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Description
A P-value based method is proposed for statistical monitoring of various types of profiles in phase II. The performance of the proposed method is evaluated by the average run length criterion under various shifts in the intercept, slope and error standard deviation of the model. In our proposed approach, P-values are computed at each level within a sample. If at least one of the P-values is less than a pre-specified significance level, the chart signals out-of-control. The primary advantage of our approach is that only one control chart is required to monitor several parameters simultaneously: the intercept, slope(s), and the error standard deviation. A comprehensive comparison of the proposed method and the existing KMW-Shewhart method for monitoring linear profiles is conducted. In addition, the effect that the number of observations within a sample has on the performance of the proposed method is investigated. The proposed method was also compared to the T^2 method discussed in Kang and Albin (2000) for multivariate, polynomial, and nonlinear profiles. A simulation study shows that overall the proposed P-value method performs satisfactorily for different profile types.
ContributorsAdibi, Azadeh (Author) / Montgomery, Douglas C. (Thesis advisor) / Borror, Connie (Thesis advisor) / Li, Jing (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2013
Fabrication of Alignment and Chemical Gradient Scaffold for Tendon-Bone Repair using Electrospinning
Description
Heterogeneous musculoskeletal tissues, such as the tendon-bone junction, is crucial for transferring mechanical loading during human physical activity. This region, also known as the enthesis, is composed of a complex extracellular matrix with gradient fiber orientations and chemistries. These different physical and chemical properties are crucial in providing the support that these junctions need in handling mechanical loading of everyday activities. Currently, surgical restorative procedures for a torn enthesis entail a very invasive technique of suturing the torn tendon onto the bone. This results in improper reinjury. To circumvent this issue, one common strategy within tissue engineering is to introduce a biomaterial scaffold which acts as a template for the local damaged tissue. Electrospinning can be utilized to fabricate a fibrous material to recapitulate the structure of the extracellular matrix. Currently electrospinning techniques only allow the creation of scaffold that consists of only one orientation and material. In this work, we investigated a multicomponent, magnetically assisted, electrospinning technique to fabricate a fiber alignment and chemical gradient scaffold for tendon-bone repair
ContributorsLe, Minh (Author) / Holloway, Julianne (Thesis director) / Green, Matthew (Committee member) / W.P. Carey School of Business (Contributor) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The Partition of Variance (POV) method is a simplistic way to identify large sources of variation in manufacturing systems. This method identifies the variance by estimating the variance of the means (between variance) and the means of the variance (within variance). The project shows that the method correctly identifies the variance source when compared to the ANOVA method. Although the variance estimators deteriorate when varying degrees of non-normality is introduced through simulation; however, the POV method is shown to be a more stable measure of variance in the aggregate. The POV method also provides non-negative, stable estimates for interaction when compared to the ANOVA method. The POV method is shown to be more stable, particularly in low sample size situations. Based on these findings, it is suggested that the POV is not a replacement for more complex analysis methods, but rather, a supplement to them. POV is ideal for preliminary analysis due to the ease of implementation, the simplicity of interpretation, and the lack of dependency on statistical analysis packages or statistical knowledge.
ContributorsLittle, David John (Author) / Borror, Connie (Thesis advisor) / Montgomery, Douglas C. (Committee member) / Broatch, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015