Quality engineering of a traction alternator by robust design

Robust design is an engineering methodology for improving productivity during research and development so that high-quality products can be developed and produced quickly and at low cost. A large electrical company was developing traction alternators for a diesel electrical engine. Customer requirement was to obtain very high efficiency which, in turn, was influenced by several design parameters. The usual approach of the 'design-build-test' cycle was considered time-consuming and costly; it used to take anywhere from 4 months to 1 year before finalizing the product design parameters as it involved physical assembly and also testing. Instead, the authors used Taguchi's parameter design approach. This approach took about 8 weeks to arrive at optimum design parameter values; clearly demonstrating the cutting edge of this methodology over the traditional design-build-test approach. The prototype built and tested accordingly gave satisfactory overall performance, meeting and even exceeding customer requirements

Conceptual robustness in simultaneous engineering: An extension of Taguchi's parameter design

Simultaneous engineering processes involve multifunctional teams; team members simultaneously make decisions about many parts of the product-production system and aspects of the product life cycle. This paper argues that such simultaneous distributed decisions should be based on communications about sets of possibilities rather than single solutions. By extending Taguchi's parameter design concepts, we develop a robust and distributed decision-making procedure based on such communications. The procedure shows how a member of a design team can make appropriate decisions based on incomplete information from the other members of the team. More specifically, it (1) treats variations among the designs considered by other members of the design team as conceptual noise; (2) shows how to incorporate such noises into decisions that are robust against these variations; (3) describes a method for using the same data to provide preference information back to the other team members; and (4) provides a procedure for determining whether to release the conceptually robust design or to wait for further decisions by others. The method is demonstrated by part of a distributed design process for a rotary CNC milling machine. While Taguchi's approach is used as a starting point because it is widely known, these results can be generalized to use other robust decision techniques.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45879/1/163_2005_Article_BF01608400.pd

Estimating the Diets of Animals Using Stable Isotopes and a Comprehensive Bayesian Mixing Model

Using stable isotope mixing models (SIMMs) as a tool to investigate the foraging ecology of animals is gaining popularity among researchers. As a result, statistical methods are rapidly evolving and numerous models have been produced to estimate the diets of animals—each with their benefits and their limitations. Deciding which SIMM to use is contingent on factors such as the consumer of interest, its food sources, sample size, the familiarity a user has with a particular framework for statistical analysis, or the level of inference the researcher desires to make (e.g., population- or individual-level). In this paper, we provide a review of commonly used SIMM models and describe a comprehensive SIMM that includes all features commonly used in SIMM analysis and two new features. We used data collected in Yosemite National Park to demonstrate IsotopeR's ability to estimate dietary parameters. We then examined the importance of each feature in the model and compared our results to inferences from commonly used SIMMs. IsotopeR's user interface (in R) will provide researchers a user-friendly tool for SIMM analysis. The model is also applicable for use in paleontology, archaeology, and forensic studies as well as estimating pollution inputs