Elias Montini

Elias Montini
University of Applied Sciences and Arts of Southern Switzerland · Department of Innovative Technologies

Master of Science in Engineering
Researcher at SPS lab, Executive PhD student at POLIMI-DEIB

About

15
Publications
3,920
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96
Citations
Introduction
My research activity has been carried out mainly through research projects funded at national and international level in the context of digitization in manufacturing. The scientific activities address process innovation achieved through factory digitization and adaptive automation to support human and machine interaction. I have experience in design and develop work environments, where humans and machines complement their capacities to optimize performances and improve workers' wellbeing.
Additional affiliations
October 2020 - present
Politecnico di Milano
Position
  • PhD Student
Education

Publications

Publications (15)
Article
In the context of the Industry 4.0 approach, applications and solutions supporting monitoring, simulation, optimisation and decision-making in production systems are exponentially growing. These solutions are commonly built on digital twins, i.e., comprehensive, structured and effective digital representations of the production system and its entit...
Preprint
Today, there are many examples in the literature where digital copies of machines, devices, products or entire production systems are used to improve performance, make predictions and take decisions. However, humans have been so far excluded from these digital representations, even though their influence on process quality, performance and continuo...
Chapter
Full-text available
The need to comply with shorter product life-cycles, diversified market demands and increased global competitiveness is leading to a dramatic increase in production systems requirements in terms of flexibility and responsiveness. Industry 4.0 and its push for digitalisation are becoming a pervasive reality impacting almost each phase of the company...
Research
Full-text available
In the first months of the KITT4SME project, SUPSI, WUT and Ginkgo Analytics collaborate to realise the KITT4SME report 2021. This report includes: - a sum-up of a methodology to assess AI readiness and maturity level in SMEs; - the results obtained through a survey investigating AI adoption that involved 36 European manufacturing companies; - a se...
Conference Paper
Over the last years, the flourishing of the B2B platforms led to the diffusion of business models inspired by the sharing economy. Manufacturing as a service (MaaS) is a paradigm that is often cited in this context, even though literature on the topic is still scarce as well as empirical evidence. This paper contributes to this field discussing the...
Conference Paper
Full-text available
Today literature proposes several models to assess the level of digitisation of a company. However, digitisation includes innumerable elements and aspects that require either models that are too complex to be easily applied by Small and Medium Enterprises (SMEs) or too high-level to provide significant hints for improvement. This paper proposes a m...
Article
Full-text available
Industry 4.0 (I4) as a concept offers powerful opportunities for many businesses. The set of Industry 4.0 technologies is still discussed, and boundaries are not perfectly clear. However, implementation of Industry 4.0 concept becomes strategic principle, and necessary condition for succeeding on turbulent markets. Radio Frequency Identification (R...
Article
Today literature proposes several models to assess the level of digitisation of a company. However, digitisation includes innumerable elements and aspects that require either models that are too complex to be easily applied by Small and Medium Enterprises (SMEs) or too high-level to provide significant hints for improvement. This paper proposes a m...
Article
Over the last years, the flourishing of the B2B platforms led to the diffusion of business models inspired by the sharing economy. Manufacturing as a service (MaaS) is a paradigm that is often cited in this context, even though literature on the topic is still scarce as well as empirical evidence. This paper contributes to this field discussing the...
Article
Full-text available
Multiple and diverse factory digital twins have been proposed in the literature. However, despite the recognized growing importance of workers in smart and autonomous industrial settings, such models still lack or oversimplify human representation. Human digital twins must include human monitoring and behavioural data and models based on psychophys...
Article
Full-text available
This paper proposes an adaptive human-machine collaboration paradigm based on machine learning. Human-machine collaboration requires more than letting humans and machines interact according to fixed rules. A decision-maker is needed to assess production status and to activate adaptations that improve productivity and workers’ well-being. The propos...
Conference Paper
Full-text available
The integration of IoT infrastructures across production systems, together with the extensive digitalisation of industrial processes, are drastically impacting manufacturing value chains and the business models built on the top of them. By exploiting these capabilities companies are evolving the nature of their businesses shifting value proposition...
Conference Paper
The sharing economy emerged in recent years as a model disrupting the approach to traditional B2B and B2C value chains by giving access to underutilized resources at a fraction of the cost to whom cannot or do not want to buy new products. In this context, multi-sided platforms (MSPs) play the pivotal role of providing the environments and the tech...
Conference Paper
An Industry 4.0 framework, showing every possible action towards the complete digitalization of a company both considering strategic and technological aspects, is proposed. The state of the art analysis and re-elaboration allows to coherently integrating many valuable but scattered and narrow contributions into a holistic view covering the followin...
Conference Paper
Manufacturing companies continuously face the challenge of improving their sustainability profile, but one of the major problems with sustainability-centred business approaches relates to the simultaneous pursuit of private and public (society and environment) benefits. Industrial symbiosis (IS) can be a powerful answer to these approaches: IS can...

Network

Cited By

Projects

Projects (5)
Project
BRILLIANT aims to provide to SMEs turn-key solutions that they can leverage to autonomously replicate collaborative work cells in an intuitive and efficient way. BRILLIANT pursues two main objectives towards autonomous uptake of collaborative solutions by SMEs: 1) Developing smart, orchestrated and reconfigurable collaborative workcells to reduce adoption barriers of collaborative solutions for SMEs. For this reason, it introduces solutions for seamless connection of company equipment and digitisation of signals and parameters coming from legacy systems into a cloud platform. At the same time, it provides a stepwise procedure, with guidelines and quantifiable KPIs, for evaluating the potential of current industrial applications towards the adoption of collaborative approaches. 2) Combine flexibility and dexterity of humans with repeatability of cobots towards artisanal manufacturing 4.0.
Project
Artificial intelligence (AI) systems are increasingly improving the automation of production in the manufacturing sector. But in order for these systems to be trusted and applicable when replacing human tasks in dynamic operation, they need to be safe and adjustable – to react to different situations, security threats, unpredictable events or specific environments. The EU-funded STAR project will rise to this challenge by designing new technologies to enable the implementation of standard-based, secure, safe, reliable and trusted human-centric AI systems in manufacturing environments. The project will aim to research and integrate leading-edge AI technologies like active learning systems, simulated reality systems, explainable AI, human-centric digital twins, advanced reinforcement learning techniques and cyber-defence mechanisms, to allow the safe deployment of sophisticated AI systems in production lines. (Grant agreement ID: 956573)
Project
KITT4SME specifically targets European SMEs and mid-caps to provide them with scope-tailored and industry-ready hardware, software and organisational kits, delivered as a modularly customisable digital platform, that seamlessly introduce artificial intelligence in their production systems. Uptake of the resulting packages and of the provided services is strongly supported by the clear characterisation and market readiness of the individual components as well as by the platform grounding on the already established RAMP marketplace. Leverage on the network of Digital Innovation Hubs, four of which are represented in the consortium, ensures that KITT4SME are widely distributed to a wide audience of companies in Europe. Seamless adoption of the customised kits is made possible by a Powered by FIWARE infrastructure that flawlessly combine factory systems (such as MES and ERP), IoT sensors and wearable devices, robots, collaborative robots and other factory data sources with functional modules capable to trigger data-driven value creation. https://cordis.europa.eu/project/id/952119/it