Tolerance optimization with statistical approach in the CAT environment

Nowadays, product development in all its phases plays a fundamental role in the industrial chain. The need for a company to compete at high levels, the need to be quick in responding to market demands and therefore to be able to engineer the product quickly and with a high level of quality, has led to the need to get involved in new more advanced methods/ processes. In recent years, we are moving away from the concept of 2D-based design and production and approaching the concept of Model Based Definition. By using this approach, increasingly complex systems turn out to be easier to deal with but above all cheaper in obtaining them. Thanks to the Model Based Definition it is possible to share data in a lean and simple way to the entire engineering and production chain of the product. The great advantage of this approach is precisely the uniqueness of the information. In this specific thesis work, this approach has been exploited in the context of tolerances with the aid of CAD / CAT software. Tolerance analysis or dimensional variation analysis is a way to understand how sources of variation in part size and assembly constraints propagate between parts and assemblies and how that range affects the ability of a project to meet its requirements. It is critically important to note how tolerance directly affects the cost and performance of products. Worst Case Analysis (WCA) and Statistical analysis (RSS) are the two principal methods in DVA. The thesis aims to show the advantages of using statistical dimensional analysis by creating and examining various case studies, using PTC CREO software for CAD modeling and CETOL 6σ for tolerance analysis. Moreover, it will be provided a comparison between manual and 3D analysis, focusing the attention to the information lost in the 1D case. The results obtained allow us to highlight the need to use this approach from the early stages of the product design cycle.

Transgenerational effects of temperature on egg and larval development in Cyprinodon variegatus

Transgenerational plasticity (TGP), a type of maternal effect, occurs when the environment experienced by one or both the parents prior to fertilization directly translates, without changing DNA sequences, into changes in offspring reaction norms. Evidence of such effects has been found in several traits throughout many phyla, and, although of great potential importance - especially in a time of rapid climate change - TGP in thermal growth physiology had never been demonstrated for vertebrates until the first experiment on thermal TGP in sheepshead minnows, who, given sufficient time, adaptively program their offspring for maximal egg viability and growth at the temperature experienced before fertilization. This study on sheepshead minnows from South Carolina and Connecticut investigates how population, parent temperature, and offspring temperature affect egg production, size, viability, larval survival and growth rates, whether these effects provide evidence of TGP, and whether and how they vary with length of exposure time (5, 12, 19, 26, 33 and 43 days) of the parents to the new experimental temperatures of either 26°C or 32°C. Several results are consistent with those obtained in the previous TGP study, which outline a sequence of events consisting of an initial adjustment period to the new temperatures, in which egg production decreases and no signs of TGP are present, followed by a shift to TGP (towards 26-33 days of exposure) in which parents start to produce more eggs which are better adapted to the new thermal environment. Other results present new information, such as signs of TGP in the parent temperature effect on egg sizes already around 20 days of exposure. The innovative idea of populations being able to adapt to rapidly shifting environments through non-genetic mechanisms such as TGP opens new possibilities of survival of species and will have important implications on ecology, physiology, and contemporary evolution.