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Data center availability is critical considering the explosive growth in Internet services and people's dependence on them. Furthermore, in recent years, sustainability has become important. However, data center designers have little information on the sustainability impact of data center availability architectures. In this paper, we present an approach to estimate the sustainability impact of such architectures. Availability is computed using Stochastic Petri Net (SPN) models while an exergy-based lifecycle assessment (LCA) approach is used for quantifying sustainability impact. The approach is demonstrated on real life data center power infrastructure architectures. Five different architectures are considered and initial results show that quantification of sustainability impact provides important information to a data center designer in evaluating availability architecture choices.

Nowadays, companies must embrace the concept of Digitalization and Industry 4.0 to remain competitive in the market. The reality is that most of them do not have their industrial devices prepared to access their data on a real-time basis. As most companies do not have the possibility to renew all their legacy devices and because these devices are still very productive, a retrofit solution is of high interest. In this work, we propose an affordable procedure that allows data collection and monitoring of older injection machines, as a contribution towards legacy devices integration. The developed system neither requires additional proprietary modules, nor contractual annual fees for different devices, sharing the same interface across different machine manufacturers and also contributing to uniform data collection. Evaluation was carried out in a real shop floor, monitoring the injection parameters for different machine models, validating the effectiveness of the developed system.

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Purpose: to evaluate the reliability of the maximum phonation time (MPT) and Vital Capacity intra and inter-examiner, by means of the single-breath counting test (CT) and the sustained /a/ phoneme, and the slow vital capacity (SVC). Methods: a reliability study carried out in three groups of healthy individuals, each group with 30 volunteers, allocated according to age. SVC was measured using a spirometer, while the MPT was assessed by the phoneme /a/ and CT. The data were analyzed using SPSS version 20.0. Initially, descriptive statistics were used and for data reliability, the intraclass correlation coefficient (ICC). Results: the Intraclass Correlation Coefficients (ICC) were considered excellent, with significant results above 0.92 for SVC and greater than 0.79 for CT and phoneme /a/. Regarding the inter-examiner evaluation, the ICCs were also significant for both SVC with values greater than 0.96, and for CT and the phoneme /a/ with values greater than 0.85. The error inherent in the technique was assessed using the standard error of the measurement for intra and inter-examiner analyses with values ranging from 1.79 to 3.29 for phoneme /a/, 3.20 to 6.58 for CT and 65, 05 to 206.73 for SVCml. Conclusion: phonation techniques with the phoneme /a/ and CT, as well as SVC, have an excellent reliability, due to intra and inter-examiner agreement measures.