Towards the Augmentation of Digital Twin Performance.

Digital Twin (DT) aims to provide industrial companies with an interface to visualize, analyze, and simulate the production process, improving overall performance. This paper proposes to extend existing DT by adding a complementary methodology to make it suitable for process supervision. To implement our methodology, we introduce a novel framework that identifies, collects, and analyses data from the production system, enhancing DT functionalities. In our case study, we implemented Key Performance Indicators (KPIs) in the immersive environment to monitor physical processes through cyber representation. First, a review of the Digital Twin (DT) allows us to understand the status of the existing methodologies as well as the problem of data contextualization in recent years. Based on this review, performance data in Cyber-Physical Systems (CPS) are identified, localized, and processed to generate indicators for monitoring machine and production line performance through DT. Finally, a discussion reveals the difficulties of integration and the possibilities to respond to other major industrial challenges, like predictive maintenance.

Smartphone LiDAR Data: A Case Study for Numerisation of Indoor Buildings in Railway Stations.

The combination of LiDAR with other technologies for numerisation is increasingly applied in the field of building, design, and geoscience, as it often brings time and cost advantages in 3D data survey processes. In this paper, the reconstruction of 3D point cloud datasets is studied, through an experimental protocol evaluation of new LiDAR sensors on smartphones. To evaluate and analyse the 3D point cloud datasets, different experimental conditions are considered depending on the acquisition mode and the type of object or surface being scanned. The conditions allowing us to obtain the most accurate data are identified and used to propose which acquisition protocol to use. This protocol seems to be the most adapted when using these LiDAR sensors to digitise complex interior buildings such as railway stations. This paper aims to propose: (i) a methodology to suggest the adaptation of an experimental protocol based on factors (distance, luminosity, surface, time, and incidence) to assess the precision and accuracy of the smartphone LiDAR sensor in a controlled environment; (ii) a comparison, both qualitative and quantitative, of smartphone LiDAR data with other traditional 3D scanner alternatives (Faro X130, VLX, and Vz400i) while considering three representative building interior environments; and (iii) a discussion of the results obtained in a controlled and a field environment, making it possible to propose recommendations for the use of the LiDAR smartphone at the end of the numerisation of the interior space of a building.

Biological Practices and Fields, Missing Pieces of the Biomimetics' Methodological Puzzle.

Facing current biomimetics impediments, recent studies have supported the integration within biomimetic teams of a new actor having biological knowledge and know-how. This actor is referred to as the "biomimetician" in this article. However, whereas biology is often considered a homogenous whole in the methodological literature targeting biomimetics, it actually gathers fundamentally different fields. Each of these fields is structured around specific practices, tools, and reasoning. Based on this observation, we wondered which knowledge and know-how, and so biological fields, should characterize biomimeticians. Following the design research methodology, this article thus investigates the operational integration of two biological fields, namely ecology and phylogenetics, as a starting point in the establishment of the biomimetician's biological tools and practices. After a descriptive phase identifying specific needs and potential conceptual bridges, we presented various ways of applying biological expertise during biomimetic processes in the prescriptive phase of the study. Finally, we discussed current limitations and future research axes.

Standardised evaluation of medicine acceptability in paediatric population: reliability of a model.

OBJECTIVES: Our novel tool to standardise the evaluation of medicine acceptability was developed using observational data on medicines use measured in a paediatric population included for this purpose (0-14 years). Using this tool, any medicine may be positioned on a map and assigned to an acceptability profile. The present exploration aimed to verify its statistical reliability. METHODS: Permutation test has been used to verify the significance of the relationships among measures highlighted by the acceptability map. Bootstrapping has been used to demonstrate the accuracy of the model (map, profiles and scores of acceptability) regardless of variations in the data. Lastly, simulations of enlarged data sets (×2; ×5; ×10) have been built to study the model's consistency. KEY FINDINGS: Permutation test established the significance of the meaningful pattern identified in the data and summarised in the map. Bootstrapping attested the accuracy of the model: high RV coefficients (mean value: 0.930) verified the mapping stability, significant Adjusted Rand Indexes and Jaccard coefficients supported clustering validity (with either two or four profiles), and agreement between acceptability scores demonstrated scoring relevancy. Regarding enlarged data sets, these indicators reflected a very high consistency of the model. CONCLUSIONS: These results highlighted the reliability of the model that will permit its use to standardise medicine acceptability assessments.

Standardized method to assess medicines' acceptability: focus on paediatric population.

OBJECTIVES: The purpose of this article was to present an original standardized tool assessing the medicine's acceptability whichever their characteristics and the patient features. METHODS: An acceptability map was built with objective measures from medicine use assessments collected in real-life conditions. Multiple correspondence analysis (MCA) was used for the mapping process. Hierarchical classification on the principal components (HCPC) of the MCA was performed for the clustering process corresponding to distinct acceptability profiles. KEY FINDINGS: The results presented here focus on 234 evaluations issued from the paediatric population and gathered in four clusters: 'well-accepted' (50%), 'accepted' (19%), 'poorly accepted' (25%) and 'not accepted' medicines (6%). The first one was characterized by a dose fully taken, in a short time, with a patient's positive reaction; the second by a longer administration time, a neutral reaction and the use of methods to achieve administration (reward, divided dose). Differentiation between the two last clusters was, respectively, originated by a required dose partially taken or not taken. CONCLUSIONS: The acceptability profile of each medicine can be evaluated with the map position of the related patient's assessments barycentre. This tool should satisfy expectations in terms of methods for appropriate acceptability evaluation and standardized comparison among medicines.

Anticipating the use of future things: towards a framework for prospective use analysis in innovation design projects.

Anticipation of future product use is a persistent issue in User-Centered Design. In this paper, we argue that one obstacle to early integration of use analysis in innovation design is overreliance on retrospective use analysis, i.e. that which is based on clear references to existing products or activities. In contrast, innovation design projects are full of uncertainty, leading to a need for prospective analysis. After having described some limitations of prospective use analysis, we contend that creativity tools may be used to assist the anticipation of future product use, by allowing designers to approach the variability of situations of future use in a structured manner rather than by "muddling through". We illustrate the expected benefits of this approach with two case studies, and describe some prospects for future research and practice in ergonomics.