S. K. Hazra

Benchmark 2 – Springback of a Jaguar Land Rover Aluminium

The aim of this benchmark is the numerical prediction of the springback of an aluminium panel used in the production of a Jaguar car. The numerical simulation of springback has been very important for the reduction of die try outs through the design of the tools with die compensation, thereby allowing for the production of dimensionally accurate complex parts at a reduced cost. The forming stage of this benchmark includes one single forming operation followed by a trimming operation. Cross-sectional profiles should be reported at specific (provided) sections in the part before and after springback. Problem description, tool geometries, material properties, and the required simulation reports are summarized in this benchmark briefing.

Predicting the Occurrence of Cosmetic Defects in Automotive Skin Panels

The appearance of defects such as hollows and shock lines can affect the perceived quality and attractiveness of automotive skin panels. These defects are the result of the stamping process and appear as small, localized deviations from the intended styling of the panels. Despite their size, they become visually apparent after the application of paint and the perceived quality of a panel may become unacceptable. Considerable time is then dedicated to minimizing their occurrence through tool modifications. This paper will investigate the use of the wavelet transform as a tool to analyze physically measured panels. The transform has two key aspects. The first is its ability to distinguish small scale local defects from large scale styling curvature. The second is its ability to characterize the shape of a defect in terms of its wavelength and a correlation value. The two features of the transform enable it to be used as a tool for locating and predicting the severity of defects. The paper will describe the transform and illustrate its application on test cases.

Detecting subtle cosmetic defects in automotive skin panels

Abstract Cosmetic defects, such as ‘hollows’, are deviations in topology of automotive skin panels that form as a result of springback at the end of the forming process. These deviations are usually too small and local to be detected by discrete measurements of the panel but become visually apparent after the application of paint. As a result, the perceived quality of a panel may become unacceptable and considerable time may be dedicated to minimizing their occurrence through tool modifications. This paper proposes that there are three aspects to the problem. The first is the springback of the panel, the second is the optics of the painted panel, and the third is the ability of human sight to perceive a defect. In particular, it is argued that hollows cause optical distortions that inform the human eye of the presence of a defect. The paper then suggests that signal processing techniques, in particular the wavelet transform, provide a way to relate the geometry of a hollow to the resulting optical distortion. The transform was applied to two physical parts and the paper will discuss the effectiveness of the transform in locating and quantifying the relative severities of the defects that were present.

The Bendability of Ultra High strength Steels

Automotive manufacturers have been reducing the weight of their vehicles to meet increasingly stringent environmental legislation that reflects public demand. A strategy is to use higher strength materials for parts with reduced cross-sections. However, such materials are less formable than traditional grades. The frequent result is increased processing and piece costs. 3D roll forming is a novel and flexible process: it is estimated that a quarter of the structure of a vehicle can be made with a single set of tooling. Unlike stamping, this process requires material with low work hardening rates. In this paper, we present results of ultra high strength steels that have low elongation in a tension but display high formability in bending through the suppression of the necking response.

Analytical methodology for the determination of the flow curves of aluminum and steel alloys using the hydraulic bulge tests

In sheet metal forming simulation, flow curve is a vital ingredient for reliable numerical results. It is more appropriate to determine the flow curve using biaxial stress state tests such as hydraulic bulge test instead of uniaxial test because hardening proceeds to higher strains. With a uniaxial test, higher strains are extrapolated which might lead to incorrect results. The bulge test coupled with the digital image correlation (DIC) system is utilized for the determination of the stress-strain data. In the absence of DIC system, analytical methodologies were used to estimate hardening. Typically such models incorporate a correction factor to achieve correlation to experimental data. An example is the Chakrabarty and Alexander method which uses a correction factor based on the n-value. Here, the Chakrabarty and Alexander approach is modified by utilizing a correction factor based on normal anisotropy. When compared to DIC data, the modified model was found to be predictive of hardening curves for the m...

A novel inspection system for cosmetic defects

The appearance of automotive skin panels creates desirability for a product and differentiates it from the competition. Because of the importance of skin panels, considerable care is taken in minimizing defects such as the hollow defect that occur around door-handle depressions. However, the inspection process is manual, subjective and time-consuming. This paper describes the development of an objective and inspection scheme for the hollow defect. In this inspection process, the geometry of a panel is captured using a structured lighting system. The geometry data is subsequently analyzed by a purpose-built wavelet-based algorithm to identify the location of any defects that may be present and to estimate the perceived severity of the defects without user intervention. This paper describes and critically evaluates the behavior of this physically-based algorithm on an ideal and real geometry and compares its result to an actual audit. The results show that the algorithm is capable of objectively locating and classifying hollow defects in actual panels.

Determining a probabilistic forming limit curve

Forming Limit Curves are surrounded by uncertainty - in particular the uncertainty surrounding the calculation of limit strains from experimental data. The position dependent method outlined in ISO12004-2 is known to make assumptions regarding the behavior of sheet metal at the onset of necking. Recent time dependent methods better utilize measured strain data from digital image correlation (DIC) techniques to determine the onset of localized necking. Both approaches generate a series of forming limit strains which require subsequent interpretation to produce a deterministic forming criterion. By acknowledging the inherent heterogeneous plastic deformation behavior of sheet metal, a new statistical approach to quantifying formability is proposed. Gaussian Mixture Models are used to characterize DIC-measured strain data and to determine both onset of localized necking and the size and location of the neck itself. By avoiding any pre-conceptions regarding the size or characteristics of the localized neck, a more realistic and robust probabilistic forming criterion is attainable.

Subtle cosmetic defects in automotive skin panels

Cosmetic defects such as ‘hollows’ are the result of deviations in a skin panel. These deviations are usually too small and local to be detected by discrete measurements of the panel but become visually apparent after the application of paint. As a result, the perceived quality of a panel may become unacceptable and considerable time may be dedicated to minimizing their occurrence through tool modifications. This paper proposes that there are three aspects to the problem: the springback or buckling of the panel, the optics of the painted panel and the ability of an observer to perceive the defect. In particular, it will be argued that hollows cause optical distortions that inform the human eye of the presence of a defect. The paper then suggests that signal processing techniques, in particular the wavelet transform, provide a simple way of locating and quantifying the severity of these defects. The transform was applied to two physical parts and a simulation model.