Nathan Ray Soderborg

System function and architecture: OPM-based definitions and operational templates

This framework for modeling and conceptually representing a systems specification identifies essential objects and processes while minimizing ambiguity in functional and architectural requirements.

Neural network application to comprehensive engine diagnostics

The authors examine the application of trainable classification systems to the problem of diagnosing faults in engines at the manufacturing plant. It is demonstrated how a combination of conventional statistical processing methods and neural networks can be combined to create a classifier system for engine diagnostics. The most significant computational effort is required for the principal component analysis and to properly develop the hard-shell classifiers using data sets augmented with Monte Carlo methods. Once these procedures are carried out, the application of neural networks to the data set to obtain the trainable classifier is quite straightforward.<<ETX>>

Compound Noise: Evaluation as a Robust Design Method

This paper evaluates compound noise as a robust design method. Application of compound noise as a robust design method leads to a reduction in experimental effort. The compound noise strategy was applied to two types of situation: the first type has been described with active effects up to two-factor interactions and the second type has been described with effects up to three-factor interactions. These two situations are illustrated with help of case studies. The paper provides theoretical justification for the effectiveness of the compound noise strategy as formulated by Taguchi and Phadke. For example, we found that the compound noise strategy is very effective for systems which exhibit effect sparsity. This paper gives an alternative procedure to formulate a compound noise, distinctly different from Taguchis formulation. The alternative method requires less information to formulate compound noise as compared to Taguchis formulation. Overall, the paper studies the effectiveness of such an alternative formulation, outlines scenarios where compound noise as a robust design method can be effectively used and gives alternative strategies for the systems on which compound noise cannot be effective. Copyright

Model of IIHS side impact torso response measures using transfer function equations

Vehicle to vehicle crash compatibility is becoming an increasingly more important consideration during vehicle safety development due to the increasing numbers of SUVs and pickups in the vehicle fleet. According to the Insurance Institute for Highway Safety (IIHS), their side impact crash test represents what happens when a passenger vehicle is struck by a pickup truck or SUV. The IIHS side impact test measures 37 different response criteria using an instrumented 5 th percentile female SID-lls ATD (anthropomorphic test device) in driver and left rear passenger seats. These measures are grouped into head and neck, torso, and pelvis and left leg regions. This paper will describe the development of transfer function equation models to assess the performance of design countermeasures by comparing the response measures of the torso region of the body. This transfer function model will be a useful tool in determining the significance of certain design parameters and making performance comparisons of design proposals. This tool will also allow safety engineers to experiment with various designs in the early stages of the development of the side impact countermeasures.

Streamlining robust parameter design efforts

This paper proposes and evaluates techniques to streamline robust parameter design, that is, to make products robust using fewer experimental runs. The evaluations are conducted using a combination of hierarchical probability models and six case studies. A procedure is presented for choosing among methods to balance the needs for speed and accuracy. Simulations of robust parameter design being deployed in this way suggest that the proposed approach gives good results and reduces sensitivity of the design process to the fidelity of a priori judgments of which subsystems need robustness improvement.