Predictive-Inspection Based Process Control in End Milling Operations

2005 ◽  
Author(s):  
Aftab Khan ◽  
Dawn Tilbury ◽  
James Moyne
Keyword(s):  
Process Control ◽  
Product Quality ◽  
Manufacturing Process ◽  
Process Model ◽  
Manufacturing Industry ◽  
End Milling ◽  
Loop Control ◽  
Diagnostic Data ◽  
Milling Operations ◽  
Final Inspection

In the manufacturing industry, product quality control is often treated as a completely different problem than process diagnostics. Diagnostics methods are used to quickly identify faults during the process, whereas product quality is assessed at the final inspection stage, after the process is completed. The large amount of data that is collected to enable the on-line diagnostics, however, can be used to predict the product quality before the part is measured at the final inspection stage. This predicted quality can be used as feedback to a control system that improves the process quality by adjusting the process inputs. In this paper we propose a predictive inspection based process control solution for a manufacturing process. A manufacturing process is modelled as an input-output system with the machine settings as inputs and two kinds of outputs: diagnostic data and quality. This model is obtained from off-line experiments using a combination of process inputs and external disturbances. In the online implementation the predictive process model is updated with the diagnostic data collected during runtime and quality is improved by using a two-loop control strategy, on a part-to-part or run-to-run (R2R) basis. The proposed approach is applied to and developed for an end milling operation and simulation and experimental results are presented.

Learning Algorithm Based Modeling and Process Parameters Recommendation System for Binder Jetting Additive Manufacturing Process

2015 ◽  
Author(s):  
Han Chen ◽  
Yaoyao F. Zhao
Keyword(s):  
Additive Manufacturing ◽  
Product Quality ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Process Model ◽  
Recommendation System ◽  
Powder Materials ◽  
Quality Properties ◽  
Binder Jetting ◽  
Printing Time

Binder Jetting (BJ) process is an additive manufacturing process in which powder materials are selectively joined by binder materials. Products can be manufactured layer by layer directly from 3D model data. It is not always easy for manufacturing engineers to choose proper BJ process parameters to meet the end-product quality and fabrication time requirements. This is because the quality properties of the products fabricated by BJ process are significantly affected by the process parameters. And the relationships between process parameters and quality properties are very complicated. In this paper, a process model is developed by Backward Propagation (BP) Neural Network (NN) algorithm based on 16 groups of orthogonal experiment designed by Taguchi Method to express the relationships between 4 key process parameters and 2 key quality properties. Based on the modeling results, an intelligent parameters recommendation system is developed to predict end-product quality properties and printing time, and to recommend process parameters selection based on the process requirements. It can be used as a guideline for selecting the proper printing parameters in BJ to achieve the desired properties and help to reduce the printing time.

Real-Time Control of Cyber-Physical Manufacturing Process Under Uncertainty

2018 ◽  
Author(s):  
Saideep Nannapaneni ◽  
Sankaran Mahadevan ◽  
Abhishek Dubey
Keyword(s):  
Process Control ◽  
Dimension Reduction ◽  
Product Quality ◽  
Real Time ◽  
Manufacturing Process ◽  
Sensor Data ◽  
Control Input ◽  
Time Process ◽  
Computational System ◽  
Uncertainty Sources

Modern manufacturing processes are increasing becoming cyber-physical in nature, where a computational system monitors the system performance, provides real-time process control by analyzing sensor data collected regarding process and product characteristics, in order to increase the quality of the manufactured product. Such real-time process monitoring and control techniques are useful in precision and ultra-precision machining processes. However, the output product quality is affected by several uncertainty sources in various stages of the manufacturing process such as the sensor uncertainty, computational system uncertainty, control input uncertainty, and the variability in the manufacturing process. The computational system may be a single computing node or a distributed computing network; the latter scenario introduces additional uncertainty due to the communication between several computing nodes. Due to the continuous monitoring process, these uncertainty sources aggregate and compound over time, resulting in variations of product quality. Therefore, characterization of the various uncertainty sources and their impact on the product quality are necessary to increase the efficiency and productivity of the overall manufacturing process. To this end, this paper develops a two-level dynamic Bayesian network methodology, where the higher level captures the uncertainty in the sensors, control inputs, and the manufacturing process while the lower level captures the uncertainty in the communication between several computing nodes. In addition, we illustrate the use of a variance-based global sensitivity analysis approach for dimension reduction in a high-dimensional manufacturing process, in order to enable real-time analysis for process control. The proposed methodologies of process control under uncertainty and dimension reduction are illustrated for a cyber-physical turning process.

Research of Discrete Manufacturing Industry Production Control System Based on RFID Technology

2014 ◽  
Vol 926-930 ◽  
pp. 1493-1496
Author(s):  
Xiang Qian Ding ◽  
Wei Dong Zhang ◽  
Rui Chun Hou
Keyword(s):  
Control System ◽  
Process Control ◽  
Production Process ◽  
Real Time ◽  
Manufacturing Process ◽  
Manufacturing Industry ◽  
Production Control ◽  
Process Control System ◽  
Rfid Technology ◽  
Discrete Manufacturing

In view of the current discrete manufacturing workshop production process control problem of poor real-time performance, reliability, this paper proposes a discrete manufacture based on rfid technology workshop production process control system solutions. For discrete manufacturing enterprise workshop layer of the production process control system emphasizes the manufacturing process of real-time data acquisition, validity and enforceability of the production plan. Developed a discrete manufacturing process control system based on RFID, provides the foundation for just-in-time production of discrete manufacturing.

scholarly journals PROCESS CAPABILITY IMPROVEMENT BY PUTTING ‘STATISTICAL PROCESS CONTROL’ INTO PRACTICE

2013 ◽  
pp. 251-256
Author(s):  
PIYUSH KUMAR SONI ◽  
IMTIYAZ KHAN ◽  
ABHISHEK ROHILLA
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Product Quality ◽  
Statistical Process Control ◽  
Manufacturing Process ◽  
Process Capability ◽  
Statistical Process ◽  
Quality Of Products ◽  
Capability Improvement

Quality control helps industries in improvement of its product quality and productivity. Statistical Process Control (SPC) is one of the tools to control the quality of products that practice in bringing a manufacturing process under control. In this paper, the process control of a CNC Grinder manufactured at PMT Machines Ltd. Halol, (Gujarat) India is discussed. The varying measurements have been recorded for a number of samples of a Cam Roller Shoe obtained from a number of trials with the CNC Grinder. SPC technique has been adopted, by which the process is finally brought under control and process capability is improved.

scholarly journals Fabrication and characterization of resistive double square loop arrays for ultra-wide bandwidth microwave absorption

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ji-Young Jeong ◽  
Je-Ryung Lee ◽  
Hyeonjin Park ◽  
Joonkyo Jung ◽  
Doo-Sun Choi ◽  
...  
Keyword(s):  
Sheet Resistance ◽  
Manufacturing Process ◽  
End Milling ◽  
Milling Process ◽  
Wide Bandwidth ◽  
Machined Surface ◽  
Array Pattern ◽  
Micro End Milling ◽  
Array Structures ◽  
Printing Processes

AbstractMicrowave absorbers using conductive ink are generally fabricated by printing an array pattern on a substrate to generate electromagnetic fields. However, screen printing processes are difficult to vary the sheet resistance values for different regions of the pattern on the same layer, because the printing process deposits materials at the same height over the entire surface of substrate. In this study, a promising manufacturing process was suggested for engraved resistive double square loop arrays with ultra-wide bandwidth microwave. The developed manufacturing process consists of a micro-end-milling, inking, and planing processes. A 144-number of double square loop array was precisely machined on a polymethyl methacrylate workpiece with the micro-end-milling process. After engraving array structures, the machined surface was completely covered with the developed conductive carbon ink with a sheet resistance of 15 Ω/sq. It was cured at room temperature. Excluding the ink that filled the machined double square loop array, overflowed ink was removed with the planing process to achieve full filled and isolated resistive array patterns. The fabricated microwave absorber showed a small radar cross-section with reflectance less than − 10 dB in the frequency band range of 8.0–14.6 GHz.

Toward Metamodels for Composable and Reusable Additive Manufacturing Process Models

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Paul Witherell ◽  
Shaw Feng ◽  
Timothy W. Simpson ◽  
David B. Saint John ◽  
Pan Michaleris ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Metal Powder ◽  
Manufacturing Process ◽  
Process Model ◽  
Model Development ◽  
Process Models ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Future Work ◽  
Am Processes

In this paper, we advocate for a more harmonized approach to model development for additive manufacturing (AM) processes, through classification and metamodeling that will support AM process model composability, reusability, and integration. We review several types of AM process models and use the direct metal powder bed fusion AM process to provide illustrative examples of the proposed classification and metamodel approach. We describe how a coordinated approach can be used to extend modeling capabilities by promoting model composability. As part of future work, a framework is envisioned to realize a more coherent strategy for model development and deployment.

Optimal Parameter Design of Solder Residue in Flip Chip Process by Using Taguchi Method

2010 ◽  
Vol 443 ◽  
pp. 543-548
Author(s):  
Jian Long Kuo ◽  
Kai Lun Chao ◽  
Chun Cheng Kuo
Keyword(s):  
Taguchi Method ◽  
Product Quality ◽  
Manufacturing Process ◽  
Flip Chip ◽  
Optimal Parameter ◽  
Experimental Testing ◽  
Signal To Noise Ratio ◽  
Optimal Solution ◽  
Passive Component

Because the solder residue was found in the manufacturing process which greatly affected the product quality, the purpose of this paper was to make the product quality improved and to find an optimal solution for process parameters in the flip chip process. The experimental testing was based on SMT manufacturing process. The amount and size of solder left on passive component in the process of manufacturing were considered as the quality traits. Since too many solders left on the passive component side during flux cleaning process, it was possible that the balling would be flowed into the chip, which caused the bump short in the chip and affected the quality of the product. In this paper, orthogonal array by using Taguchi method is adopted as the effective experimental method with the least experimental runs. Also, based on the quality evaluation of signal-to-noise ratio, the ANOVA is used to evaluate the effects of quality target according to the experimental results. The results reveal that the optimization in the process is confirmed. Therefore, this study can effectively improve the solder residue in semiconductor manufacturing process.

Discrete part manufacturing process control with quality considerations

1992 ◽  
Vol 30 (8) ◽  
pp. 1889-1899
Author(s):  
ROBERT P. DAVIS ◽  
WILLIAM G. FERRELL ◽  
SANKAR SENGUPTA
Keyword(s):  
Process Control ◽  
Manufacturing Process ◽  
Manufacturing Process Control ◽  
Discrete Part
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