Keywords

1 Introduction

In recent years, the capability to provide consumers and clients with personalised products that meet their specific needs on a large scale, thanks to high levels of flexibility in the production system, has emerged as one of the strategies that can enable to differentiate business offer through high value-added innovative products (Seitz et al., 2020; Aheleroff et al., 2019; Martinelli and Tunisini, 2019). With regard to consumer goods (clothing, footwear, sports items, eyewear, etc.) an approach based on a high level of customisation (i.e. personalisation) helps emphasizing the strength of Made in Italy since it provides consumers with a product that combines design and style, with advantages in terms of both functions and comfort (Macchion et al., 2019; He et al., 2022). Other relevant sectors such as the medical one (with personalised prostheses in the orthopaedic, dental and other fields), and production of durable goods in general (in industrial design, automotive and manufacturing sectors overall) can benefit from this approach by seizing the opportunities and challenges arising from a growing demand, both at European level and worldwide, for products that differ in value, functionality and performance (Trenfield et al., 2019; Siiskonen et al. 2020).

The objective of this strategic action line is to study and develop industrial systems and models for an efficient production of personalised products to meet the specific requirements of individual clients and ensure a high degree of integration that can make the clients themselves active players of the developed solutions.

Such design and production systems should be design and developed in a reconfigurable way in order to manufacture specific products needed at times of particular emergency (such as health emergencies) or in the aftermath of disruptive events that can suddenly change the system’s priorities and require the industrial system to reposition on product ranges other than the usual (Fig. 1).

Fig. 1
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Strategic Action Line 1—Personalised production

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To this end, specific models and tools will need to be developed, using technologies that are versatile from both a manufacturing point of view (such as additive manufacturing, micro-processing), and digital point of view (such as artificial intelligence, IoT, Big Data), to exploit the knowledge of the specific context through an integrated approach to the design, production, validation and management of products and services (such as design tools that can promptly generate design alternatives).

Priority research and innovation topics depend on the different development aspects and include digital solutions for the acquisition of customers’ requirements, product configurators, advanced measurement systems, consumer-monitoring platforms, and innovative customised-production technologies, such as additive manufacturing, micro-manufacturing, hybrid processes, etc. New flexible and agile supply chain models are also needed, to take into account product modularization, postponement and “multi decoupling-point” strategies with a view to personalisation.

Prerequisites for personalised production systems are cyber security, privacy protection and the availability of platforms for data storage and traceability of information. The digital architectures shall be designed to foster the advancement of interoperability standards and to promote the integration of the different IT systems available in the production and distribution chain.

The solutions identified should be geared towards eco-compatibility criteria, with a view to controlling environmental impact, like in mass production (in particular, for consumer goods such as footwear, clothing, etc.), fostering production systems to reduce processing and manufacturing waste generation to a minimum.

Expected impact: increasing offer of personalised solutions in various manufacturing sectors; improvement of end product quality; improved matching of consumer needs and proposed solutions; increase in the efficiency and adaptability of customized production systems; optimization of customization processes through an improved control of waste levels and use of resources (such as set up times, production queues, scraps); management of logistics processes with control of procurement and production lead times along the entire supply chain thanks to the interoperability and transparency of processes; models and tools for decentralized production; reduction in the cost of the personalised product/service (compared to the current cost of manufacturing a personalised product).

2 PRI1.1: Advanced Tools for Configuration and Design of Personalised Solutions

Customers can be effectively integrated into the production chain through the identification and correct interpretation of their individual requirements during the design phase. The tools must be targeted at gathering customers’ requirements and correctly using them to deliver an optimized concept and design for individual and specific products (Tan et al., 2022; Hara et al., 2019). There is, therefore, a primary need for tools that enable customers to communicate their ideas and/or requirements in a simple way, without demanding specific knowledge and/or posing cultural and linguistic restrictions. The ability to orchestrate properly the innovation phase of a product or service in a multidisciplinary environment involving many players that interact in a virtual way becomes of fundamental importance (Reinhart et al., 2010). Furthermore, the growing demand for possible product variants increases the importance for companies to predict the impact of design choices on all aspects of their production cycle (e.g. product functionality, manufacturability and production costs), distribution, use and disposal/recycling. The ability to exploit the specific knowledge of the context in which a product will be used thanks to artificial intelligence technologies becomes fundamental for the creation of efficient tools, in particular for those types of products created to meet specific requirements that can impact on the functionality of the product itself (e.g. bio-medical products).

The goals of this research and innovation priority are therefore:

  • Development of “multi-user” collaborative design platforms that enable the interaction of all the different players involved in the production process (designers, end users, producers, suppliers of materials and components). These platforms must be based on sharing knowledge to predict systems’ behaviour and improve modelling and simulation, offering and integrating easy-to-use solutions and more efficient test and validation methods. In particular, it includes:

  • Automated and creative design systems to facilitate the design of product alternatives;

  • Design systems with embedded tools for the assessment of the feasibility and product-costing;

  • Configuration tools that can successfully integrate the identified customer requirements;

  • Geometric processing and analysis methods to integrate design and simulation in a consistent way and maximize the advantage of using specific production technologies.

  • Development of “mobile” platforms that, by using artificial intelligence and big data analytics, can support the collection of both users’ requirements (directly and indirectly expressed), and feedback from the field during product usage, and at the same time facilitate the identification of market trends. Specifically, it includes:

  • Data Capturing systems for the acquisition and analysis of heterogeneous data from different sources (such as social media, feedback during the use phase of a product, etc.);

  • Systems for storing and managing large amounts of “personal” data obtained from widely used applications, protected and made available to consumers, to be used during personalisation process.

  • Development of innovative virtual and collaborative design platforms (based on AI, VR/AR technologies) intended for non-expert users; such platforms should not require specific knowledge or design skill but rather support the user in expressing or detecting in a natural and easy way their specific requirements. In particular, these solutions should be based on:

  • Emerging Human–Computer Interaction-HCI technologies (e.g. visual, tactile, sound) for easy and natural interaction;

  • 3D modelling representations suitable to manage multidimensional heterogeneous data (i.e. images, 3D geometry);

  • Systems based on the principles of the Internet of Actions (IoA) to allow the user (consumer, retailer, manufacturer) to act remotely and reproduce sensations and actions in an interactive and adaptive way. It is thus possible for expert and non-expert operators to interact remotely. The development of new sensors and actuators will be essential in creating the perception of being present when working/acting from remote, and in ensuring accurate and safe remote actions.

  • Development of tools and methods for the creation of structured product models starting from the collected data based on context semantics and geared to overcome the limits of 3D reconstruction due to the lack of effective integration between detected data and knowledge of the reference domain (for instance, in models of anatomical parts for the construction of personalised prostheses the limit is represented by the incomplete integration of medical knowledge).Specifically, it includes::

  • 3D reconstruction methods guided by semantics of the context

  • Systems for managing feedback on wearable products (IOT) to test products’ functionality during use.

Interaction with Other Strategic Action Lines

  • LI4—Product design for customisation should be aligned with process design and efficiency

  • LI6—Product design for customisation should be aligned with process design to support product reconfigurability

  • LI7—The management of big data related to customisation is essential in managing inputs from products, customers and the market, just as cyber-security aspects are in the management of data.

Time Horizon

Short-term goals (2–3 years):

  • Development of capturing systems for the acquisition and analysis of heterogeneous data;

  • Development of systems for storing and managing large amounts of “personal” data obtained from widely used applications, protected and made available to consumers, to be used in the personalisation process.

Medium-term goals (4–6 years):

  • Development of automated and creative design systems to rapidly produce design alternatives;

  • Development of design tools integrated with feasibility assessment and product costing tools;

  • Development of configuration optimization tools that can successfully integrate specific requirements;

  • Definition of geometric processing and analysis methods to integrate design and simulation in a consistent way and maximize the advantage of using specific production technologies;

  • Development of systems based on emerging Human–Computer Interaction-HCI technologies (e.g. visual, tactile, sound technologies) for easy and natural interaction;

  • Definition of new representations for 3D modelling suitable to manage multidimensional heterogeneous data (i.e. images, 3D geometry);

  • 3D reconstruction methods guided by semantics of the context;

  • Development of systems for managing feedback on wearable products (IOT) to test products’ functionality during use.

3 PRI1.2: Solutions for the Efficient Production of High Value Personalised Products

Personalised products require modular, flexible and adaptable production systems, i.e. adapting and reconfiguring themselves according to the features required from time to time by the customer, without losing efficiency and product quality, in accordance with the emerging production paradigms of “Zero-waste and Zero Defect manufacturing”, focusing on product quality and efficient use of resources.

Production systems heading in this direction already exist but the amount of alternatives required by personalisation is constantly increasing and must ensure that resources can be used efficiently and adapted to such needs. A high level of customisation (personalisation) also requires production phases to be synchronized with the product design, and with the logistics for handling the parts, so that information can be moved from one phase to another in a flexible and reliable manner (Medini et al., 2019). It is therefore necessary to study new reconfigurable systems and new plug-and-produce devices capable of guaranteeing a rapid response to frequent changes in customers’ requirements and unit batches as well (Plasch et al., 2012).

These new paradigms carry along a strong integration between production and logistics systems at shop floor level. New digital models, algorithms and self-adaptive autonomous technologies need to be developed to ensure real-time planning and control of reconfigurable production and logistics systems, reducing reconfiguration and downtime (Medini et al., 2019; Keiningham et al., 2020; Zhang et al., 2019).

The goals of this research and innovation priority are:

  • Reconfigurable production systems dedicated to both B2B and B2C personalisation for the production of components and products very often characterized by dynamic properties and behaviours, differentiated in response to the needs and requirements of the consumer. In particular, these solutions must be supported by innovative approaches to the production process and its control, in order to transform the project into a product that has the appropriate mechanical and functional characteristics according to user needs. In this context, the hybridization of traditional technologies (i.e. hybrid/additive), that is the integration of different production processes into a single machine, is a step towards a potentially very broad diversification of technological alternatives.

  • Manufacturing technologies for products with complex geometries and high surface finishes, combining different materials and a progressive variation of properties in the various areas of the production process.

  • Solutions for modularity and reconfigurability of manufacturing lines: such solutions should be supported by flexible “plug & produce” modules that can be applied on machines built by different manufacturers. In particular, the development of production platforms that allow the automatic integration of production modules for customized components with those for standard components (tooling/production line set-up) in order to guarantee various functions such as: the integration of modules equipped with controllers with different degrees of intelligence; product changeover; the management of demand fluctuation and its impacts on the production system; the removal and/or integration of modules in real time. In addition, modular self-adjusting and self-adapting systems of a plug-and-produce type, based on digital models and artificial intelligence can help to promptly react to frequent changes in customer orders and to the high variability of demand.

  • Procurement/storage/handling systems that are tailored to the increased variability of shapes, sizes, weight and materials required by the wide range of different raw materials, semi-finished and finished products necessary for the goods personalisation. The adoption of advanced sensor systems is required, for instance, for the tracking of products in batch-1, for the automatic creation of assembly kits, visual inspection systems for the assembly kits control even with customized and unitary batch.

Interaction with Other Strategic Action Lines

  • LI4—High efficiency integrated systems: a reconfigurable internal production and logistics system must guarantee high efficiency even in contexts of high level of product personalisation.

  • LI5—Innovative production processes: reconfigurability and high flexibility production systems can be achieved through intelligent machines and handling systems.

  • LI6 and LI7—An efficient production of personalised and high value-added products can be obtained by controlling reconfigurable production systems, Digital Twin solutions, implementation of Human Robot Co-working and applications of AI algorithms.

Time Horizon

Short-term goals (2–3 years) that are pursued starting from existing technologies:

  • Improving the surface finish in product manufacturing through additive manufacturing and increasing the productivity of hybrid machines for additive manufacturing up to the levels of mass production systems;

  • Easily integrate, exchange, or remove production equipment without the need for specialized personnel to reconfigure the system, through advanced Plug and Produce technologies.

Medium-term goals (4–6 years) that involve significant development:

  • Development of integrated frameworks (from end-user design to product delivery) that can ensure a time to market ranging from 24–48 h;

  • Innovative technologies for handling soft and flexible materials such as grip**, moving, positioning, sorting, joining processes, in order to include these handling solutions in flexible production processes;

  • Intelligent manufacturing and handling solutions that can adapt themselves to the product characteristics (in terms of size, shape, weight, colour, material composition, defects, etc.).

Long-term goals (7–10 years) that require the integration of all the technologies developed as a result of a research and innovation priority:

  • Digital Twin platforms for customized and resilient productions.

4 PRI1.3: Advanced solutions for customer-driven production management

From a technological point of view, it is essential that demand-driven production is synchronized with the customer order management, with scheduling and production, through a coordinated management of material and information flows. It is also necessary to coordinate production with internal and external logistics through appropriate models for integrating information that comes from different sources.

In order to achieve these objectives, new management systems must be developed, based on technologies such as Big Data Analytics, Artificial Intelligence and decision-supporting models geared to increase the companies’ ability to manage and use large amounts of data from different sources (customer, suppliers, social networks) to allow better production management, dynamic supply and distribution networks.

The use of big data technology also allows the activation of blockchain processes that guarantee the integrity of the transferred data. In addition, greater interoperability, transparency and autonomy in the product life cycle through the use of resources and value-added services is desirable.

In this context, goals of this research and innovation priority are:

  • Collaborative platforms development: through appropriate knowledge sharing systems at different levels of the value chain these platforms can support decisions such as: dynamic network configuration, decentralized planning of activities, real-time management of independent and reconfigurable production systems, product modularization strategies, postponement strategies and “multi decoupling-point”. These platforms must be able to manage key elements such as demand variability, specific personalisation characteristics within product families, economy-of-scale, service capacity, and the trade-off between the decentralization of production (global integration) and the local manufacturing of some of the components needed in personalisation. These collaboration platforms must guarantee high levels of interoperability between different information management systems.

  • Production and logistics control and monitoring tools for managing disruptive events: tools based on the data collected in real time from different sources (machinery, products, suppliers, handling systems). These tools allow company manager the detection of critical issues and definition of response policies to any uncontrolled processes, through solutions capable of “mediating” on different products, processes or services and capable of operating with small batches, even down to one. It is necessary to be able to track the status of each resource in real time, in order to implement specific actions (process parameters, replacement and maintenance policies) and react promptly to unexpected events. Furthermore, the possibility to provide real-time data to check the resources and process status will allow the development of new approaches for the certification of the personalised product for anti-counterfeiting purposes and for the certification of production process, particularly in highly regulated sectors such as biomedical and aerospace. These tools will have to operate according to the paradigms of interoperability, transparency and autonomy.

  • Models and methods for the validation and certification of information for the design, production and distribution of personalised products. Such systems must enable decentralized interaction in the production chain, ensuring the coordination of actions and supporting the collection and sharing of data through synchronization even in very dispersed and broad contexts from a trust-management perspective.

  • Digital Twin platforms capable of integrating suppliers and users in a transparent and efficient manner. Such systems should also allow the real-time management of autonomous systems, which ought to be self-adapting and self-organizing in kee** with paradigms of interoperability, transparency and autonomy.

Interaction with Other Strategic Action Lines

  • LI4—Production planning and management require high-efficiency integrated systems, especially where considerable product personalisation is required.

  • LI5—The management of internal and external logistics to ensure reconfigurability and flexibility needs innovative and “smart” production processes.

  • LI6 and LI7—Digital Twin solutions and AI algorithm applications can ensure efficient management of the supply chain of high value-added personalised products.

Time Horizon

Short-term goals (2–3 years) that are pursued starting from existing technologies:

  • Development of models to formalize and connect the design, production and distribution requirements of personalised products;

  • Development of systems to share data collected from the field (e.g. distributed ledger technology) with production management systems and vice versa.

Medium-term goals (4–6 years) that entail significant development:

  • Greater extension of End-to-End Engineering through the design of systems for the reconfigurability of a product’s dynamic requirements.

Long-term goals (7–10 years) that require the integration of all the technologies developed as a result of the research and innovation priority:

  • Design and develop Digital Twin platforms to integrae material and information flows between suppliers and users transparently and efficiently;

  • Digital Twin tools that allow the real-time management of autonomous systems, which are self-adapting and self-organizing according to the following paradigms: interoperability, transparency and autonomy.

5 PRI1.4: Mini-Factories in the Production and Distribution Chain of Personalised Products

Small-scale distributed production becomes increasingly important in different sectors and in different situations (such as in a health crisis when it is necessary to quickly produce basic necessities with limitations deriving, for example, from the closure of national and regional borders) and is based on the structuring of production facilities with very fast set-up and decommissioning times and easily transferable to different locations (real mini-plants, fab-labs, production in containers).

It is thus possible to ensure that part of the production and in particular the manufacturing of personalised parts/components is postponed to the last mile and carried out near the place of delivery and use of the objects.

It is therefore necessary to define new organizational models based, in accordance with the urban manufacturing paradigm, on the creation of laboratories and mini-factories equipped with advanced machinery that support the production of personalized products quickly and at low cost. The new organizational model must include the use of technology highly reconfigurable and adaptable to the specific context and the revision of the collaboration model upstream with suppliers and downstream with users to redefine the flow of operations.

The possibility of operating locally (neighbourhood, municipality, region) with dedicated mini-factories, in addition to reducing logistics costs, can extend the scope of application of “customized” recycling technologies that would otherwise be too expensive and thus meet to the growing demand for customization in the repair/reuse of end-of-life products.

The mini-factory model can constitute the connection between (Do-it-yourself) makers and industrial companies and give rise to new functionalities and innovative production methods (new processes, new machines, low-cost ideas, etc.).

The goals of this research and innovation priority are therefore:

  • Simplified, easily transportable and low-cost set-up machinery for the on-site production of dedicated products, or for the functionalization/customization of products, or for disassembly (modular factory—factory on truck, etc.) purposes. In particular, development of new production technologies that are very versatile in terms of geometries and materials in order to obtain a large set of components with multiple functions with a limited set of machinery.

  • Innovative production chain management models based on the study of decentralized production centres to bring personalisation to the last mile. New production models integrated with distribution, that allow the delivery of raw materials and small batches of products in urban contexts (mini factories served as consumers—use of e-commerce systems) even with the use of adequate self-driving vehicles that can circulate in difficult environments with low carbon emission.

  • Multi-user collaboration platforms for the design, manufacturing and distribution of products and related components, based on open innovation principles that integrate mini-factories. This also implies the definition of new IP sharing mechanisms, in order to guarantee rewarding systems for new types of business.

  • New service centre models to provide temporary solutions (rental) consisting of autonomous mini-factories, in order to facilitate the access of new innovative players (makers, small businesses, etc.). These service centres should also ensure integration between different mini-factories for the production of components and products of different types by means of design and production systems that allow the sharing of resources and materials.

Interaction with Other Strategic Action Lines

This priority is closely linked to the LI5 line of intervention and in particular to the development of low cost and high productivity multimaterial additive technologies (for local “real time” production of personalised products/components).

Time Horizon

Short-term goals (2–3 years) that are pursued starting from existing technologies:

  • Development of multi-user collaboration platforms for the design, production and distribution of personalised products and related components, based on open innovation principles (Distributed Design Platform);

  • Development of simplified, transportable and low cost set-up machinery (integrated, ultra-fast, self-configurable and user-friendly systems).

Medium-term goals (4–6 years) that entail significant development:

  • New production models integrated with distribution, which allow the delivery of raw materials and small batches of products in urban contexts (mini-factories served as consumers);

  • Development of new models of service centres to provide temporary (rental) solutions of autonomous mini-factories to facilitate the access of new players (makers, small businesses, etc.).

Long-term goals (7–10 years) that require the integration of all the technologies developed as a result of the research and innovation priority:

  • Integration in a single supply chain of the four previous objectives.

6 PRI1.5: Production Systems of Smart Materials for Product/service Personalisation

This research and innovation priority focuses on technologies and processes for the production of innovative and intelligent materials (e.g. sensorized fabrics, display materials, micro- and nano-materials, multifunctional fabrics, materials for biomedical use, high-performance renewable materials) that can produce in line with the specific consumer needs or can perform a function based on the adaptive capacity of the material itself (i.e. that can work as sensors by capturing changes in parameters and at the same time as actuators by performing an action). To achieve this goal, the new production systems should produce components made of homogeneous materials (to be easily recyclable and based on the intrinsic active properties of the material, such as shape memory materials, photosensitive, magnetostrictive materials, etc.) or components with engineered morphological structures (lattice structures, multiscale, with gradient, micro-kinematics, etc.) or composite structures or materials.

The ability to integrate a device with sensor capabilities that can equip it with intrinsic intelligence is also of utmost importance. Examples include Lab-on-chip with integrated biosensors for precision medicine and mechanical devices that can monitor external parameters related to the work environment or the device’s internal parameters (such as fatigue, critical situations of dysfunctionality, etc.).

The goals of this research and innovation priority are therefore:

  • Production systems that aim at integrating “smart” functions directly during the manufacturing process (on line), that is production systems that can directly manage materials with smart functions or assign functions to the components downstream the production process

  • 3D printing or multi-material additive systems, that is additive systems that can manage multiple materials at the same time, geared at producing functional devices with property gradient and additive systems that provide the product with smart functionalities during the manufacturing process (even achieving non-constant functionalities in the final device)

  • Components with engineered and “customizable” morphological structures (latex, multiscale, gradient, micro-kinematic structures, etc.): composite structures or materials that can make use of such engineering in the manufacturing of components with high functional performance and easy personalisation.

  • Innovative production technologies for the manufacturing of intelligent micro-devices, including devices with sensor capabilities, such as for example lab-on-chip with integrated biosensors for precision medicine or mechanical devices that can monitor external parameters and parameters related to the work environment and device’s internal parameters (such as fatigue, critical situations of non-functionality, etc.).

Interaction with Other Strategic Action Lines

Connection with the PRI5.5 of action line LI5, which deals with the production and manufacturing processes of innovative materials.

Time Horizon

Short-term goals:

  • Development of design tools for engineered morphological structures;

Medium-term goals:

  • Development of production systems based on the use of smart materials and with high geometric flexibility (4D printing);

  • Development of design tools for active structures.

Medium-long term goals:

  • Development of innovative production technologies for the manufacturing of bioengineered Lab-on-chip micro-devices with integrated biosensors for precision medicine.