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Metal additive manufacturing is growing its impact on high-tech industrial sectors so far. The capability to recover and repair worn components, with costs that are gradually more affordable, is giving a boost to the development of these technologies. The direct laser metal deposition (DLMD) technology is taking a leading role in this domain. Manufacturing components, with high mechanical properties, require a careful process design and a continuous control. The monitoring of the thermal field thus assumes a crucial role in processes in which high-power sources are involved. Thermal treatments influence the microstructure, morphology and the grain size of the depositions indeed, which determine high-performance standards. In this work, an ytterbium fibre laser source was used to build single-track depositions of a nickel-based superalloy powder on a substrate of the same material. Temperature field monitoring was performed using a high-frequency (100 Hz) IR thermal camera, allowing an accurate monitoring of peeks temperature, thermal cycles and thermal gradients. Thermal data and process parameters were compared with metallographic analysis to capture the relation between the geometrical and microstructural characteristics of clads. The study focuses on the influence of the powder feed rate and energy density on thermal parameters. An innovative approach to the solidification map method, commonly implemented with numerical simulations of welding and additive manufacturing, has been successfully applied to experimental data giving results consistent with the literature.

The direct laser metal deposition (DLMD) is an emerging technology in the additive manufacturing field, which is becoming widely adopted in several industrial applications. The optimal selection of process parameters is critical, given the cost of physical tests and the requirement for high-quality manufacturing. Correct forecasting of process parameters using predictive physical models is a viable alternative to shorten the setup phase and improve the sustainability. In this paper, firstly, several models available so far in the literature are reviewed, and then, a general model is derived to evaluate the best combination of process parameters in single track operations. The proposed phenomenological model allows simple forecasting based on three main process parameters: laser power (P), powder feed rate (F) and translation speed (V). An innovative approach is proposed to generalise the model and overcome the “try and error” method used in numerous works to determine the exponents (α, β, γ). The model was designed considering the physical parameters which best explained the variability of the exponents: the thermal diffusivity of the base material and the density of the powder material. The best ranges of the process parameter exponents are suggested to establish the most suitable combined parameters for the prediction of geometric characteristics of the clad. The potentialities of the model are proven based on an experimental case performed over a commercially available Nickel-based super-alloy powder. New formulations are recommended, which are in good agreement with the behaviours defined in the literature, as shown in the test case.

International audience; The digital twin has received strong interests from researchers and industries since it allows predictive manufacturing by integrating the cyber and the physical space. An important prerequisite for the cyber-physical integration is a proper and highly-accurate digital model. Considering the complexity of digital modelling, the paper aims at developing and using predefined modelling patterns to enable building digital models independently of the specific application domain. The idea is explored and validated on a real case study by designing a set of patterns to create a digital twin model prototype adopted to control and optimize the manufacturing system taken into account.

International audience; Manufacturing enterprises are facing the need to align themselves to the new information technologies (IT) and respond to the new challenges of variable market demand. One of the key enablers of this IT revolution toward Smart Manufacturing is the digital twin (DT). It embeds a “virtual” image of the reality constantly synchronized with the real operating scenario to provide sound information (knowledge model) to reality interpretation model to draw sound decisions. The paper aims at providing an up-to date picture of the main DT components, their features and interaction problems. The paper aims at clearly tracing the ongoing research and technical challenges in conceiving and building DTs as well, according to different application domains and related technologies. To this purpose, the main questions answered here are: ‘What is a Digital Twin?’; ‘Where is appropriate to use a Digital Twin?’; ‘When has a Digital Twin to be developed?’; ‘Why should a Digital Twin be used?’; ‘How to design and implement a Digital Twin?’; ‘What are the main challenges of implementing a Digital Twin?’. This study tries to answer to the previous questions funding on a wide systematic literature review of scientific research, tools, and technicalities in different application domains.

Direct metal laser deposition (DMLD) is an additive manufacturing technique suitable for coating and repair, which has been gaining a growing interest in 3D manufacturing applications in recent years. However, its diffusion in the manufacturing industry is still limited due to technical challenges to be solved—both the sub-optimal quality of the final parts and the low repeatability of the process make the DMLD inadequate for high-value applications requiring high-performance standards. Thus, real-time monitoring and process control are indispensable requirements for improving the DMLD process. The aim of this study was the optimization of deposition strategies for the fabrication of thin walls in AISI 316L stainless steel. For this purpose, a coaxial monitoring system and image processing algorithms were employed to study the melt pool geometry. The comparison tests carried out highlighted how the region-based active contour algorithm used for image processing is more efficient and stable than others covered in the literature. The results allowed the identification of the best deposition strategy. Therefore, it is shown how this monitoring methodology proved to be suitable for designing and implementing the right building strategy for DMLD manufactured 3D components. A fast and stable image processing method was achieved, which can be considered for future closed-loop monitoring in real-time applications.

International audience; Despite the recent growing interest in the " factory smartness " , still there are few small and medium enterprises (SMEs) that adopt effective I4.0 solutions. The main reasons can be related to the lack of formalized processes, lack of ICT knowledge as well as low-cost commercial systems. To cope with these issues, this work focuses on the development and the application of an approach to provide SMEs with a multipurpose , modular, knowledge-based system: the main aim is to provide a modular and extensible system that can be incrementally implemented without requiring a huge initial investments. This system is based on a core design-knowledge metamodel. From this core metamodel, multi-purposes modules can be built: in this paper, we present modules for the traceability support, the AR-powered assembly support, the machine-to-machine control and the data analysis support.

In this paper, hybrid laser-MAG (metal active gas) welding of twinning-induced plasticity (TWIP) and dual-phase (DP) steels with austenitic stainless steel (AISI316) was simulated by means of the finite element method. A thermo-mechanical model, which uses a 3D heat sources, was developed using the software Simufact Welding. The calculated dimensions, shape and distortion of the weld were compared with the experimental results, thence the model was validated. The metallurgical transformations for the DP steel were evaluated using the continuous cooling transformation (CCT) diagram and the calculated cooling rate. The numerical model predicted accurately the shape of the molten pool, the thermal cycles as well as the geometrical distortion of the butt weld. Therefore, the numerical model showed a good reliability and its potential for further development.

The number of scientific papers in the field of Sustainable Manufacturing (SM) shows a strong growth of interest in this topic in the last 20 years. Despite this huge number of publications, a clear statement of the profound meaning of Sustainable Manufacturing, or at least a strong theoretical support, is still missing. The 6R framework seems to be a first attempt to rationalize this issue, as it is an axiomatic identification of its true nature. Recognizing the pursuing of one or more of the Reduce-Recycle-Reuse-Recover-Redesign-Remanufacture principles allows users to identify if any manufacturing action is in the right direction of sustainability. In the paper, the authors speculate on the use of this framework and its possible extension by referring to all the existing scientific contributions on Sustainable Manufacturing in the SCOPUS® databases as a source of data. Starting from the measurement of the distribution of the scientific papers allocated onto the 6Rs dimensions, by using both author keywords and automatically extracted multiword from texts, the distribution of the scientific papers among the 6R was derived. A new framework is proposed based on analytical text tools to compare the affinity of the applied research activities of the Italian Technologist network SOSTENERE to sustainable manufacturing and provide also a benchmarking view to describe the Italian way to SM with respect to the rest of existing applications.

Part 14: Data Management for Collaboration in Value Creation Networks; International audience; The digital transformation of collaborative networked manufacturing enterprises requires building and applying digital models representing the set of resources and processes knowledge. Modelling such digital copy of the physical system to perform real-time validation and optimization is quite complex and thus needs a big amount of data and some modelling patterns representing the operational semantics of the modelled elements. Generally, the modelling action has a specific application type. For this reason, the core challenge of the digital transformation modelling is to create a modular "digital model", namely a decomposable and re-composable model, towards different applications. The authors propose an approach based on the combination of data-driven and model-driven approaches, to identify and formalize modelling patterns, that combine for developing a modular executable model of the studied system.

International audience; Manufacturing organizations are facing the urge to adopt new strategies like sustainability to be able to respond to the market and customer's demand for sustainable products due to the scarcity of the natural resources or government policies. To serve this purpose, the main questions risen are "How sustainability is defined through its dimensions? and What sub-dimensions can denominate sustainable manufacturing? Focusing on the questions, this study is cantered by a systematic literature review based on sustainability, its dimensions and subdimensions to investigate sustainability in manufacturing and the domains on which manufacturers can act on to be more "sustainable". Although the literature is more focused on the three traditional dimensions of sustainability namely: environmental, economic and social, a more detailed look through the dimensions is needed to help manufacturing organizations sketch their own sustainable strategies on more specific issues. The study of the dimensions led to a hierarchy of importance for the traditional three, in which environmental dimension of sustainability showed to be conspicuous. Therefore, the dimension was chosen for the further analysis conducted by Formal Concept Analysis (FCA) on its sub-dimensions to explore the trends in their combination by manufacturers while trying to reach sustainability.

The development and implementation of the smart factory paradigm seems to be a must almost widespread all over the Western manufacturing companies so far. This article explores the application of exergetic analysis models as a feasible approach to customize such an announced paradigm shift: the implementation criteria as well as the true expected benefits are, in fact, far to be clearly understood or even perceived. An Italian medium enterprise located in the south of Italy operating in the automotive sector is adopted as a test bench. The standard use of exergetic model was adopted to assess and improve the sustainability of the manufacturing processes performed by the company, namely: turning, milling, grinding, plating and dehydrogenation. This thermodynamic view of the processes, on the other hand, represented a guideline to design a smart factory solution, and thus to structure the critical variables and the paths to digitalize processes for the intelligent control of the core production processes.

Published in IFAC-PapersOnline, 51(11):921-926, 2018; International audience; Six sigma is a well-assessed methodology for optimizing the performance of the enterprise through the reduction of the variability of their process outputs. Six sigma implementation consists of the development of the DMAIC phases to improve existent processes. Each phase of this methodology adopts statistical as well as qualitative tools to fix variability sources and assess the process to a six sigma level of quality. However, there is a lack of an implementation model on how to guide effectively the implementation of the methodology DMAIC. This is particularly true for SMEs that not have enough human resources for supporting the needed knowledge. To answer to this limitation of six sigma, the objective of this paper is to present a framework to support the implementation of six sigma approach in SMEs. This framework is formalized by a meta-model, which is based on different studies on six sigma, its phases and its tools. This framework aims to propose a solution to validate the passage between the DMAIC phases defining the requirements to be satisfied during each phase.

International audience; Highly customized products with shorter life cycles characterize the market today: the smart manufacturing paradigm can answer these needs. In this latter production system context, the interaction between production resources (PRs) can be swiftly adapted to meet both the variety of customers' needs and the optimization goals. In the scientific literature, several architectural configurations have been devised so far to this aim, namely: hierarchical, heterarchical or hybrid. Whether the hierarchical and heterarchical architectures provide respectively low reactivity and a reduced vision of the optimization opportunities at production system level, the hybrid architectures can mitigate the limit of both the previous architectures. However, no hybrid architecture can ensure all PRs are aware of how orienting their behavior to achieve the optimization goal of the manufacturing system with a minimal computational effort. In this paper, a new " hybrid architecture " is proposed to meet this goal. At each order entry, this architecture allows the PRs to be dynamically grouped. Each group has a supervisor , i.e. the optimizer, that has the responsibility: 1) to monitor the tasks on all the resources, 2) to compute the optimal manufacturing parameters and 3) to provide the optimization results to the resources of the group. A software prototype was developed to test the new architecture design in a simulated flow-shop and in a simplified job shop production.

Best track paper (1/20); International audience; Today, sustainability becomes one of the biggest challenges. It represents a key issue in every production activity. To face this issue, a possible solution is to enhance knowledge usage in manufacturing and sustainability domains. In this paper, we extend the ONTO-PDM ontology for formalizing sustainable manufacturing knowledge. An industrial case is presented for instantiating the extension. Moreover we design a knowledge-based system, which exploits sustainable manufacturing knowledge for supporting design and process planning with sustainability proposals, generating machine code starting from product specifications.

International audience; Standardisation initiatives (ISO and IEC) try to answer the problem of managing heterogeneous information, scattered within organizations, by formalising the knowledge related to products technical data. While the product is the centred object from which, along its life cycle, all enterprise systems, either inside a single enterprise or between cooperating networked enterprises, have a specific view, we may consider it as active as far as it participates to the decisions making by providing knowledge about itself. This paper proposes a novel approach, postulating that the product, represented by its technical data, may be considered as interoperable per se with the many applications involved in manufacturing enterprises as far as it embeds knowledge about itself, as it stores all its technical data, provided that these are embedded on a common model. The matter of this approach is to formalise of all technical data and concepts contributing to the definition of a Product Ontology, embedded into the product itself and making it interoperable with applications, minimising loss of semantics.

International audience; The product variety management is a key process to deal with the flexibility requested by the mass customisation. In this paper we show that current variety-modelling methods miss a customer representation: without a proper assessment of the customers is not possible to define the product variety that has to be developed to meet the requirements of a customer segment. Here we present an innovative approach to rationalise the product variety, i.e. to link each product variant to the customer profile who needs it. The aim is to optimise the product variety avoiding excesses (variants not related to a customer), lacks (customers not related to a variant) or redundancies (two or more variants proposed to a customer). An overview of customer modelling approaches in the classic product design (non-customisable) is presented. The innovative approach is here developed using system-thinking concepts. A knowledge-based system that uses this approach is designed. Finally the approach is explained using a real industrial case of a quasi-real coil design process.

International audience; Sustainability is one of the biggest challenges of this century either for the environment or economical growth. The required cultural shift needs challenging action that will involve deeply software and hardware aspect of manufacturing processes. In this paper, the software part of the matter is addressed by proposing a product centric ontology, in which concepts of product, processes and resources are associated to functions and sustainable manufacturing knowledge. The aim is to design a knowledge-based system that, simulating a sustainable manufacturing expert, is able to automatically identify change opportunities and to propose alternatives on the basis of the existing production scenario.

International audience; This paper proposes an approach for facilitating systems interoperability in a manufacturing environment. It is based on the postulate that an ontological model of a product may be considered as a facilitator for interoperating all application software that share information during the physical product lifecycle. The number of applications involved in manufacturing enterprises may in fact refer to the knowledge that must be embedded in it, appropriately storing all its technical data based on a common model. Standardisation initiatives (ISO and IEC) try to answer the problem of managing heterogeneous information scattered within organizations, by formalising the knowledge related to product technical data. The matter of this approach is to formalise all those technical data and concepts contributing to the definition of a Product Ontology, embedded into the product itself and making it interoperable with applications, thus minimising loss of semantics.

ISSN: 1367-5788; International audience; Standardisation initiatives (ISO and IEC) try to answer the problem of managing heterogeneous information, scattered within organizations, by formalising the knowledge related to products technical data. While the product is the centred object from which, along its life cycle, all enterprise systems, either inside a single enterprise or between cooperating networked enterprises, have a specific view, we may consider it as active as far as it participates to the decisions making by providing knowledge about itself. This paper proposes a novel approach, postulating that the product, represented by its technical data, may be considered as interoperable per se with the many applications involved in manufacturing enterprises as far as it embeds knowledge about itself, as it stores all its technical data, provided that these are embedded on a common model. The matter of this approach is to formalise of all technical data and concepts contributing to the definition of a Product Ontology, embedded into the product itself and making it interoperable with applications, minimising loss of semantics

International audience; The “Babel tower effect”, induced by the heterogeneity of applications available in the operation of enterprises brings to a consistent lack of “exchangeability” and risk of semantic loss whenever cooperation has to take place within the same enterprise. Generally speaking, this kind of problem falls within the umbrella of interoperability between local reference information models .This position paper discuss some idea on this field and traces a research roadmap to make enterprise interoperable on the basis of this statement to face interoperability of RIMs by focusing the attention on the product. By applying a transformation between local information models into an “ontological reference model” centred on the product it is possible to insure applications interoperability