• Smart Structures and Systems
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• v.15 no.5
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• pp.1329-1344
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• 2015

The stiffness of a structure is one of several structural signals that are useful indicators of the amount of damage that has been done to the structure. To accurately estimate the stiffness, an equation of motion containing a stiffness parameter must first be established by expansion as a linear series model, a Taylor series model, or a power series model. The model is then used in multivariate autoregressive modeling to estimate the structural stiffness and compare it to the theoretical value. Stiffness assessment for modeling purposes typically involves the use of one of three statistical model refinement approaches, one of which is the efficient Akaike information criterion (AIC) proposed in this paper. If a newly added component of the model results in a decrease in the AIC value, compared to the value obtained with the previously added component(s), it is statistically justifiable to retain this new component; otherwise, it should be removed. This model refinement process is repeated until all of the components of the model are shown to be statistically justifiable. In this study, this model refinement approach was compared with the two other commonly used refinement approaches: principal component analysis (PCA) and principal component regression (PCR) combined with the AIC. The results indicate that the proposed AIC approach produces more accurate structural stiffness estimates than the other two approaches.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.21-28
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• 2015

As film products are increasingly used in a wide range of areas, from producing traditional flexible packaging to high-tech electronic products, a higher level of quality is demanded. Most film products are made in the form of rolled finished goods, therefore, various quality issues related to their shape characteristics must be addressed. The thickness of the film products is one of the most common and important critical-to-quality attributes (CTQs). Particularly, the degree of thickness uniformity is more important than other thickness parameters, because it will be potential causes of many secondary thickness-related quality problems, such as wrinkles or faulty windings. To control the degree of thickness uniformity, the fixed bending region is oneof the most important CTQs to manage. Fixed bending regions are special points in the transverse direction of a rolled product with consistent minute variations of the thickness gap. This paper describes the measurement and analysis of thickness uniformity data, which were performed in a real manufacturing field of biaxial oriented polypropylene (BOPP) film. In previous researches, quality function deployment (QFD) or fault tree analysis were used to find the most critical process attributes out to controlthe CTQ of thickness uniformity. Whereas, this paper uses traditional control charts to find the most critical process attributes out in this problem. In addition, the selection of one of the major critical process attributes (CTPs) that is expected to affect the CTQ of thickness uniformity is also described. The selected critical-to-process attributes are the controlled temperatures along the transverse direction. A dramatic improvement in thickness uniformity was observed when the selected CTPs were controlled.