Silvia Menato

An integrative approach improves sustainability impacts of innovation. An empirical study

A review of recent literature in the field indicates there is an increasing interest in improving sustainability performances of manufacturing. The integrated innovation of product, process and supply chain can be a promising way to improve economic, social and environmental performances of manufacturing enterprises, but there is still a lack of empirical evidence on the topic. This paper compares the sustainability-related performances of three different states, which a unique business context went through. The final state, a small-sized mini-factory for the local transformation of sheep wool, outperforms the other (more traditional) configurations in terms of social end economic impacts, with just partial advantages in terms of environmental performances.

Empowering widespread shoe personalization via a 3D foot scanning App

Unceasing market request for personalization of consumer goods calls for more and more flexible production technologies, and for increasingly reliable means to gather precise pictures of what each customer desires. Fitting is especially crucial to accomplish personalization in footwear, where the prevailing of manual operations makes production flexibility quite easy, but the close interaction between shoe and foot requires extremely precise knowledge of the body part which is being gloved. In a still ongoing research project, the authors are developing a powerful smartphone App to perform a 3D scanning of a foot, whose preliminarily registered performances are here presented and discussed. The solution is expected to establish a new standpoint in the trade-off between the level of precision of the gathered data and the ubiquity and accessibility of the scanning functionality, thus empowering a widespread best-matched fit personalization in the footwear market.

Human-centric data model and data integration platform enabling personalized product service systems for healthcare

This work describes a Human-Centric Data Model (HCDM), designed for easily ensuring a high level of scalability in order to be applied in many different scenarios, dealing with the production of personalized goods and the development of enhanced services for improving the wellbeing of specific target groups of people. The HCDM is integrated into a comprehensive system architecture, going from sensors development to services provision. The characteristics of the proposed HCDM have been defined accordingly to the objectives of the product service systems to be offered as well as to the nature of the available sensors. A particular attention has been devoted to the data modeling, storage and analysis in order to ensure efficient personalized real-time synchronous services directly managed by the user while fostering the development of asynchronous services involving a wide variety of external service providers.