The abstracts of all oral and poster presentations, in most instances accompanied by full papers and/or presentation slides, are available on the ENBIS web site (www.enbis.org).Once again the ENBIS special issue covers theoretical and methodological advances in business and industrial statistics and shows the variety of topics that characterize the ENBIS community.Taking advantage of the coincidence in place and time with the XXI IMEKO World Congress the ENBIS 15 was connected to it; this specially issue, features two papers related to measurement. Akkerhuis and de Mast 1 consider the problem of measurement error of nominal measurements when there is no 'gold standard' and provide a method to estimate systematic and random error components, and Berni and Nikiforova 2 suggest a novel approach for analyzing interlaboratory comparison data based on an error measurement model in order to consider both the measured values and their uncertainty.Postelnicu, Raviv and Ben-Gal 3 propose a method to minimize the expected number of clicks required to reach a website page. The method proposed provides very good results with a relatively low computational cost.Motivated by test data from video images coming from drones, Avery, Orndorff, Robinson and Freeman 4 investigate the regularization for continuously observed covariated that resembles step functions.Damblin, Keller, Barbillon and Pasanisi 5 propose a Bayesian method to evaluate and finally select computer codes modeling complex physical systems. Another paper dealing with the modelization of Computer Experiments is Meta-models in Computer Experiments: Kriging vs Artificial Neural Networks by Vicario, Craparotta and Pistone. 6 The authors compare the performances of two of the most popular metamodels, Kriging (using two different approaches, a parametric one and a non-parametric based on experimental variograms, in the estimation of the correlation structure) and Artificial Neural Network, in order to state which one guarantees higher accuracy at a satisfactory cost in Computational Fluid Dynamics experiments providing energy loss in Low Pressure Turbines, for the aim of reducing the specific fuel consumption.The goal of Browne, Iooss, Le Gratiet, Lonchampt and Remy 7 in Stochastic simulators based optimization by Gaussian process metamodelsApplication to maintenance investments planning issues is the optimization of industrial asset management strategies. They build a metamodel of the stochastic simulator for assessing the indicator of interest (Net Present Value). In the paper the quantile function of the stochastic simulator is emulated. In a Gaussian process framework, an adaptive design method (QFEI) is defined by extending the well-known EGO algorithm, for the aim of obtaining an 'optimal' solution using a small number of simulator runs regarding the case study considered.Fasso, Toccu and Magno, 8 motivated by a multiple profile monitoring problem of a steam sterilizer, introduce general multifunctional EWMA control charts. Another paper dealing with the process m...