◽  
Irina Besliu ◽  
Oana Dodun ◽  
Miroslav Radovanović
Keyword(s):  
Material Removal ◽  
Machine Building ◽  
Surface Generation ◽  
Manufacturing Processes ◽  
Machining Processes ◽  
Machined Surfaces

The examination of the main machining methods applied in manufacturing processes from machine building and based on material removal from workpiece highlights essentially the existence of distinct processes able to generate material. An analysis of certain machining methods able to develop processes of material removal from workpieces was initiated by taking into consideration the principle machining schema and the capacity of generating machined surfaces. One concluded that within distinct machining processes, various phenomena are applied in order to obtain material removal from workpiece.

scholarly journals The ethical adoption of artificial intelligence in radiology

BJR|Open ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 20190020 ◽  
Author(s):  
Keshav Shree Mudgal ◽  
Neelanjan Das
Keyword(s):  
Artificial Intelligence ◽  
Health Authority ◽  
Training Data ◽  
Current Understanding ◽  
Prediction System ◽  
Knowledge Gaps ◽  
Cause Analysis ◽  
Distant Future ◽  
Root Cause ◽  
Data Usage

Artificial intelligence (AI) is rapidly transforming healthcare—with radiology at the pioneering forefront. To be trustfully adopted, AI needs to be lawful, ethical and robust. This article covers the different aspects of a safe and sustainable deployment of AI in radiology during: training, integration and regulation. For training, data must be appropriately valued, and deals with AI companies must be centralized. Companies must clearly define anonymization and consent, and patients must be well-informed about their data usage. Data fed into algorithms must be made AI-ready by refining, purification, digitization and centralization. Finally, data must represent various demographics. AI needs to be safely integrated with radiologists-in-the-loop: guiding forming concepts of AI solutions and supervising training and feedback. To be well-regulated, AI systems must be approved by a health authority and agreements must be made upon liability for errors, roles of supervised and unsupervised AI and fair workforce distribution (between AI and radiologists), with a renewal of policy at regular intervals. Any errors made must have a root-cause analysis, with outcomes fedback to companies to close the loop—thus enabling a dynamic best prediction system. In the distant future, AI may act autonomously with little human supervision. Ethical training and integration can ensure a "transparent" technology that will allow insight: helping us reflect on our current understanding of imaging interpretation and fill knowledge gaps, eventually moulding radiological practice. This article proposes recommendations for ethical practise that can guide a nationalized framework to build a sustainable and transparent system.

scholarly journals Induction of Highly Dynamic Shock Waves in Machining Processes with Multiple Loads and Short Tool Impacts

2019 ◽  
Vol 9 (11) ◽  
pp. 2293 ◽  
Author(s):  
Andreas Tausendfreund ◽  
Dirk Stöbener ◽  
Andreas Fischer
Keyword(s):  
Shock Waves ◽  
High Speed ◽  
Short Pulse ◽  
Milling Process ◽  
Manufacturing Processes ◽  
Speckle Photography ◽  
Machining Processes ◽  
Initial State ◽  
Multiple Loads ◽  
Measurement Results

In order to study the mechanical loads of a workpiece in manufacturing processes such as single-tooth milling, in-process measurements of workpiece deformations are required. To enable the resolution of shock waves due to the mechanical impact of the tool, a novel measurement system based on speckle photography is introduced to measure the dynamic deformations and strains with a high temporal and spatial resolution. The measurement results indicate deformations and strains propagating through the workpiece with the speed of sound triggered by the tool impact (i.e., the tool impact is shown to induce shock waves during milling). Finite element simulations of the workpiece behavior are performed in addition, which support the experimental findings. In the considered case, the dynamic excitation subsides after 300 ms. Hence, in processes with even shorter cyclic multiple loads, the tool encounters an already excited initial state during machining, which needs to be taken into account when precisely modeling the milling process and the resulting workpiece quality. Finally, the measurement results demonstrate that speckle photography in combination with modern high-speed cameras and compact short-pulse lasers provides a deeper understanding of individual manufacturing processes.

scholarly journals Analysis of Flatness Deviations for Austenitic Stainless Steel Workpieces after Efficient Surface Machining

2014 ◽  
Vol 14 (4) ◽  
pp. 204-212 ◽  
Author(s):  
K. Nadolny ◽  
W. Kapłonek
Keyword(s):  
Stainless Steel ◽  
Austenitic Stainless Steel ◽  
Experimental Tests ◽  
Machining Process ◽  
Roughness Parameters ◽  
Workpiece Surface ◽  
Surface Machining ◽  
Measurement Results ◽  
Surface Flatness ◽  
Surface Topographies

Abstract The following work is an analysis of flatness deviations of a workpiece made of X2CrNiMo17-12-2 austenitic stainless steel. The workpiece surface was shaped using efficient machining techniques (milling, grinding, and smoothing). After the machining was completed, all surfaces underwent stylus measurements in order to obtain surface flatness and roughness parameters. For this purpose the stylus profilometer Hommel-Tester T8000 by Hommelwerke with HommelMap software was used. The research results are presented in the form of 2D surface maps, 3D surface topographies with extracted single profiles, Abbott-Firestone curves, and graphical studies of the Sk parameters. The results of these experimental tests proved the possibility of a correlation between flatness and roughness parameters, as well as enabled an analysis of changes in these parameters from shaping and rough grinding to finished machining. The main novelty of this paper is comprehensive analysis of measurement results obtained during a three-step machining process of austenitic stainless steel. Simultaneous analysis of individual machining steps (milling, grinding, and smoothing) enabled a complementary assessment of the process of shaping the workpiece surface macro- and micro-geometry, giving special consideration to minimize the flatness deviations

Electrofluidic Assembly of Nanoelectromechanical Systems

2001 ◽  
Vol 687 ◽  
Author(s):  
Stephane Evoy ◽  
Ben Hailer ◽  
Martin Duemling ◽  
Benjamin R. Martin ◽  
Thomas E. Mallouk ◽  
...  
Keyword(s):  
Nanoelectromechanical Systems ◽  
Quality Factors ◽  
Top Down ◽  
High Quality ◽  
Resonant Frequencies ◽  
Surface Machining ◽  
Sensor Applications ◽  
Surface Assembly ◽  
Manufacturing Technologies ◽  
20 Nm

AbstractRecent advances in surface nanomachining have allowed the fabrication of mechanical structures with dimensions reaching 20 nm, and resonant frequencies in the 100s of MHz. Structural issues prevent the “top-down” surface machining of high-quality NEMS resonators. Such systems are alternatively to be bestowed by “bottom-up” manufacturing technologies. We report the surface assembly of RF-range NEMS. Using electrofluidic assembly, we have successfully positioned Rh mechanical beams onto specific sites of a silicon circuit. With diameters as small as 250 nm and lengths varying from 2 to 3 [.proportional]m, preliminary results show mechanical resonances ranging from 5 MHz to 80 MHz, and quality factors reaching 500. We also report the development of nanostructured NEMS for sensor applications, and present strategies for their deployment in integrative nanosystems.

An Intelligent Optimization Approach of Feedrate Scheduling Based on Hybrid Simulation Models

2008 ◽  
Vol 392-394 ◽  
pp. 211-215
Author(s):  
Li Qiang Zhang ◽  
Yu Han Wang ◽  
Ming Chen
Keyword(s):  
Tool Path ◽  
Mechanistic Model ◽  
Geometric Model ◽  
Physical Models ◽  
Free Form ◽  
Optimization Approach ◽  
Machining Processes ◽  
Surface Machining ◽  
Feedrate Scheduling ◽  
Free Form Surface

In free-form surface machining, it is essential to optimize the feedrate in order to improve the machining efficiency. Conservative constant feedrate values have been mostly used since there was a lack of physical models and optimization tools for the machining processes. The overall goal of this research is the integration of geometric and mechanistic milling models for force prediction and feedrate scheduling for free-form surface machining. For each tool move a geometric model calculates the cutting geometry parameters, then a mechanistic model uses this information with the constraint force to calculate desired feedrates. The feedrate is written into the part program. When the integrated modeling approach was used, it was shown that the machining time can be decreased significantly along the tool path. Production time in machining propeller example was reduced to 35% compared to constant feedrate cases.

Investigating Cyber-Physical Threats of Numerically Controlled Manufacturing Processes

2020 ◽  
Author(s):  
Joseph Piacenza ◽  
Kenneth J. Faller ◽  
Bradley Regez ◽  
Luisfernando Gomez
Keyword(s):  
Manufacturing Systems ◽  
Ex Situ ◽  
Raspberry Pi ◽  
Manufacturing Processes ◽  
Device Design ◽  
Cnc Machine ◽  
Machining Processes ◽  
Machine Performance ◽  
Design Iteration ◽  
Lathe Machine

Abstract Motivated by cyber-physical vulnerabilities in precision manufacturing processes, there is a need to externally examine the operational performance of Computer Numerically Controlled (CNC) manufacturing systems. The overarching objective of this work is to design and fabricate a proof-of-concept CNC machine evaluation device, ultimately re-configurable to the mill and lathe machine classes. This device will assist in identifying potential cyber-physical security threats in manufacturing systems by identifying perturbations, outside the expected variations of machining processes, and comparing the desired command inputted into the numerical controller and the actual machine performance (e.g., tool displacement, frequency). In this directed research, a device design is presented based on specific performance requirements provided by the project sponsor. The first design iteration is tested on a Kuka KR 6 R700 series robotic arm, and machine movement comparisons are performed ex-situ using Keyence laser measurement sensors. Data acquisition is performed with a Raspberry Pi 4 microcomputer, controlled by custom, cross-platform Python code, and includes a touch screen human-computer interface. A device design adapted for a CNC mill is also presented, and the Haas TM-2 is used as a case study, which can be operated by technicians to check CNC machine accuracy, as needed, before a critical manufacturing process.

Multi-Operational Machining Processes Modeling for Sequential Root Cause Identification and Measurement Reduction

2004 ◽  
Author(s):  
Hui Wang ◽  
Qiang Huang ◽  
Reuven Katz
Keyword(s):  
Machine Tool ◽  
Propagation Model ◽  
Machining Processes ◽  
Error Sources ◽  
Variation Reduction ◽  
Measurement Reduction ◽  
Propagation Modeling ◽  
Root Cause ◽  
Variation Propagation ◽  
Root Cause Identification

Variation propagation modeling has been proved to be an effective way for variation reduction and design synthesis in multi-operational manufacturing processes (MMP). However, previously developed approaches for machining processes did not directly model the process physics regarding how fixture, and datum, and machine tool errors generate the same pattern on part features. Consequently, it is difficult to distinguish error sources at each operation. This paper formulates the variation propagation model using the proposed equivalent fixture error (EFE) concept. With this concept, datum error and machine tool error are transformed to equivalent fixture locator errors at each operation. As a result, error sources can be grouped and root cause identification can be conducted in a sequential manner. The case studies demonstrate the model validity through a real cutting experiment and model advantage in measurement reduction for root cause identification.

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