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PURPOSE
To provide an application framework for the implementation of a smart and sustainable factory in the manufacturing industry.
Typology: Industrial Research
Final Result: FR6 | Operational framework for the implementation of Intelligent Industry.
Responsible Partner: Gruppo Ceramiche Gresmalt
Duration: 24 months
Operative Units: Sassuolo (MO), Scandiano (RE), Viano (RE), Casalgrande (RE), Fiorano (MO)
DESCRIPTION
WP 6 focuses on the transition of manufacturing factories to an intelligent operating model, known as an intelligent factory or smart factory.
The goal is to provide an application framework to help companies make this transition in a sustainable way.
The methodological approach adopted is Abductive Design Thinking, which combines analytical and intuitive thinking to promote technological innovation.
Expected outcomes include environmental impact assessment models integrated into the architecture of intelligent factories and technological solutions for product innovation.
This research represents an innovative contribution in the ceramics industry by exploring the potential of Abductive Design Thinking in solving complex operational problems.
ACTIVITIES
In order to achieve the purpose of the WP, the activities described below have been planned.
6.1 Technological footprint modelling for the Intelligent IndustryDefining a method for determining the technological footprint based on the Technological Sustainability model..6.2 Environmental footprint modelling for the Intelligent IndustryAssessment of environmental impacts through input-output-outcome analysis.6.3 Social footprint modelling for the Intelligent IndustryDetermination of social footprint considering the principles of responsible innovation in industrial operations.6.4 Economic footprint modelling for the Intelligent IndustryAssessment of economic footprint to quantify added value that the organization transfers to the territory and the community.6.5 Thermodynamic modeling of sustainability for the Intelligent IndustryDefinition of a thermodynamic model for sustainability assessment.6.6 Study and design of an Edge-to-Cloud architecture for the Intelligent IndustryDesign of the Edge-to-Cloud platform.6.7 Study and design of the Intelligent Factory for the Intelligent IndustryImplementation of AI algorithms in the Intelligent Factory system.6.8 Data-driven product analysisApplication of data mining techniques for profiling consumer demand. 6.9 Data-driven product designImplementation of a design model based on Design Thinking that takes advantage of the full digital potential offered by data digitization.6.10 Intelligent Industry modeling.Elaboration of a modeling framework to support decision-making.
RESULTS
Below are the results achieved to date:
6.1 Technological footprint modelling for the Intelligent IndustryThe activity of OR 6.1 explored the efficiency of Gresmalt's technological system and business processes in order to identify inefficiencies and make improvements.The aim was to develop an innovative method, called Technological Footprint Assessment Plus (TFA+), to assess the technological performance of a company's production facilities.Through a combined analysis of empirical and theoretical data, an attempt was made to understand how technologies influence efficiency, effectiveness, productivity and value created.The results showed that the technology footprint can be effectively measured with different indicators, providing a clear view of the impact of technologies. The TFA+ allows companies to monitor their technology performance, contributing to their competitiveness and sustainability and highlighting the need for continuous technological evolution to keep industries at the forefront and sustainable in the long term.6.2 Environmental footprint modelling for the Intelligent IndustryThe activity developed the new “Environmental Footprint Assessment Plus (EFA+)” method to monitor the environmental performance of Gresmalt's production facilities, with the aim of reducing environmental impact and improving operational efficiency.The method uses specific environmental indicators to measure aspects such as natural resource consumption, CO₂ emissions, and resource productivity.Analysis of the data collected has shown that EFA+ can provide a clear view of environmental impact and guide continuous improvement of business practices.By taking a multidimensional approach, EFA+ supports process optimization, emission control, and sustainable value creation, contributing to the company's competitiveness and reputation in the market.6.3 Social footprint modelling for the Intelligent IndustryThe research activity developed the Social Footprint Assessment Plus (SFA+), an innovative method to measure the social impact of production activities, combining Social Life Cycle Assessment (SO-LCA) with EU ethical guidelines (Ethics by Design, Doing, Using).The SFA+ assesses efficiency, productivity, effectiveness, social impact and value created by standardising data in energy units and integrating the DALY parameter to measure effects on human health. This approach enables accurate comparisons and supports strategic decisions to improve sustainability and social responsibility.The results (2017-2022) showed progress in resource management, economic efficiency and reduction of environmental impacts. The SFA+ fits into the ‘footprint family’, bridging the gap in integrated sustainability assessment and providing an operational tool for continuous monitoring of social performance.6.4 Economic footprint modelling for the Intelligent IndustryOR 6.4 developed the Economic Footprint Assessment Plus (EcFA+), an innovative method to measure the economic impact of smart industry.Overcoming the limitations of Life Cycle Costing (LCC), EcFA+ considered not only direct and indirect costs, but also the added value created for the company, the community and the environment. The analysis assessed operational efficiency, productivity and long-term economic effectiveness using a conceptual model based on financial inputs, production activities, outputs and impacts.The application of EcFA+ to Gresmalt's plants showed continuous improvement, confirming a high capacity for value creation and efficient use of resources.Due to its multidimensional structure, EcFA+ has proven to be a strategic tool for continuous monitoring and optimisation of industrial practices, supporting the transition to a more sustainable and resilient economy.6.5 Thermodynamic modeling of sustainability for the Intelligent IndustryThe OR 6.5 activity developed a new approach to assessing the sustainability of industrial organisations, integrating environmental, economic, social and technological dimensions into a single index: the Thermodynamic Sustainability Index.By adapting the Extended Exergy Accounting Plus (EEA+) model, an analysis system based on thermodynamic principles was constructed, capable of overcoming the subjectivities typical of assigning weights to the various sustainability indicators.The result is an alpha version of the EEA+ model, optimised for the ceramics sector, which allows an integrated quantitative assessment of the entire company system.This innovative approach makes it possible to monitor sustainability performance objectively, improve resource efficiency and reduce environmental impact, helping to make companies more resilient, sustainable and competitive in the long term.6.6 Study and design of an Edge-to-Cloud architecture for the Intelligent IndustryAs part of OR 6.6, Gresmalt has designed a new smart factory model, evolving from the Industry 4.0 paradigm towards Intelligent Industry.The goal is to create an interconnected, self-adaptive manufacturing ecosystem based on advanced digital technologies such as IoT, AI, machine learning and real-time analytics.A key element is the Edge-to-Cloud (E2C) architecture, which allows data to be processed close to the source for immediate responsiveness, while the cloud supports long-term strategic analysis.This technological evolution enables proactive resource management and a transformation of the production process into a flexible, efficient and resilient system, paving the way for a truly intelligent factory.6.7 Study and design of the Intelligent Factory for the Intelligent IndustryThe OR 6.7 activity designed an innovative Intelligent Factory model for the ceramic industry, based on the integration of digital systems (MES, ERP, BI) with machine learning algorithms, in an Edge-to-Cloud architecture capable of real-time optimisation of production resources.The system allows proactive and flexible management, with significant reductions in downtime compared to traditional Smart Factory models.A digital twin simulated the performance of the new model, highlighting advantages in terms of business continuity, efficiency and sustainability.This activity marked a strategic advance towards Intelligent Industry, combining productivity, adaptability and sustainable impact. Integration with evaluation tools such as TFA+, EFA+, SFA+, EcoFA+ and EEA+ will further improve control and business performance in the long term.
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