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The identification and translation of customer needs early in the design process is a major challenge for product design researchers. Some needs are explicit and customers can state them very clearly. Other needs are implicit, so customers cannot express them, e.g., those pertaining to the affective and emotional sphere. In this work, we describe the methods most commonly used to capture explicit...
In this chapter, an original design strategy for product innovation is presented. This strategy is based on a continuous innovation process and takes advantages of both emotional design methodologies and participative design tools in virtual reality (VR). It combines techniques for user need identification and virtual reality experiments to simulate user-product interaction. This original combination...
From the early development phases of a new industrial product, realistic simulations can be performed in a virtual environment to study the human-machine interaction. In a virtual lab, it is possible to perform experiments to assess the ergonomics of the new product using mannequins simulating the human body, and to deal with the problem of anthropometric variation.
This chapter is about experiments for quality improvement and the innovation of products and processes performed by computer simulation. It describes familiar methods for creating surrogate models of simulators (emulators), with particular reference to Kriging interpolation, and some new ways of fitting the models to the simulated data.
The need to assess the reliability of new automotive products in a timely manner compels manufacturers to make use of early failure warranty data. However, the narrow observation period and the moderate sizes of early warranty data sets result in reliability estimates that are not very accurate. Nevertheless, when a new product is not revolutionary but instead the result of making improvements to...
In this chapter, a stochastic process-based approach is adopted to formulate the reliability function for cylinder liners of diesel engines used for marine propulsion, which fail when their wear exceeds a specified limit. In order to describe the wear process, three different stochastic models are proposed. The first two are based on age-dependent processes, namely a shock model with independent nonstationary...
An alternative title for this chapter could be “Innovation for Statistics”, which would be equally appropriate to illustrate its contents. In fact, the chapter shows how to perform the innovation process approach in order to fulfill a scientific research need in a specific application area. More specifically, this chapter describes the incremental development of a new control chart of the Weibull...
In recent decades, the literature on technology management has proposed S-curves as promising tools for analyzing the life-cycle of technological innovation in order to support company strategies and policies. Nevertheless, the scant attention devoted to the analytical foundations of the S-curve model has limited its capacity to actually model the performance of technological innovation.
The selection of design points is mandatory when the goal is to study how the observed response varies upon changing the set of input variables. In physical experimentation, the researcher is asked to investigate a number of issues to gain valuable inferences. Design of experiments (D.o.E.) is a helpful tool for achieving this goal. Unfortunately, designing a computer experiment (CE), used as a surrogate...
This chapter describes an interesting case of process innovation generated by transferring two statistical technologies from their native application fields to a different one. The technologies are prediction by Kriging models and sequential experiments, originally developed for geostatistics applications and clinical trials, respectively. The combination of the two, i.e., sequential experiments driven...
Technical innovation in industry can massively benefit from an investigation strategy which properly combines experiments in the field with experiments on a simulation model of the product or the process. However, a methodological frame-work for the effective integration of the two kinds of investigation is still missing. On the one hand, simulation and lab tests are routinely used together in R&D...
This chapter deals with the problem of assessing the quality of land-cover databases, since only high-quality products are useful for gaining knowledge about and managing territory. After a brief analysis of the main aspects of quality control and validation of land-cover databases, the main concepts of statistical quality control methods are recalled in order to show how some quality control procedures...
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