The construction of interpretable Takagi-Sugeno (TS) fuzzy models by means of clustering is addressed. First, it is shown how the antecedent fuzzy sets and the corresponding consequent parameters of the TS model can be derived from clusters obtained by the Gath-Geva (GG) algorithm. To preserve the partitioning of the antecedent space, linearly transformed input variables can be used in the model. This may, however, complicate the interpretation of the rules. To form an easily interpretable model that does not use the transformed input variables, a new clustering algorithm is proposed, based on the expectation-maximization (EM) identification of Gaussian mixture models. This new technique is applied to two well-known benchmark problems: the MPG (miles per gallon) prediction and a simulated second-order nonlinear process. The obtained results are compared with results from the literature.

The fast development of smart sensors and wearable devices has provided the opportunity to develop intelligent operator workspaces. The resultant Human-Cyber-Physical Systems (H-CPS) integrate the operators into flexible and multi-purpose manufacturing processes. The primary enabling factor of the resultant Operator 4.0 paradigm is the integration of advanced sensor and actuator technologies and communications solutions. This work provides an extensive overview of these technologies and highlights that the design of future workplaces should be based on the concept of intelligent space.

Countries have to work out and follow tailored strategies for the achievement of their Sustainable Development Goals. At the end of 2018, more than 100 voluntary national reviews were published. The reviews are transformed by text mining algorithms into networks of keywords to identify country-specific thematic areas of the strategies and cluster countries that face similar problems and follow similar development strategies. The analysis of the 75 VNRs has shown that SDG5 (gender equality) is the most discussed goal worldwide, as it is discussed in 77% of the analysed Voluntary National Reviews. The SDG8 (decent work and economic growth) is the second most studied goal, With 76 %, while the SDG1 (no poverty) is the least focused goal, it is mentioned only in 48 % of documents and the SDG10 (reduced inequalities) in 49 %. The results demonstrate that the proposed benchmark tool is capable of highlighting what kind of activities can make significant contributions to achieve sustainable developments.

The application of white box models in digital twins is often hindered by missing knowledge, uncertain information and computational difficulties. Our aim was to overview the difficulties and challenges regarding the modelling aspects of digital twin applications and to explore the fields where surrogate models can be utilised advantageously. In this sense, the paper discusses what types of surrogate models are suitable for different practical problems as well as introduces the appropriate techniques for building and using these models. A number of examples of digital twin applications from both continuous processes and discrete manufacturing are presented to underline the potentials of utilising surrogate models. The surrogate models and model-building methods are categorised according to the area of applications. The importance of keeping these models up to date through their whole model life cycle is also highlighted. An industrial case study is also presented to demonstrate the applicability of the concept.