The Experts below are selected from a list of 1842 Experts worldwide ranked by ideXlab platform
Bernard F. Rolfe - One of the best experts on this subject based on the ideXlab platform.
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Effects of temperature in relation to sheet Metal Stamping
2020Co-Authors: Paul C Okonkwo, M P Pereira, Georgina Kelly, Bernard F. RolfeAbstract:The demand to reduce the use of lubricants and increase tool life in sheet Metal Stamping has resulted in increased research on the sliding contact between the tool and the sheet materials. Unlubricated sliding wear tests for soft carbon steel sliding on D2 tool steel were performed using a pin-on-disk tribometer. The results revealed that temperature has an influencing role in the wear of tool steel and that material transfer between tool and sheet can be minimized at a certain temperature range in sheet Metal Stamping.
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Investigating galling wear behaviour in sheet Metal Stamping using acoustic emissions
Wear, 2018Co-Authors: Vignesh Vishnudas Shanbhag, Bernard F. Rolfe, Natarajan Arunachalam, M P PereiraAbstract:Abstract Galling wear in sheet Metal Stamping processes can degrade the product quality and adversely affect the mass production. Studies have shown that acoustic emissions sensors can be used to measure galling. However, the link between the features of the acoustic emissions signal and galling during complex manufacturing processes, such as sheet Metal Stamping, are not well understood. In the first section of this paper, it is shown that time domain features of the acoustic emission signal, such as RMS and peak, can be used to identify when the tooling is unworn or severely worn. These results were correlated with the wear measurement of the maximum depth of the surface profile of the stamped part. In the second section of the paper, time-frequency techniques were used to understand the characteristics of the AE signal associated with wear of the sheet Metal Stamping dies. The results show that it is possible to identify changes in acoustic emission signal using time-frequency techniques much prior to the observation of major changes in the time domain features and visual observation of wear on parts. In the third section of the paper, a new acoustic emission feature known as mean frequency estimate is proposed for the condition monitoring of the Stamping wear. This mean frequency estimate feature showed a clear shift in the acoustic emission signal much before the observation of severe wear. The methodology used in this paper to study wear progression can lay the basis for real-time monitoring of tool wear in the Stamping industry.
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Time series analysis of tool wear in sheet Metal Stamping using acoustic emission
Journal of Physics: Conference Series, 2017Co-Authors: Vignesh Vishnudas Shanbhag, Bernard F. Rolfe, M P Pereira, Natarajan ArunachalamAbstract:Galling is an adhesive wear mode that often affects the lifespan of Stamping tools. Since Stamping tools represent significant economic cost, even a slight improvement in maintenance cost is of high importance for the Stamping industry. In other manufacturing industries, online tool condition monitoring has been used to prevent tool wear-related failure. However, monitoring the acoustic emission signal from a Stamping process is a non-trivial task since the acoustic emission signal is non-stationary and non-transient. There have been numerous studies examining acoustic emissions in sheet Metal Stamping. However, very few have focused in detail on how the signals change as wear on the tool surface progresses prior to failure. In this study, time domain analysis was applied to the acoustic emission signals to extract features related to tool wear. To understand the wear progression, accelerated Stamping tests were performed using a semi-industrial Stamping setup which can perform clamping, piercing, Stamping in a single cycle. The time domain features related to Stamping were computed for the acoustic emissions signal of each part. The sidewalls of the stamped parts were scanned using an optical profilometer to obtain profiles of the worn part, and they were qualitatively correlated to that of the acoustic emissions signal. Based on the wear behaviour, the wear data can be divided into three stages: - In the first stage, no wear is observed, in the second stage, adhesive wear is likely to occur, and in the third stage severe abrasive plus adhesive wear is likely to occur. Scanning electron microscopy showed the formation of lumps on the Stamping tool, which represents galling behavior. Correlation between the time domain features of the acoustic emissions signal and the wear progression identified in this study lays the basis for tool diagnostics in Stamping industry.
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Audio signal analysis for tool wear monitoring in sheet Metal Stamping
Mechanical Systems and Signal Processing, 2017Co-Authors: Indivarie Ubhayaratne, M P Pereira, Y. Xiang, Bernard F. RolfeAbstract:Stamping tool wear can significantly degrade product quality, and hence, online tool condition monitoring is a timely need in many manufacturing industries. Even though a large amount of research has been conducted employing different sensor signals, there is still an unmet demand for a low-cost easy to set up condition monitoring system. Audio signal analysis is a simple method that has the potential to meet this demand, but has not been previously used for Stamping process monitoring. Hence, this paper studies the existence and the significance of the correlation between emitted sound signals and the wear state of sheet Metal Stamping tools. The corrupting sources generated by the tooling of the Stamping press and surrounding machinery have higher amplitudes compared to that of the sound emitted by the Stamping operation itself. Therefore, a newly developed semi-blind signal extraction technique was employed as a preprocessing technique to mitigate the contribution of these corrupting sources. The spectral analysis results of the raw and extracted signals demonstrate a significant qualitative relationship between wear progression and the emitted sound signature. This study lays the basis for employing low-cost audio signal analysis in the development of a real-time industrial tool condition monitoring system.
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An audio signal based model for condition monitoring of sheet Metal Stamping process
2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA), 2015Co-Authors: Indivarie Ubhayaratne, Y. Xiang, Michael Pereira, Bernard F. RolfeAbstract:Tool condition monitoring is an important factor in ensuring manufacturing efficiency and product quality. Audio signal based methods are a promising technique for condition monitoring. However, the influence of interfering signals and background noise has hindered the use of this technique in production sites. Blind signal separation (BSS) has the potential to solve this problem by recovering the signal of interest out of the observed mixtures, given that the knowledge about the BSS model is available. In this paper, we discuss the development of the BSS model for sheet Metal Stamping with a mechanical press system, so that the BSS techniques based on this model can be developed in future. This involves conducting a set of specially designed machine operations and developing a novel signal extraction technique. Also, the link between Stamping process conditions and the extracted audio signal associated with Stamping was successfully demonstrated by conducting a series of trials with different lubrication conditions and levels of tool wear.
R. Du - One of the best experts on this subject based on the ideXlab platform.
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Monitoring and Diagnosis of Sheet Metal Stamping Processes
Springer Series in Advanced Manufacturing, 2020Co-Authors: R. DuAbstract:Sheet Metal Stamping is one of the most commonly used manufacturing processes. Every day, millions of parts are made by Stamping, ranging from small battery caps to large automobile body panels. Yet, it is a difficult process involving the press, the dies (including the binder), the material (the blank) and the forming process with very large forces. Even with advanced technologies today, such as finite element modeling (FEM) and computer control, malfunctions occur from time to time. As a result, condition monitoring and fault diagnosis are important. This chapter presents research on monitoring and diagnosis of sheet Metal Stamping processes. It consists of five sections. Section 8.1 introduces some of the authors’ research on the sheet Metal Stamping process. Section 8.2 is a brief description of the sheet Metal Stamping process. Understanding this section is essential to the rest of the chapter. Section 8.3 presents an effective online monitoring method based on support vector regression (SVR). Section 8.4 gives a new diagnosis method based on infarred thermal imaging. Finally, Section 8.5 contains conclusions.
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Fault diagnosis of Stamping process based on empirical mode decomposition and learning vector quantization
International Journal of Machine Tools & Manufacture, 2007Co-Authors: A.m. Bassiuny, Xiaoli Li, R. DuAbstract:Sheet Metal Stamping process is widely used in industry due to its high accuracy and productivity. However, monitoring the process is a difficult task since the monitoring signals are typically non-stationary transient signals. In this paper, empirical mode decomposition (EMD) is applied to extract the main features of the strain signals. First, the signal is decomposed by EMD into intrinsic mode functions (IMF). Then the signal energy and the Hilbert marginal spectrum, which reflects the working condition and the fault pattern of the process, are computed. Finally, to identify the faulty conditions of process, the learning vector quantization (LVQ) network is used as a classifier with the Hilbert marginal spectrum as the input vectors. The performance of this method is tested by 107 experiments derived from different conditions in the sheet Metal Stamping process. The artificially created defects can be detected with a success rate of 96.3%. The method seems to be useful to monitor a sheet Metal Stamping process in practice.
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Diagnosis of sheet Metal Stamping processes based on 3-D thermal energy distribution
IEEE Transactions on Automation Science and Engineering, 2007Co-Authors: Yiu-Ming Harry Ng, Maolin Yu, Y Huang, R. DuAbstract:In this paper, a new approach is proposed using the 3-D thermal energy distribution of the workpiece. The new approach is based on the fact that during the Stamping process, the workpiece absorbs energy to deform. This mechanical energy is converted into thermal energy. Therefore, it is possible to diagnose the Stamping by analyzing the 3-D thermal energy distribution. In practice, the thermal energy distribution can be acquired using an infrared camera. However, it is often necessary to reconstruct the 3-D thermal energy distribution, which can be accomplished by using the Octree algorithm. On the other hand, one can compute the thermal energy distribution through finite-element modeling (FEM) as the baseline for diagnosis. Then, by comparison, the diagnosis can be carried out. A couple of examples are presented in detail together with the experiment validation. Note to Practitioners - These days computer-aided design (CAD) and finite-element modeling (FEM) are widely used for sheet Metal Stamping, especially in the automotive and aerospace industries. However, fault diagnosis and die tryout still rely heavily on the experiences of the engineers/machinists on the shop floor. An existing diagnosis method compares the strain distribution calculated using FEM and the experimental strain distribution, which is calculated from the measured deformation of the initial grid pattern. However, this method is time consuming as it requires the initial grid pattern preparation by either chemical etching or laser marking. This paper presents a new method for diagnosing sheet Metal Stamping processes. The new method compares the thermal distribution calculated using FEM and the experimental thermal distribution result, which can be acquired using an infrared (IR) camera. Therefore, it is more convenient to use it on the shop floor. The thermal FEM can be found based on strain FEM. However, the infrared image is 2-D and, hence, 3-D thermal distribution reconstruction is often necessary. This paper includes several practical examples. Some practical concerns, such as the conduction heat lost to the environment and the infrared camera viewing angles, are also discussed. © 2007 IEEE.
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Minimization of the thickness variation in multi-step sheet Metal Stamping
Journal of Materials Processing Technology, 2006Co-Authors: Y Huang, Z.y. Lo, R. DuAbstract:Abstract This paper presents an efficient method to optimize the intermedial tool surfaces in the multi-step sheet Metal Stamping process to obtain improved quality of a product at the end of forming. The proposed method is based on a combination of finite element modeling (FEM) and the response surface method (RSM). The objective of the optimization is to minimize the thickness variation of the part at the final stage. The constraint function of local fracture is introduced by the use of the forming limit curve (FLC). With acceptable accuracy and high efficiency, the multi-step inverse method is used together with RSM to check various intermediate surfaces to search for the optimal shape parameters. After the convergence of the optimization, the result is validated using commercial software DYNAFORM ® .
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A new approach to solve key issues in multi-step inverse finite-element method in sheet Metal Stamping
International Journal of Mechanical Sciences, 2006Co-Authors: Ying Huang, Yi-ping Chen, R. DuAbstract:Abstract Multi-step inverse finite-element method (FEM) has been introduced to improve the accuracy of simulation in the sheet Metal Stamping. Moreover, it has also been used to try to obtain the strain distribution and shape of the blank in the intermediate steps. But there are two key problems which are essential for the realization of multi-step inverse FEM: the first one is the determination of initial solutions on the intermediate three-dimensional (3-D) configurations and the other is how to control the movement of nodes only on sliding constraint surfaces during Newton–Raphson iterations. In the study, the two questions above have been solved with our proposed methods: the former is obtained by mapping the arc-length of the final part onto intermediate sliding constraint surfaces with modified arc-length search method, and the latter is conducted by introducing an approach which is similar to that of contact search. The present inverse multi-step FEM has been realized and applied to a two-step deep drawing product. The obtained numerical results have been used to compare with that of incremental FEM to evaluate the effectiveness of the procedures proposed. Comparisons between multi-step inverse FEM and one-step inverse FEM have also been conducted to verify the effect of multi-step.
M P Pereira - One of the best experts on this subject based on the ideXlab platform.
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Tool wear analysis in sheet Metal Stamping
2020Co-Authors: M P PereiraAbstract:This thesis advances the understanding of die wear in sheet Metal Stamping. It was found that transient conditions exist at the die radius, resulting in severe contact pressures that are critical to the wear behaviour. The findings challenge applicability of traditional wear tests and models for sheet Metal Stamping processes.
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Effects of temperature in relation to sheet Metal Stamping
2020Co-Authors: Paul C Okonkwo, M P Pereira, Georgina Kelly, Bernard F. RolfeAbstract:The demand to reduce the use of lubricants and increase tool life in sheet Metal Stamping has resulted in increased research on the sliding contact between the tool and the sheet materials. Unlubricated sliding wear tests for soft carbon steel sliding on D2 tool steel were performed using a pin-on-disk tribometer. The results revealed that temperature has an influencing role in the wear of tool steel and that material transfer between tool and sheet can be minimized at a certain temperature range in sheet Metal Stamping.
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Investigating galling wear behaviour in sheet Metal Stamping using acoustic emissions
Wear, 2018Co-Authors: Vignesh Vishnudas Shanbhag, Bernard F. Rolfe, Natarajan Arunachalam, M P PereiraAbstract:Abstract Galling wear in sheet Metal Stamping processes can degrade the product quality and adversely affect the mass production. Studies have shown that acoustic emissions sensors can be used to measure galling. However, the link between the features of the acoustic emissions signal and galling during complex manufacturing processes, such as sheet Metal Stamping, are not well understood. In the first section of this paper, it is shown that time domain features of the acoustic emission signal, such as RMS and peak, can be used to identify when the tooling is unworn or severely worn. These results were correlated with the wear measurement of the maximum depth of the surface profile of the stamped part. In the second section of the paper, time-frequency techniques were used to understand the characteristics of the AE signal associated with wear of the sheet Metal Stamping dies. The results show that it is possible to identify changes in acoustic emission signal using time-frequency techniques much prior to the observation of major changes in the time domain features and visual observation of wear on parts. In the third section of the paper, a new acoustic emission feature known as mean frequency estimate is proposed for the condition monitoring of the Stamping wear. This mean frequency estimate feature showed a clear shift in the acoustic emission signal much before the observation of severe wear. The methodology used in this paper to study wear progression can lay the basis for real-time monitoring of tool wear in the Stamping industry.
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Time series analysis of tool wear in sheet Metal Stamping using acoustic emission
Journal of Physics: Conference Series, 2017Co-Authors: Vignesh Vishnudas Shanbhag, Bernard F. Rolfe, M P Pereira, Natarajan ArunachalamAbstract:Galling is an adhesive wear mode that often affects the lifespan of Stamping tools. Since Stamping tools represent significant economic cost, even a slight improvement in maintenance cost is of high importance for the Stamping industry. In other manufacturing industries, online tool condition monitoring has been used to prevent tool wear-related failure. However, monitoring the acoustic emission signal from a Stamping process is a non-trivial task since the acoustic emission signal is non-stationary and non-transient. There have been numerous studies examining acoustic emissions in sheet Metal Stamping. However, very few have focused in detail on how the signals change as wear on the tool surface progresses prior to failure. In this study, time domain analysis was applied to the acoustic emission signals to extract features related to tool wear. To understand the wear progression, accelerated Stamping tests were performed using a semi-industrial Stamping setup which can perform clamping, piercing, Stamping in a single cycle. The time domain features related to Stamping were computed for the acoustic emissions signal of each part. The sidewalls of the stamped parts were scanned using an optical profilometer to obtain profiles of the worn part, and they were qualitatively correlated to that of the acoustic emissions signal. Based on the wear behaviour, the wear data can be divided into three stages: - In the first stage, no wear is observed, in the second stage, adhesive wear is likely to occur, and in the third stage severe abrasive plus adhesive wear is likely to occur. Scanning electron microscopy showed the formation of lumps on the Stamping tool, which represents galling behavior. Correlation between the time domain features of the acoustic emissions signal and the wear progression identified in this study lays the basis for tool diagnostics in Stamping industry.
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Audio signal analysis for tool wear monitoring in sheet Metal Stamping
Mechanical Systems and Signal Processing, 2017Co-Authors: Indivarie Ubhayaratne, M P Pereira, Y. Xiang, Bernard F. RolfeAbstract:Stamping tool wear can significantly degrade product quality, and hence, online tool condition monitoring is a timely need in many manufacturing industries. Even though a large amount of research has been conducted employing different sensor signals, there is still an unmet demand for a low-cost easy to set up condition monitoring system. Audio signal analysis is a simple method that has the potential to meet this demand, but has not been previously used for Stamping process monitoring. Hence, this paper studies the existence and the significance of the correlation between emitted sound signals and the wear state of sheet Metal Stamping tools. The corrupting sources generated by the tooling of the Stamping press and surrounding machinery have higher amplitudes compared to that of the sound emitted by the Stamping operation itself. Therefore, a newly developed semi-blind signal extraction technique was employed as a preprocessing technique to mitigate the contribution of these corrupting sources. The spectral analysis results of the raw and extracted signals demonstrate a significant qualitative relationship between wear progression and the emitted sound signature. This study lays the basis for employing low-cost audio signal analysis in the development of a real-time industrial tool condition monitoring system.
Yiu-Ming Harry Ng - One of the best experts on this subject based on the ideXlab platform.
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Diagnosis of sheet Metal Stamping processes based on 3-D thermal energy distribution
IEEE Transactions on Automation Science and Engineering, 2007Co-Authors: Yiu-Ming Harry Ng, Maolin Yu, Y Huang, R. DuAbstract:In this paper, a new approach is proposed using the 3-D thermal energy distribution of the workpiece. The new approach is based on the fact that during the Stamping process, the workpiece absorbs energy to deform. This mechanical energy is converted into thermal energy. Therefore, it is possible to diagnose the Stamping by analyzing the 3-D thermal energy distribution. In practice, the thermal energy distribution can be acquired using an infrared camera. However, it is often necessary to reconstruct the 3-D thermal energy distribution, which can be accomplished by using the Octree algorithm. On the other hand, one can compute the thermal energy distribution through finite-element modeling (FEM) as the baseline for diagnosis. Then, by comparison, the diagnosis can be carried out. A couple of examples are presented in detail together with the experiment validation. Note to Practitioners - These days computer-aided design (CAD) and finite-element modeling (FEM) are widely used for sheet Metal Stamping, especially in the automotive and aerospace industries. However, fault diagnosis and die tryout still rely heavily on the experiences of the engineers/machinists on the shop floor. An existing diagnosis method compares the strain distribution calculated using FEM and the experimental strain distribution, which is calculated from the measured deformation of the initial grid pattern. However, this method is time consuming as it requires the initial grid pattern preparation by either chemical etching or laser marking. This paper presents a new method for diagnosing sheet Metal Stamping processes. The new method compares the thermal distribution calculated using FEM and the experimental thermal distribution result, which can be acquired using an infrared (IR) camera. Therefore, it is more convenient to use it on the shop floor. The thermal FEM can be found based on strain FEM. However, the infrared image is 2-D and, hence, 3-D thermal distribution reconstruction is often necessary. This paper includes several practical examples. Some practical concerns, such as the conduction heat lost to the environment and the infrared camera viewing angles, are also discussed. © 2007 IEEE.
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CASE - Diagnosis of sheet Metal Stamping processes based on thermal energy distribution
IEEE International Conference on Automation Science and Engineering 2005., 2005Co-Authors: Yiu-Ming Harry Ng, Maolin Yu, Y Huang, R. DuAbstract:Computer-aid design (CAD) and finite element analysis (FEA) have been widely used in sheet Metal Stamping nowadays, especially in automotive and aerospace industries. However, die tryout and fault diagnosis still heavily rely on the experiences of the machinists on the shop floor. In this paper, a novel approach is proposed using the thermal energy distribution of the part. The new approach is based on the fact that during the Stamping process, the part absorbs energy to deform. Since most of the (plastic) deformation energy would convert to heat energy, it is therefore possible to detect possible defects by means of analyzing its thermal energy distribution. In practice, the thermal energy distribution can be acquired using an infrared camera. Furthermore, it is possible to compute the thermal energy distribution through a simple FEA. A practical example of cup drawing is discussed in details together with the experiment validation.
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Diagnosis of sheet Metal Stamping processes based on thermal energy distribution
IEEE International Conference on Automation Science and Engineering 2005., 2005Co-Authors: Yiu-Ming Harry Ng, Maolin Yu, Y Huang, R. DuAbstract:Computer-aid design (CAD) and finite element analysis (FEA) have been widely used in sheet Metal Stamping nowadays, especially in automotive and aerospace industries. However, die tryout and fault diagnosis still heavily rely on the experiences of the machinists on the shop floor. In this paper, a novel approach is proposed using the thermal energy distribution of the part. The new approach is based on the fact that during the Stamping process, the part absorbs energy to deform. Since most of the (plastic) deformation energy would convert to heat energy, it is therefore possible to detect possible defects by means of analyzing its thermal energy distribution. In practice, the thermal energy distribution can be acquired using an infrared camera. Furthermore, it is possible to compute the thermal energy distribution through a simple FEA. A practical example of cup drawing is discussed in details together with the experiment validation.
Y Huang - One of the best experts on this subject based on the ideXlab platform.
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Diagnosis of sheet Metal Stamping processes based on 3-D thermal energy distribution
IEEE Transactions on Automation Science and Engineering, 2007Co-Authors: Yiu-Ming Harry Ng, Maolin Yu, Y Huang, R. DuAbstract:In this paper, a new approach is proposed using the 3-D thermal energy distribution of the workpiece. The new approach is based on the fact that during the Stamping process, the workpiece absorbs energy to deform. This mechanical energy is converted into thermal energy. Therefore, it is possible to diagnose the Stamping by analyzing the 3-D thermal energy distribution. In practice, the thermal energy distribution can be acquired using an infrared camera. However, it is often necessary to reconstruct the 3-D thermal energy distribution, which can be accomplished by using the Octree algorithm. On the other hand, one can compute the thermal energy distribution through finite-element modeling (FEM) as the baseline for diagnosis. Then, by comparison, the diagnosis can be carried out. A couple of examples are presented in detail together with the experiment validation. Note to Practitioners - These days computer-aided design (CAD) and finite-element modeling (FEM) are widely used for sheet Metal Stamping, especially in the automotive and aerospace industries. However, fault diagnosis and die tryout still rely heavily on the experiences of the engineers/machinists on the shop floor. An existing diagnosis method compares the strain distribution calculated using FEM and the experimental strain distribution, which is calculated from the measured deformation of the initial grid pattern. However, this method is time consuming as it requires the initial grid pattern preparation by either chemical etching or laser marking. This paper presents a new method for diagnosing sheet Metal Stamping processes. The new method compares the thermal distribution calculated using FEM and the experimental thermal distribution result, which can be acquired using an infrared (IR) camera. Therefore, it is more convenient to use it on the shop floor. The thermal FEM can be found based on strain FEM. However, the infrared image is 2-D and, hence, 3-D thermal distribution reconstruction is often necessary. This paper includes several practical examples. Some practical concerns, such as the conduction heat lost to the environment and the infrared camera viewing angles, are also discussed. © 2007 IEEE.
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Minimization of the thickness variation in multi-step sheet Metal Stamping
Journal of Materials Processing Technology, 2006Co-Authors: Y Huang, Z.y. Lo, R. DuAbstract:Abstract This paper presents an efficient method to optimize the intermedial tool surfaces in the multi-step sheet Metal Stamping process to obtain improved quality of a product at the end of forming. The proposed method is based on a combination of finite element modeling (FEM) and the response surface method (RSM). The objective of the optimization is to minimize the thickness variation of the part at the final stage. The constraint function of local fracture is introduced by the use of the forming limit curve (FLC). With acceptable accuracy and high efficiency, the multi-step inverse method is used together with RSM to check various intermediate surfaces to search for the optimal shape parameters. After the convergence of the optimization, the result is validated using commercial software DYNAFORM ® .
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CASE - Diagnosis of sheet Metal Stamping processes based on thermal energy distribution
IEEE International Conference on Automation Science and Engineering 2005., 2005Co-Authors: Yiu-Ming Harry Ng, Maolin Yu, Y Huang, R. DuAbstract:Computer-aid design (CAD) and finite element analysis (FEA) have been widely used in sheet Metal Stamping nowadays, especially in automotive and aerospace industries. However, die tryout and fault diagnosis still heavily rely on the experiences of the machinists on the shop floor. In this paper, a novel approach is proposed using the thermal energy distribution of the part. The new approach is based on the fact that during the Stamping process, the part absorbs energy to deform. Since most of the (plastic) deformation energy would convert to heat energy, it is therefore possible to detect possible defects by means of analyzing its thermal energy distribution. In practice, the thermal energy distribution can be acquired using an infrared camera. Furthermore, it is possible to compute the thermal energy distribution through a simple FEA. A practical example of cup drawing is discussed in details together with the experiment validation.
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Diagnosis of sheet Metal Stamping processes based on thermal energy distribution
IEEE International Conference on Automation Science and Engineering 2005., 2005Co-Authors: Yiu-Ming Harry Ng, Maolin Yu, Y Huang, R. DuAbstract:Computer-aid design (CAD) and finite element analysis (FEA) have been widely used in sheet Metal Stamping nowadays, especially in automotive and aerospace industries. However, die tryout and fault diagnosis still heavily rely on the experiences of the machinists on the shop floor. In this paper, a novel approach is proposed using the thermal energy distribution of the part. The new approach is based on the fact that during the Stamping process, the part absorbs energy to deform. Since most of the (plastic) deformation energy would convert to heat energy, it is therefore possible to detect possible defects by means of analyzing its thermal energy distribution. In practice, the thermal energy distribution can be acquired using an infrared camera. Furthermore, it is possible to compute the thermal energy distribution through a simple FEA. A practical example of cup drawing is discussed in details together with the experiment validation.