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Multiple international organizations and many governments around the world have declared climate emergency. There is a pressing need to minimize the environmental impacts of human activities including manufacturing processes. Machining by mechanical cutting is a fundamental manufacturing process and minimizing and eliminating its environmental impacts is vital. In this keynote paper, sustainability in the context of machining is identified. The resources used in machining have been categorized and the social and environmental impacts and potential methods to reduce them have been identified. The findings are critically discussed and the gaps and challenges for future research direction are highlighted. [ABSTRACT FROM AUTHOR]

The fraction of materials that does not reach the target product in discrete manufacturing is very significant. Directing secondary material streams towards other manufacturing processes, possibly after intermediate pre-processing, offers opportunities for more energy and resource efficient recycling routes. This paper contributes to the exploration of such symbiotic recycling strategies by identifying relevant process mechanisms and by systematically scanning the manufacturing domain for relevant process combinations. Emerging and proven symbiotic combinations within the discrete manufacturing domain are reviewed, with proper attention for the quantification of the thus avoided environmental impact. A series of representative case studies illustrates the feasibility of applying industrial symbiosis principles in a discrete manufacturing context, with uniform data sheets providing detailed information on relevant research achievements. [ABSTRACT FROM AUTHOR]

Today, tailored laser beams are rarely used and thus an opportunity to optimize existing or introduce new processes is missed. New methods of dynamic beam shaping have the potential to change that in future. This keynote paper deals with methods allowing a transient energy input into the workpiece at such time scales that the underlying interaction processes are guided towards the desired result. It shows principles, categorizes necessary system technology, and gives application examples to familiarize the reader with the topic. It postulates that time-scale-dependent coupling between transient energy input and addressed process features is key for achieving the optimum. [ABSTRACT FROM AUTHOR]

The transition from conventional standalone metrology to integrated metrology has been accelerating in advanced manufacturing over the past decade. This keynote paper defines the concept of integrated metrology, which extends beyond parts inspection and encompasses processes and manufacturing equipment to enhance efficiency and productivity. The paper presents the characteristics, benefits, constraints, and future possibilities of integrated metrology for parts, processes, and equipment. It also includes a classification of the physical quantities of measurands, the corresponding measuring instruments, data and communication methods, uncertainty, and traceability. The paper also discusses future challenges and emerging trends. [ABSTRACT FROM AUTHOR]

Forming processes are known for their intricacies in prediction and control due to the complex loading conditions and material flow. This paper will first introduce the AI algorithms used or having potential to be used in forming, and then investigate the state-of-the-art advances of AI-based technologies in forming processes with four main pillars of process simulation, process design and optimization, in-situ process control, and qualification and certification of forming processes and formed products. Future directions of AI in forming for both academic research and industrial applications will be proposed to leverage digitalization and data science to explore new solutions in forming processes. [ABSTRACT FROM AUTHOR]

Microstructures with high surface integrity are difficult to efficiently fabricate on silicon carbide. A method for modifying the band gap via ion implantation is proposed, which induces a crystalline-to-amorphous transition so that the laser intensity for material removal is substantially reduced. The structure can be generated by a single pulse, considerably increasing the efficiency. Furthermore, chemical etching is introduced to make the process material selective and self-limited. This new approach achieves not only subnanometric roughness but also less subsurface damage and a remarkable improvement in controllability. [ABSTRACT FROM AUTHOR]

Modern medical implants are characterized by non-circular shapes, which is often challenging for economic production. Non-Circular-Rotary-Turning (NCRT) is a newly developed process for manufacturing non-circular cross-sections at high productivity and a high degree of geometric freedom. In this work, the basic process kinematics of NCRT are presented. A process design method is proposed and validated. The fundamental cutting conditions are examined using simulation and the cutting forces are studied experimentally. In an example of application, NCRT enables to reduce machining time by a factor of more than ten compared to a conventional process chain, resulting even in better surface quality. [ABSTRACT FROM AUTHOR]

Laser powder blown directed-energy deposition (DED) enables the flexible fabrication of functionally gradient structures. In the region where multiple feedstocks are blended, it is natural to apply the 'rule of mixtures'. Here, we show that by blending PH48S and 316L-Si steel powders using DED, the resulting material possesses lower yield strength but increased hardening and a secondary hardening regime not observed in the original alloys, invalidating direct interpolation between feedstock properties. Microstructural analysis of the mixed material revealed a solidification-driven multi-phase hierarchal microstructure. This result enables greater accuracy and increased design space in the co-design of materials and manufacturing processes. [ABSTRACT FROM AUTHOR]

Creasing and folding are fundamental steps in many manufacturing processes of multi-material paperboard packaging. The complex structure of these materials, which comprise layers of cellulose fibres, aluminium, and polyethylene, coupled with the growing complexity of packaging designs, make these process operations essential to ensure the required structural integrity for packaging as well as their functionality in daily life. This paper introduces an approach for modelling damage in paper-based sandwich materials by integrating fibre-based and cohesive numerical modelling techniques. The results prove the effectiveness of the proposed methodology, opening new possibilities for process design and optimization in packaging manufacturing. [ABSTRACT FROM AUTHOR]

In manufacturing, the essential product characteristics are often created through multiple stages. Coupling product data obtained through inspection and controllers based on decision models with prediction capabilities enables quality control loops, enhancing both feedback and feedforward mechanisms. This paper proposes a methodology to merge the formulation of feedback and feedforward quality control loops into a performance evaluation model for multi-stage manufacturing systems. This approach evaluates quality control loop impacts system-wide, aiding in configuring and reconfiguring quality gates. A case study illustrates how allocating inspection technologies and efficient decision models improves overall system performance through effective feedback and feedforward control loops. [ABSTRACT FROM AUTHOR]

Nowadays, the growing complexities of manufacturing processes and systems make it difficult to identify the root causes of critical deviations in performance. Conventional methods often fall short in capturing the multifaceted nature of these challenges, despite a wealth of diverse untapped manufacturing data. To harness the full potential of diverse data sets and transform them into a valuable asset to guide root cause exploration, this paper presents an innovative approach that combines multimodal predictive analysis and explainable artificial intelligence (XAI) to uncover insights into system dynamics. This work contributes to a paradigm shift in industrial decision-making regarding manufacturing diagnostics. [ABSTRACT FROM AUTHOR]

The paper investigates the self-organization of open, very large, and complex networks as design and manufacturing systems, proposing a model of network behavior that could improve design and control (optimize) the networks. Two metrics identify self-organization: entropy and the power law distribution of network member interactions. The network's behavior identification and model validation arise across two real-life networks: the Arduino Forum network and the EEVBlog Forum network, which include designers and producers/makers. [ABSTRACT FROM AUTHOR]

Safety concerns severely impede industrial adoption of emerging human-robot collaborative manufacturing systems. A human-centric anomaly detection framework rooted in decision theory is proposed for integrated safety and quality assurance—which is a marked departure from earlier, quality- or safety-exclusive process control approaches. The framework adapts deep learning models to track fast robot motions from surveillance cameras and provides real-time, risk-metered alerts of anomalous trajectory deviations with theoretical guarantees. Application to a shared human-robot assembly line suggests that the framework can outperform conventional statistical process control methods in reducing safety risks and allows for straightforward extensions to more involved manufacturing settings. [ABSTRACT FROM AUTHOR]

Reconfigurable manufacturing systems can rely on the collaboration of autonomous modular machines, dynamically planning production tasks and effectively satisfying demands. This paper introduces a decentralized knowledge-based framework, considering task uncertainties, module specialization, and reconfiguration constraints. By taking advantage of scenario reproducibility of simulations and utilizing deep reinforcement learning with multi-objective rewards, the proposed method enables machines to autonomously make intelligent decisions and collaborate on sequential, co-executed, or parallel tasks. Experiments are designed to evaluate the effectiveness of autonomous machines in planning tasks and the adaptability to uncertain situations in manufacturing operations, showcasing efficient module usage without compromising completion speed. [ABSTRACT FROM AUTHOR]

Flexible and rapidly adaptable automated production processes, e.g. with collaborative lightweight robots, are key aspects for the competitiveness of companies in globalised markets. However, software adaptation of the robot still requires specific programming skills. We have developed a human-centred programming by demonstration approach based on augmented reality to enable operators to intuitively adapt the robot programme. The developed hand-interaction model overcomes the challenge of object tracking during the assembly demonstration phase. This allows quick programme modifications by the operator using the head-mounted augmented reality device. The human-in-the-loop concept ensures a highly reliable and robust programming process. [ABSTRACT FROM AUTHOR]

Manufacturing processes are becoming increasingly data-driven. Integrating manufacturing data and process models in real-time, a digital twin (DT) may function as an autonomous and dynamic digital replica. This, in turn, may enable manufacturers to not only understand and monitor a process but also proactively control it in real-time or a product over its life cycle. This paper examines the DT concept and its evolution and presents a future DT framework. DTs' key components (e.g., process models) and implementation are focused on additive manufacturing, electrical discharge machining, and electrochemical machining. Furthermore, current challenges and future research directions are summarized. [ABSTRACT FROM AUTHOR]

Biologicalisation as the convergence of biology, engineering and information technology offers the prospect of dramatic step change scenarios for future innovative development. A large number of highly stimulating and potentially very valuable solutions, created over millions of years of evolution, are available in nature's solution space and waiting for application in technology. Transfer methods linking the biosphere and the technosphere are classified as functionalities which assume: bio-inspiration from nature, bio-integration combining biological and technological solutions, and bio-intelligence. The latter aims at achieving developments towards living systems based on the (reasonably) high level of appreciation of the environment, the system's capability and the specific task to be undertaken using decision making or self-reasoning. The use of large numbers of different sensors is involved together with sensor fusion strategies, self-healing and self-organising properties, along with functional integration. Moreover, to derive maximum benefit, the key enabling technologies will play a crucial role going forward. The impact on industry of unique and outstanding solutions will radically change the way manufacturing is performed today by building on new levels of latency, interconnectivity and communication. This paper aims at supporting the comprehension of these developments and revealing future trends, research needs and educational requirements in manufacturing science and technology as the biosphere and the technosphere converge to create the new levels of global sustainability. [ABSTRACT FROM AUTHOR]

The paper describes the state-of-the-art in modeling and simulation of surface texture and topography generation at micro and nano dimensional scales. Three main classes of manufacturing processes used for the generation of engineering surfaces are considered: material removal processes, material conservative processes, and material additive processes. Types of modeling techniques for the simulation of surface generation are reviewed and discussed including analytical models, numerical multi-physics models, and data-driven methods. After presenting the application of those modeling techniques for the prediction of characteristics and geometry of surfaces generated by different manufacturing processes, their performance, implementation, and accuracy are discussed. Finally, a roadmap for the realization of a complete surface generation digital twin in manufacturing is outlined. [ABSTRACT FROM AUTHOR]

Grinding plays an important role in ensuring the final machining quality in the manufacturing process of composite parts. Problems such as grinding damage, grinding wheel wear and loading undermine the grinding efficiency and quality. This review presents relevant research progress in the field of composites grinding in recent years from the aspects of material removal mechanisms, surface integrity, and advanced grinding technologies. It further discusses the common problems of composites grinding and summarizes grinding process strategies to suppress damage. It can provide an in-depth understanding of the fundamental mechanisms involved in composites grinding and solutions to the composites grinding problems. [ABSTRACT FROM AUTHOR]

Martensitic phase analysis in hardened gear hobbing (hard-hobbing) is crucial to function-oriented gear manufacturing process. A "weighted deviation factor" has been proposed to integrate machining-induced martensitic alterations into ferritic-martensitic grain analysis. It aimed to assess the martensitic phase using the orientation deviation angle of martensite lattice to the parent austenite to replace the traditional fraction-based assessment. Therefore, the martensitic phase integrity was evaluated with strain-phase hardening to correlate the gear surface function performance. The proposed factor incorporated the martensitic phase integrity as a function of the grain area, local misorientation, and crystallographic deviation, advancing phase-based hardened steel surface modification analysis. [ABSTRACT FROM AUTHOR]

In operations management, the benefit of simulating manufacturing processes with data-driven models has been proven in scenario-based capacity and performance analytics. The availability of data is typically not a barrier anymore, as process parameters can be accessed and modelled relatively easily, however, the system logic representation and extraction has remained challenging. In this paper, a systematic method is presented to build prediction models for a complex manufacturing system that extracts not only the process parameters, but also the routing and operating logic. The approach combines network analytics and statistical modelling techniques to automate the model building and scenario analytics. [ABSTRACT FROM AUTHOR]

Current digitalized manufacturing systems do not yet achieve the goal of smart manufacturing: precise control and agility under unexpected disruptions. Push-Pull Digital Thread is a solution concept to enable contextual data and knowledge exchange across operational and functional units in a manufacturing enterprise. The extraction of decision reasoning and functional information can be facilitated by Large Language Models processing information obtained from a decision maker at the point of decision. This concept shows a potential to address critical limitations in previous endeavours for smart manufacturing systems by building a semantically searchable and sharable knowledgebase in manufacturing systems and beyond. [ABSTRACT FROM AUTHOR]

Cyber manufacturing service, which connects end users with manufacturers over the internet, is significantly hampered by the lack of an automated part retrieval method. The state-of-the-art is focused on automatic shape retrieval, which does not consider manufacturing process requirements, such as material properties. This paper proposes a manufacturing process-aware part retrieval method using deep unsupervised learning that considers both part shape and material properties. Part retrieval results show that the proposed method yields 93.0% process and function class label matching precision, which outperforms the shape-only part retrieval model and supervised learning models trained with process, function, or both labels. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for control of overlay errors in photolithography processes in semiconductor manufacturing. It minimizes the largest overlay error across all measurement markers on a pattern layer, and this minimization is done for the worst-case scenario regarding bounded process bias and modeling noise terms. This large-scale robust optimization problem was formulated as a linear program which can be solved within seconds to generate optimal control commands. Simulations based on wafer data obtained from a major 300 mm semiconductor fab illustrate consistent and significant advantages of this approach over the benchmark control strategies. [ABSTRACT FROM AUTHOR]

High-performance closed-loop control systems are crucial to process stability and part quality in additive manufacturing processes. In this work, a simulation-guided feedforward-feedback control framework is developed for the directed energy deposition process to effectively control the melt pool temperature. The developed framework consists of two stages: offline iterative finite element simulation for feedforward control and online photodiode-based temperature monitoring for feedback control. The experimental results show that the feedforward-feedback control method can significantly improve the control performance when compared to the conventional feedback control method. [ABSTRACT FROM AUTHOR]

Industrial Product-Service Systems (IPS²) have been increasingly researched and practiced in a variety of fields and sectors. Nevertheless, such solutions are not as significantly implemented as expected by the CIRP keynote in 2010: it is not a dominant business of manufacturing companies today despite their economic and environmental advantages. One reason for this delay is assumed to be that the initial efforts were mainly on business and service when design was an afterthought. The promising digital technologies that have become easily implementable in practice will in the next years facilitate design and implementation of IPS² smartly to satisfy users and contribute to sustainability. This keynote analyses literature and practice in the last decade, aiming to propose the main characteristics of IPS² of the future and design processes adequate for IPS². The design process of both production systems for sustainability and high-value systems for sustainable development goals may need to be supported differently than today. The list of recommendations for future research on IPS² design is provided at the end of the paper. [ABSTRACT FROM AUTHOR]

This keynote paper mainly focuses on advancements of machining technology and systems for enhanced performance, increased system integration and augmented machine intelligence, critically hinging on new sensors, sensor systems and sensing methodologies being robust, reconfigurable and intelligent, while providing direct adoption and plug-and-play use in industrial practice. One chief novelty is given by the key enabling technologies of Industry 4.0 where integration of sensing systems in manufacturing plants is a cornerstone for transforming conventional manufacturing concepts into digital manufacturing paradigms. Application examples to industrial processes, future challenges and coming trends in machining monitoring are shown. [ABSTRACT FROM AUTHOR]

The simulation of manufacturing processes has significant importance. The research and development of metal forming simulation started in the 1960s from the elastoplastic analysis of a simple plastic deformation, and it now covers a wide range of forming processes. The accuracy and applicability of metal forming simulation have significantly progressed, driven by the development of plasticity theory and numerical methods such as the remeshing technique and contact analysis algorithm. Now the targets of metal forming simulations are undergoing a transition from the macroscale analysis of deforming bodies to coupled analyses of deformations of deforming bodies and tools, and multiscale analyses of microstructure and texture. Past achievements of metal forming simulation show that it has reached the level of 'visualizing forming phenomena', but it will continue to evolve in the digital era, impacting the digital society and factories of the future, where machines work autonomously without human intervention. Emergent technologies require advanced materials, augmented reality, and, of course, metal forming simulation. In this paper, we reinforce the role of simulation as a means of performing computational (virtual) experiments and as a tool for the high-fidelity numerical visualization and quantification of unknown, unmeasurable, and invisible phenomena in formed components and their assembly. We will also discuss simulation–machine interactions, such as online simulation with process operation, to realize the triad of 'process operation – data – simulation' in the near future. [ABSTRACT FROM AUTHOR]

There is a strong demand for automating the rough polishing process in plastic-mold manufacturing. In this study, with the active end effector being capable of fast force control and dynamic spindle control, a robot polishing control system based on a macro-micro-mechanism was built, which controls all parameters related to Preston's law and can be linked with computer-aided manufacturing. Based on the extended Preston equation, a polishing control algorithm that achieves uniform surface quality and uniform removal depth was proposed. The spherical rough polishing test on carbon steel demonstrated the efficacy of the proposed robot polishing control. [ABSTRACT FROM AUTHOR]

A macroscopic ductile-to-brittle transition in chip formation with ductile gummy metals, arising from 3.5 to 100 nm thick organic films on the workpiece surface, is demonstrated. The principal characteristics of the phenomenon, with annealed aluminum, are change in the flow mode from one dominated by large-strain plasticity to one controlled by fracture; and up to 70% reduction in cutting force. This embrittlement has important benefits for machined surface quality – nearly an order of magnitude reduction in roughness, > 50% reduction in residual plastic strain, and smaller hardness change. Implications of the phenomenon for material removal processes and beyond are discussed. [ABSTRACT FROM AUTHOR]

Process specific actuators and sensors embedded in the tooling can enable closed-loop control of product properties in manufacturing processes to achieve desired final component characteristics. Alternatively, actuation conducted by the machine tool used and sensors positioned within the machine, i.e., outside of the tool, could increase robustness and reduce investment and installation costs for closed-loop control systems. This contribution presents and compares different closed-loop control strategies for deep drawing and demonstrates the advantages of machine based actuators and sensors in experiments and simulations. [ABSTRACT FROM AUTHOR]

Automation and technological innovations pushed manufacturing companies to integrated plant configurations, where sub-systems are highly intertwined, though easily reconfigurable thanks to modularization. Frequent reconfigurations change the way sub-systems interact amongst each other more often than in the past. However, in large manufacturing systems digital sub-system models may be still ran independently, limiting their support in decision-making. This work proposes a methodology for the hybrid digital modelling of large manufacturing systems, where hybrid stands for multi-technique modelling, to achieve: (i) reduction of modelling complexity, (ii) portability, (iii) optimal modelling choice, (iv) hybrid modelling integration. An industrial case study in the electrical equipment sector shows the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

The benefits of Industry 4.0 are limited by the large computational requirements of ever-larger digital models of complex production systems. A complementary learning paradigm is thus proposed to cultivate knowledge in a team of machines and humans that represents the key to a high-performance manufacturing system. Two types of knowledge are created using light-weighted neural networks and meta-learning: general knowledge of tasks and specific knowledge on collaboration with humans given few interactions. AI-based teaming strategies are designed to enable machines to leverage human expertise in making decisions using local communications that make intricate sensor systems and expensive computation unnecessary. [ABSTRACT FROM AUTHOR]

Automated real time quality monitoring is one of the key enablers for future high-speed production. In this research, an in-process monitoring procedure based on computer vision inspection and deep learning is proposed to indicate the tool and part quality during soft tooling injection moulding. Multiple types of injection moulding defects can be detected by the proposed method. Geometrical dimensions of the part can be measured simultaneously and the uncertainty can be quantified. Based on the obtained data, automated quality evaluation can be achieved in-process and a decision signal can be sent back to the injection moulding system for process adjustment. [ABSTRACT FROM AUTHOR]

Utilizing real-time position information of individual factory objects is a promising field of action in manufacturing systems. For realizing that, different types of real-time locating systems (RTLS) are available which differ according their inherent characteristics, performance and, thus, their feasibility for value adding manufacturing use cases. The paper introduces an innovative RTLS which utilizes optical AI enhanced sensors to detect and track objects. Detailed technical analyses also in comparison with established tag based ultra-wideband (UWB) RTLS underline the general feasibility and good performance. Finally, the capability profiles of those different RTLS technologies were brought together with the requirements of specific manufacturing use cases in order to derive favourable application fields. [ABSTRACT FROM AUTHOR]

Human-robot collaboration (HRC) allows seamless communication and collaboration between humans and robots to fulfil flexible manufacturing tasks in a shared workspace. Nevertheless, existing HRC systems lack an efficient integration of robotic and human cognitions. Empowered by advanced cognitive computing, this paper proposes a visual reasoning-based approach for mutual-cognitive HRC. Firstly, a domain-specific HRC knowledge graph is established. Next, the holistic manufacturing scene is perceived by visual sensors as a temporal graph. Then, a collaborative mode with similar instructions can be inferred by graph embedding. Lastly, mutual-cognitive decisions are immersed into the Augmented Reality execution loop for intuitive HRC support. [ABSTRACT FROM AUTHOR]

The process behaviour of bronze-bonded diamond grinding wheels depends on the selected bond composition and the sintering parameters. Understanding these dependencies is the key to a knowledge-based manufacturing process for grinding wheels. In this study, the wear behaviour of different bond compositions and sintering parameters is investigated. It could be shown that the predominant wear mechanism is mainly grain flattening and that it depends on the critical bond strength. Finally, these findings were used to analyse the workpiece quality in dependence of the variously manufactured grinding wheels. This enables a new approach for the production of load adapted grinding wheels. [ABSTRACT FROM AUTHOR]

The last decades have seen several attempts to develop Severe Plastic Deformation (SPD) processes to manufacture parts with Ultra-Fine Grained (UFG) microstructure without additional thermal processing. However, they remained mostly focused on producing small components, often in the micro-scale range, thus limiting the technological and environmental impact of SPD techniques. The paper introduces a new approach to produce large size UFG metal sheets which main innovation lies in a constrained flowforming process that allows obtaining large deformations under high hydrostatic pressure. Metal sheets with isotropic grain distribution and average grain size of 4 μm were manufactured by this process chain and their mechanical properties assessed. [ABSTRACT FROM AUTHOR]

This paper presents the enhancement of the surface measurement ability of lateral-scanning white-light interferometry (LSWLI) for applications with industrial environments including fast-rotating objects and vibrations. For this purpose, a LSWLI with an integrated laser-speckle-based measurement of the lateral displacement is realised, which enables a vibration compensation and a decoupling of the measurement speed from the surface speed. The approach is validated and characterised in a test setup meeting the measurement conditions of a rotating sheet metal roller during surface reconditioning. The promising results open up the possibility for a high-resolution optical inspection of component topographies close to industrial manufacturing processes. [ABSTRACT FROM AUTHOR]

New deal of Friction Stir Consolidation (FSC) is its evolution from Recycling technique towards Upcycling. In this paper, the potential of FSC to manufacture Functionally Graded billets is proved. Processing chips of two different aluminium alloys (AA7075, AA2011-T3), graded hardness distributions were obtained along the longitudinal direction of the manufactured billet. Material flow was analysed by EDX analyses and numerical simulations; mechanical properties were assessed through hardness measurements. The influence of material's position, mass fraction of each material and process parameters was considered. Results reveal that FSC offers a proper control in the design of billets with graded properties. [ABSTRACT FROM AUTHOR]

Gear skiving is a highly productive manufacturing process for internal gears. Due to its challenging cutting conditions often insufficient tool life is achieved and localized wear occurs. There is a lack of tool parameters in process design that allow for an uniform and comparable characterization of the process kinematics and tool geometry. In this paper, a new method for calculating process kinematics and tool profile based on parameters of profile-shifted conical gears and an approach for tool load homogenization are presented. The high potential of the methods is demonstrated by comparative tool life tests with an improvement of 300%. [ABSTRACT FROM AUTHOR]

This paper proposes a methodology that can be used to assess the effects of variations in the process parameters on the energy consumption of a Cold Metal Transfer (CMT) additive manufacturing process. The analysis was carried out at the process level and then extended to cradle-to-gate system boundaries. A thin-walled component was considered as a demonstrative case study. The results demonstrate that any variation in deposition process parameters (namely, the wire feed speed and the travel speed) affects not only the energy requirements related to the deposition process itself, but also the material deposition efficiency and the cradle-to-gate cumulative energy demand. [ABSTRACT FROM AUTHOR]

In the last few decades, metal-based composites and related manufacturing methods have attained a significant research attention thanks to the possibilities they offer to tailor both the material properties and the part in-service performances. A variety of metal-based composite parts is available for commercial applications since more affordable and robust manufacturing processes and quality control techniques have recently overcome many challenging technological issues. The paper aims at describing the forming processes applied to metal-based composites, with particular emphasis on the process features, part obtainable characteristics, and modelling issues for a convincing design and optimization of the process itself. The most recent progresses and challenges are illustrated in detail, including innovative materials and processes that are emerging to answer the requirements of advanced engineering applications as well as new modelling techniques and current approaches to face economic and environmental issues. [ABSTRACT FROM AUTHOR]

Modern ultrafast lasers are enabling better operative performances in micro and nano-fabrications of materials, benefited from their ease of use, robustness, and reliability. The purpose of this paper is to bridge the gap between the knowledge of ultrafast optics and the modern industrial applications. The paper introduces main phenomena in ultrafast laser-matter interactions by reviewing relevant theoretical models and simulation techniques. The operation of ultrafast lasers is based on nonlinear optics phenomena, fully described only in the framework of quantum-mechanics. Current trends in the development of modern ultrafast system are given. It also presents a review of the latest advances in ultrafast laser-based manufacturing processes, some of the most interesting industrial applications, and a discussion on future trends and challenges. [ABSTRACT FROM AUTHOR]

In the past few decades, there has been considerable advancement in developing and testing structured and textured cutting tools for different machining operations. This paper not only presents a review of the state-of-the-art in manufacturing processes to structure and texture surfaces of cutting tools for machining applications but also identifies the strengths and weaknesses of utilizing structured or textured rake and flank faces as well as other important functional surfaces of cutting tools. This includes an assessment of the relevant texture geometries and microscale structures and their applicability and/or limitations for the improved chip material flow and contact at the chip-tool interface, reduced forces, dynamic deflections, and friction, improved anti-adhesion and tool wear, and enhanced debris management, lubricant, and coolant utilization. This manuscript includes contributions from many research groups in academia who closely work with industry and the content presented herein is expected to provide an organized and comprehensive narrative on current advances, capabilities, and challenges in developing and implementing optimum texture and structure design on cutting tool surfaces with some guidance for future directions. [ABSTRACT FROM AUTHOR]

This keynote paper gives an overview of emerging technologies of feature-based characterisation, for surface topographies having features. It is complementary to conventional surface characterisation using texture field parameters. An original concept, the feature spectrum is proposed to organise surfaces, in order to help select the appropriate characterisation for different types of surface topographies and to achieve a more direct relationship between characterisation, manufacturing process and surface function. The keynote paper focuses on fundamentals and the state of the art for feature-based characterisation technologies. Applications of feature-based characterisation are illustrated and discussed. Guidelines for future industrial applications are laid out, and considerations for future challenges are addressed. Surfaces, Micro structure, Feature-based Characterisation. [ABSTRACT FROM AUTHOR]

Water-based manufacturing processes are under development for greener manufacturing of lithium ion batteries but their environmental impacts are unclear with new introduced materials and a large consumption of deionized water. We report a life cycle assessment (LCA) study on the water-based manufacturing of the most popular NMC-graphite battery pack configured with 57 kWh capacity. A life cycle model has been developed based on experimental and mathematical studies of the water-based manufacturing processes. Per kg battery pack produced, the water-based manufacturing can reduce the manufacturing energy by 43% and lower the cradle-to-gate life cycle impacts by 0.6%∼88% over conventional battery manufacturing. [ABSTRACT FROM AUTHOR]

Gear skiving is a high-performance gear manufacturing process, whose design typically requires numerical models to calculate the multivariate cutting conditions. Since simulation software for gear skiving is still commercially hardly available, two-dimensional approximations have widely been used by gear manufacturers to calculate the extreme values of cutting conditions. In this work, a three-dimensional model for the calculation of cutting speed, rake angle and uncut chip thickness extreme values is presented and validated by penetration volume simulations. The comparison with the two-dimensional approaches shows a significant benefit in model accuracy over a wide parameter range and its suitability for practical applications. [ABSTRACT FROM AUTHOR]

Digital twins (DTs) offer the potential for improved understanding of current and future manufacturing processes. This can only be achieved by DTs consistently and accurately representing the real processes. However, the robustness and resilience of the DT itself remain an issue. Accordingly, this paper offers an approach to deal with uncertainty and disruptions, as the DT detects these effectively and self-adapts as needed to maintain representativeness. The paper proposes an intelligent agent-based architecture to improve the robustness (including accuracy of representativeness) and resilience (including timely update) of the DT. The approach is demonstrated on a case of cryogenic secondary manufacturing. [ABSTRACT FROM AUTHOR]

Digitalization is crucial for increasing the productivity of manufacturing systems and processes, where model-based systems engineering is a key engineering discipline to support related design and planning activities. However, knowledge used in these activities is not sufficiently captured through exhaustive simulation-based searches on design spaces. This study proposes a design space model based on General Design Theory to express such knowledge using the properties of topological spaces. A simulation-based production planning case study demonstrates computation of a design space from simulation experiments using inductive and deductive reasoning, and formulation of complex design options for production plans to meet performance criteria. [ABSTRACT FROM AUTHOR]