Fixture Variation Diagnosis of Compliant Assembly Using Sensitivity Matrix

An automotive body is composed of compliant sheet metal parts.Fast and exactly diagnosing variation sources is very important when assembly variations happen.This paper proposes a diagnosis method of multi fixture variations based on the variation model of compliant sheet metal assembly.The assembly variation model is obtained by using the method of influence coefficients(MIC) and considering the manufacturing variations of compliant parts and multi fixture variations.The measurement point variations induced by part manufacturing variations are firstly removed from the measurement data.The variation patterns of multi fixture variations are constructed by column vectors of fixture variation sensitivity matrix.This method is proved to be feasible for exactly diagnosing the fixture variations and has higher diagnosis efficiency than designated component analysis(DCA).

Diagnosis of the Medium-Range Variation of the Subtropical High over the Western Pacific during a Meiyu Process by Three-Dimensional E-P Flux

In this paper, using the daily grid data (2.5 × 2.5) of the ECMWF / WMO, we have computed respectively the three-dimensional wave activity flux in the stages of pre-onset, prevailing and post ending of Meiyu from 1 to 31 July 1982. The potential vorticity field is taken as the physical quantity relating the wave activity flux to the variation of the subtropical high over the Western Pacific. It is found that the three-dimensional wave activity flux is a powerful means for diagnosis of the variation of the subtropical high over the Western Pacific: The region of the subtropical high is just the confluence area of wave energy, whose changes in intensity and range decide the variation of the subtropical high. The confluence of wave energy comes from the monsoon flow in low latitudes, the Meiyu rain belts in middle latitudes and the heating fields on the eastern side of the Qinghai-Xizang Plateau. The relation between these sources and the subtropical high displays the self-adjusting mechanism among members of East-Asia summer monsoon.

Application of Data Mining and Process Knowledge Discovery in Sheet Metal Assembly Dimensional Variation Diagnostic

Sheet metal is widely used on auto-bodies, plane-bodies and metal furniture, etc. For instance, a typical auto-body commonly consists of hundreds of sheet metal stamping parts. Because of its complexity of structure and manufacturing process, auto-bodies inevitably have geometrical variation results from a number of different sources, such as the geometrical variation of stamping parts, the transformation of assembly process parameters and even the improper design concept. As more than 30% quality defects of an auto-body are born from the dimensional deviation of Body-In-White originated during the manufacturing process, effective diagnosis and control of dimensional faults are essential to the continuous improvement of the quality of vehicles. Especially during the period of new car launching or model changing when the assembly process was changed and adjusted frequently. For continuously improving the quality of modern cars, rapid dimensional variation causes identification becomes a challenging but essential work. In this paper, main variation causes of auto-body was firstly been cataloged and analyzed, then, a dimensional variation diagnostic reasoning and decision approach was developed through the combination of data mining and knowledge discovery techniques. This approach is driven by variation pattern identification which can be discovered from the dispersive, isolated massive measured data: Correlation Analysis (CA) and Maximal Tree (MT) methods were applied to extract the large variation group from massive multidimensional measured data, while multivariate statistical analysis (MSA) approach was used to discovery the principle variation pattern. A Decision Tree (DT) approach based on the knowledge of product and assembly process was developed to fulfill the "Hypothesis and Validation" characterized variation causes reasoning procedure. An practical application case with sudden and severe dimension variation on rear end panel in up/down direction was analyzed and successfully solved aided by the devloped variation diagnostic method, which have proved that the approach is effective and efficient.

Variation Analysis and Stability Control for Measurement Process

Based on a two-section measuring method, a data collection sheet is formed. According to the data collected, the variation sources of a measurement process are analyzed and general guidelines for variation diagnosis are suggested. In our previous study, a method is presented to control the deviation of measurement system, but it is not sensitive to mean value variation and mean value drift. In this paper, a simplified data collection scheme via two-section measuring method is introduced to control both variation and center drift of measurement process. Based on this scheme, traditional SPC charts for variation control and EWMA chart for mean value drift are given.