and Management
Technology, Innovation
Applied research doctoral scholarships: 28 scholarships for innovative PhDs
The projects
• Development of digital tools for machine configuration and machining process optimization
• Dynamic human-machine interaction systems using real-time and persistent data collected from various wearable devices to achieve detailed information concerning physical and cognitive status of the industrial operators
• New skills and tools to support the servitization journey of SMEs
• Development of artificial intelligence-based tools to support technical support
• Quantitative decision support methodologies in asset management
• Development of smart sensors with a view to Industry 5.0 and Human Manufacturing
• Development of a technology mapping model of Bergamo area companies
Development of digital tools for machine configuration and machining process optimization
Company: Gildemeister Italiana S.p.A.
Tutor: Gianluca D’Urso
As part of Gildemeister Italiana’s growth strategies, we highlight the intention to develop products based on modular platforms for defining the configuration of multiprocess machines.
In other words, the intention is to move from the concept of a customer who has to adapt his process to a machine available in the catalog to a customer who can commission a machine with a high degree of customization.
While this approach provides a great deal of freedom/flexibility in configuration as well as process adaptation, the need for a kind of “Navigation System” to support and guide supplier and customer in evaluating optimal strategies emerges.
In fact, by providing customers with a wide range of machine configurations, they may be unprepared; having many more configuration possibilities i.e., many more degrees of freedom or “free” parameters, choosing and comparing possible combinations could be extremely complex.
In order to prevent a solution with great potential from becoming a limitation, this new approach will have to be accompanied by software tools that can support customers in machine configuration.
Based on the above, this research project aims to develop a tool to digitize, simulate and optimize the main aspects of a machining process and its application to different machines or configurations.
Once the part to be machined, the operations and the technological sequence have been defined, the tool should automatically provide support in the distribution of the work cycle on the different operating units, allowing the optimization of the configuration and the balancing of the work cycle itself.
Dynamic
human-machine
interaction systems
using real-time and persistent data collected from various wearable devices to achieve detailed information concerning physical and cognitive status of the industrial operator
Company: Consorzio Intellimech
Tutor: Daniele Regazzoni
Intellimech is a no-profit private research consortium promoting the collaboration of companies of different sizes and from various industrial domains.
One of the main issues of the Industry 5.0 paradigm concerns the central role of people in industrial contexts. Indeed, Industry 5.0 envisaged a business model characterized by the cooperation between machines and human beings.
Such a model requires rethinking and innovating the information management systems and tools, often inadequate to the complexity of the current socio-technological environments.
The ongoing technological changes are accompanied by the need to define digital innovation paths that are socially sustainable, putting technology at the service of humans positioned at the center of the entire production process.
Different Intellimech partners are interested to deep explore these fields:
• technologies for the personalization of work environments by including in the model the specific physical and cognitive abilities and skills of the workers, taking account of their roles, duties and needs;
• methodologies and technologies for managing human-machine interaction by promoting a flexible and adaptable solution for the development of numerous industrial applications, from new intelligent and adaptive interfaces, to human-robot collaboration;
• methodologies and technologies for optimizing the cognitive load.
Thanks to the recent advancements, the adoption of wearables sensors
has spread in the industrial context to investigate workers’ conditions and well-being.
The cumulative effect of positive impacts on the human factors brings economic benefit through productivity increase, waste reduction and decrease of absenteeism.
In this view, recently, some research activities have been focused on workers’ physiological data to infer the insurgence of phenomena such as fatigue and mental stress, which may have a relevant impact on process performance.
Another research line adopted eye trackers coupled with wearables and cameras to estimate workers’ attention and stress levels.
Despite recent developments and efforts in the field, the known solutions still lack a global approach able to create a match between the parameters from sensors and the specific characteristics of operators.
The project aims at facing the industrial interests of Intellimech partners exploring the relation between the parameters collected with the sensors and the physical /cognitive condition of workers.
New skills and tools to support the servitization journey of SMEs
Company: Soluzioni Informatiche e Tecnologiche Srl
Tutor: Giuditta Pezzotta
This research project is in the area of servitization and product-service systems, i.e., the evolution of the business model of companies from a model focused on product sales to the sale of integrated product-service solutions with the aim of creating greater value for the customer.
This transformation process also involves Small and Medium Enterprises (SMEs), for which both the literature and the market offer few methods and tools suited to their needs.
This is the context for the research project in collaboration with SIT Soluzioni Informatiche e Tecnologiche Srl, a small IT company specializing in providing Business Management Software for Small and Medium Enterprises.
The objective of the project is therefore to define, starting from their software for service management and operational processes, a tool that will accompany SMEs on their path to servitization, both from the point of view of the new skills and organizational changes required and from the point of view of software applications to support processes.
The research will involve an analysis of the literature on the level of servitization of SMEs and the identification of the main barriers and needs, both from the point of view of the skills required and the methods and tools needed to support them.
The next stage will then involve defining the requirements for the development of a tool to accompany them on the path to servitization.
The research will be accompanied by the development of case studies for business requirements analysis and validation of the developed tool.
Development of artificial intelligence-based tools to support technical support
Company: SMI S.p.A.
Tutor: Giuditta Pezzotta, Roberto Leporini
At present, it is increasingly important for companies to provide a quick response to customers that enables them to restore issues inherent in production departments as soon as possible in order to maximize their efficiency.
A company must be able to provide timely information to customers located in various parts of the world and thus overcome language and time zone barriers.
In addition, the customer’s lack of technical expertise about the product makes it more difficult for the manufacturing company’s customer service department to formulate a service request and subsequently diagnose the problem.
Therefore, the goal of the project is to develop a digital assistant equipped with a knowledge base that, having as a reference a body of documents that speak about a specific domain, is able, on the one hand, to guide the customer in formulating the service request in a complete and comprehensive manner and, on the other hand, to automatically answer technical questions or point to documents that contain the required information.
In addition, all customer interactions and inquiries should be made usable through dashboards and graphical reports in such a way that they can be used by experienced operators to extrapolate additional insights about users’ most recurring issues or arguments about the machines.
Quantitative decision support methodologies in asset management
Company: SMI S.p.A.
Tutor: Giuditta Pezzotta e Fabiana Pirola
This doctoral project lies within the research strand of industrial asset management throughout the entire life cycle and, in particular, focuses on the development of methods and tools aimed at optimizing asset utilization and extending the life cycle of assets (e.g., through the provision of preventive and predictive maintenance services or optimizing operational efficiency to minimize resource demand during the utilization phase), increasingly taking advantage of the opportunities provided by digitization and remote connection of assets.
In this context, SMI Spa, a manufacturer of bottling plants and packaging machines, is embarking on its digitization journey by remotely connecting its machines in order to collect data during the utilization phase with the aim of providing a predictive maintenance service to its customers.
Thus, the goal of the project is to define quantitative methods, based on the data collected from the field, for decision support related to the management of SMI products throughout their lifecycle, with particular reference to the maintenance domain.
In parallel, the project involves defining methodologies for comparing both the economic and environmental impact of different solutions offered to customers.
Development of smart sensors with a view to Industry 5.0 and Human Manufacturing
Azienda: TSM Sensors
Tutor: Daniele Regazzoni, Gianluca Traversi
The research project is part of the new Industry 5.0 paradigm that is becoming increasingly vibrant within the international industrial landscape.
Human-machine interaction, human-centeredness and sustainability are the cornerstones that are emerging in break with a purely profit-driven approach.
The concept of Human Manufacturing introduces a significant change in the role of the worker: the worker should not be considered as a “cost” but rather as an “investment” that enables the development of both the company and the worker himself through the greater enhancement and appreciation of human capital.
A well-being, therefore, that also becomes an economic choice for companies given that an employee who experiences the work environment well improves production and lowers the possibility of errors.
In addition to the fundamental fact that through new technologies we are able to lower the incidence of occupational diseases and accidents at work, which, among other things, represent a major expense for companies.
Psychological stress and physical problems are the cause of the most critical issues that are detected at work; however, they can be monitored, predicted and solved, before they can become a problem, thanks mainly to the use of wearable devices: by monitoring people’s physical conditions and through processing done with artificial intelligence algorithms, it is possible to predict the onset of such problems.
Thus, the goal of the project is the development and implementation of sensor and microcontroller platforms for monitoring the environment, people and industrial plants, connected to the development of artificial intelligence algorithms in order to achieve intelligent cooperation between humans and machines that leads the worker to be the guide and the model on which performance, layout and modes of use of industrial plants and operating machines are adapted.
Development of a technology mapping model of Bergamo area companies
Azienda: Digital Innovation Hub Bergamo
Tutor: Gianluca D’Urso
IIn the era of Industry 4.0, digital technologies are considered the main driver of the transformation of the manufacturing sector.
However, the effective implementation in the manufacturing sector still depends on the initial state of the company and its digital knowledge.
To understand how ready manufacturing companies are for digital transformation, a “tool” has been developed, the Industry 4.0 Test, which is a maturity assessment method for measuring the digital readiness of manufacturing companies.
The Industry 4.0 Test is the main tool adopted by the network of Italy’s Digital Innovation Hubs, entities recognized by the Ministry of Economic Development that have the task of stimulating and promoting the production system’s demand for innovation, strengthening the level of knowledge and awareness with respect to the opportunities offered by digitalization, and are the “gateway” of companies to the world of Industry 4.0.
DIH Bergamo is the territorial antenna that, under the guidance of DIH Lombardy, operates in the Bergamo ecosystem: an ecosystem founded on a virtuous manufacturing model strongly characterized by the presence of small businesses and a high entrepreneurial propensity for innovation.
One of the key elements in developing innovation activities lies in the need to know the technological level of companies in the area, in order to identify their strengths and weaknesses and the main innovation elements of interest.
To do this, it is often necessary to have tools that can map the technologies and technological priorities of companies in order to collect data and have a territorial analysis to that effect.
Based on these assumptions, the goal of the doctoral program is to develop model for technology mapping of companies in the area,
considering the peculiarities of companies in the local ecosystem.
The model should take into account several dimensions, such as (but not limited to):
• Challenges or “action principles” expressed by companies (starting from the assessment results);
• The main enabling technologies that can be used in response to these needs;
• The skills needed for the development/integration of these technologies.
Additional dimensions will be considered based on the initial analysis to develop the model.
