The full potential of predictive maintenance has not yet been utilised. Current solutions focus on individual steps of the predictive maintenance cycle and only work for very specific settings. The overarching challenge of predictive maintenance is to leverage these individual building blocks to obtain a framework that supports optimal maintenance and asset management. The PrimaVera project has identified four obstacles to tackle in order to utilise predictive maintenance at its full potential: lack of orchestration and automation of the predictive maintenance workflow, inaccurate or incomplete data and the role of human and organisational factors in data-driven decision support tools. Furthermore, an intuitive generic applicable predictive maintenance process model is presented in this paper to provide a structured way of deploying predictive maintenance solutions.
MULTIFILE
The full potential of predictive maintenance has not yet been utilised. Current solutions focus on individual steps of the predictive maintenance cycle and only work for very specific settings. The overarching challenge of predictive maintenance is to leverage these individual building blocks to obtain a framework that supports optimal maintenance and asset management. The PrimaVera project has identified four obstacles to tackle in order to utilise predictive maintenance at its full potential: lack of orchestration and automation of the predictive maintenance workflow, inaccurate or incomplete data and the role of human and organisational factors in data-driven decision support tools. Furthermore, an intuitive generic applicable predictive maintenance process model is presented in this paper to provide a structured way of deploying predictive maintenance solutions.
MULTIFILE
In cases of sexual assault, the interpretation of biological traces on clothing, and particularly undergarments, may be complex. This is especially so when the complainant and defendant interact socially, for instance as (ex-)partners or by co-habitation. Here we present the results from a study where latent male DNA on female worn undergarments is recovered in four groups with different levels of male-female social interaction. The results conform to prior expectation, in that less interaction tend to result in less male DNA on undergarments. We explore the use of these experimental data for evaluative reporting given activity level propositions in a mock case scenario. We show how the selection of different populations to represent the social interaction between complainant and defendant may affect the strength of the evidence. We further show how datasets of limited size can be used for robust activity level evaluative reporting.
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