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In this work, an efficient and easy statistical method to find an equivalent discrete distribution for a continuous random variable (r.v.) is proposed. The proposed method is illustrated by applying it to the treatment of the anthropometrical noise factors in the context of Robust Ergonomic Design (RED; Lanzotti 2006; Barone S. and Lanzotti A., 2007).

Higher efficiency and effectiveness of Research & Development phases can be attained using advanced statistical methodologies. In this work statistical methodologies are combined with a deterministic approach to engineering design. In order to show the potentiality of such integration, a simple but effective example is presented. It concerns the problem of optimising the performance of a paper helicopter. The desgin of this simple device is not new in quality engineering literature and has been mainly used for educational purposes. Taking full advantage of fundamental engineering knowledge, an aerodynamic model is originally formulated in order to describe the fligh of the helicopter. Screening experiments were necessary to get first estimates of model parameters. Subsquently, deterministic evaluations based on this model were necessary to set up further experimental phases needed to search for a better design. Thanks to this integration of statistical and deterministic phases, a significant performance improvement is obtained. Moreover, the engineering knowledge turns out to be developed since an explanation of the “why” of better performances, although approximate, is achieved. The final design solution is robust in a broader sense, being both validated by experimental evidence and closely examined by engineering knoweldge.

This paper aims at defining a structured process of continuous innovation in the product concept development phase by a statistical‐based Kansei engineering (KE) approach. It consists in the identification of quality elements satisfying both functional and emotional user needs, i.e. the total quality elements.

The approach is developed integrating results from Kano and KE analysis. Three statistical methods considered to be suitable for KE study, are used: supersaturated design for concept configuration, ordinal logistic regression for data analysis, and EVA method for quality evaluation of the optimal concept. These methods are compared with the most used ones in KE regarding their efficacy, efficiency and easiness of use. An innovative procedure to exhibit concepts in a KE session is also presented. It uses the abstraction and association idea principles to elicit users' grade of agreement for a particular Kansei word.

The proposed approach is fully exploited through a case study on train interior design, developed in a virtual reality (VR) laboratory. The evaluation of comfort improvements obtained by means of a new handle and handrail design is carried on with expert users in VR. A consistent increase of a quality index, by using the defined approach, was obtained.

This work aims at contributing to the conception of new product solutions, which are appealing and saleable. The availability of virtual reality technologies and software capable to manage complex statistical analyses, will concretely aid designers and engineers in the ideation of high‐emotional‐quality products, which can be helpful for innovative enterprises to maintain and even increase their market position.

This study aims to quantify the ultimate tensile strength and the nominal strain at break (ɛ_f) of printed parts made from polylactic acid (PLA) with a Replicating Rapid prototyper (Rep-Rap) 3D printer, by varying three important process parameters: layer thickness, infill orientation and the number of shell perimeters. Little information is currently available about mechanical properties of parts printed using open-source, low-cost 3D printers.

A computer-aided design model of a tensile test specimen was created, conforming to the ASTM:D638. Experiments were designed, based on a central composite design. A set of 60 specimens, obtained from combinations of selected parameters, was printed on a Rep-Rap Prusa I3 in PLA. Testing was performed using a JJ Instruments – T5002-type tensile testing machine and the load was measured using a load cell of 1,100 N.

This study investigated the main impact of each process parameter on mechanical properties and the effects of interactions. The use of a response surface methodology allowed the proposition of an empirical model which connects process parameters and mechanical properties. Even though results showed a high variability, additional ideas on how to understand the impact of process parameters are suggested in this paper.

On the basis of experimental results, it is possible to obtain practical suggestions to set common process parameters in relation to mechanical properties. Experiments discussed in the present paper provide a variety of data and insight regarding the relationship among the main process parameters and the stiffness and strength of fused deposition modeling-printed parts made from PLA. In particular, this paper underlines the shortage in existing literature concerning the impact of process parameters on the elastic modulus and the strain to failure for the PLA. The experimental data produced show a good degree of compliance with analytical formulations and other data found in literature.

This paper aims to present a survey concerning the accuracy of thermoplastic polymeric parts fabricated by additive manufacturing (AM). Based on the scientific literature, the aim is to provide an updated map of trends and gaps in this relevant research field. Several technologies and investigation methods are examined, thus giving an overview and analysis of the growing body of research.

Permutations of keywords, which concern materials, technologies and the accuracy of thermoplastic polymeric parts fabricated by AM, are used for a systematic search in peer-review databases. The selected articles are screened and ranked to identify those that are more relevant. A bibliometric analysis is performed based on investigated materials and applied technologies of published papers. Finally, each paper is categorised and discussed by considering the implemented research methods.

The interest in the accuracy of additively manufactured thermoplastics is increasing. The principal sources of inaccuracies are those shrinkages occurring during part solidification. The analysis of the research methods shows a predominance of empirical approaches. Due to the experimental context, those achievements have consequently limited applicability. Analytical and numerical models, which generally require huge computational costs when applied to complex products, are also numerous and are investigated in detail. Several articles deal with artificial intelligence tools and are gaining more and more attention.

The cross-technology survey on the accuracy issue highlights the common critical aspects of thermoplastics transformed by AM. An updated map of the recent research literature is achieved. The analysis shows the advantages and limitations of different research methods in this field, providing an overview of research trends and gaps.