Search

Additive manufacturing processes for the production of large structural components, such as wire arc additive manufacturing (WAAM), offer great manufacturing potential due to their flexibility and design freedom, e.g. for the automotive industry. In order to achieve the desired surface and properties of the surface zone, additive manufacturing is usually followed by mechanical finishing. In this paper, the influence of the process parameters during WAAM and deep rolling (DR) on the residual stresses and the lifetime of AlSi12 components is investigated. Knowledge of the interactions between the process parameters in WAAM and DR as well as their effect on the surface zone properties and the application behavior is elementary. This enables the prediction of the component properties and quality. With the help of the appropriate selection of the process parameters, the residual stress state and the service life can be increased in such a way that components with high fatigue strength can be manufactured. This results in an average increase in service life of up to 17.8 times. [ABSTRACT FROM AUTHOR]

Owing to the unique technological merits of additive manufacturing (AM), design for AM, particularly eco-design for AM, has been gaining attention in improving the sustainable performance of AM-fabricated (AMed) parts. The main challenge in harvesting potential sustainability benefits is how to capture the impact of design on sustainable performance. Though several existing studies adopted quantitative evaluation on AM sustainability and investigated the relationships between design information and sustainability information of AMed part, the sustainability information is still unavailable in the design phase. This hardly guides eco-design for AM in practice. To support the increasing industrial applications of AM, this paper illustrates related knowledge, that is, material-process-structure-ecoProperty (MPSeP) relationships to connect design and sustainability information in eco-design for AM. An ontology-based method is proposed to model the MPSeP relationships of the AMed part in a structured way. An example of an AMed hydraulic valve body was used to demonstrate the MPSeP modeling process. It is discussed that how the constructed model effectively assists AM designers through providing eco-design recommendation, and enables design software tools to perform sustainability analysis towards eco-design for AM. [ABSTRACT FROM AUTHOR]

The resource consumption of products and production processes, regarding energy and material, is the most important parameter in assessing economic and ecological sustainability. Existing approaches for measuring resource consumption calculate key performance indicators, such as the carbon footprint, from which actions can be derived. The data acquisition, processing, and visualization are usually complex and individually adapted to the products and production machines. This paper presents a method to capture the resource consumption of a product and production machine with low effort and in a targeted manner to calculate the carbon footprint subsequently. The approach's novelty lies in linking any sensor technology with a cross-platform application, integrating existing data sets, and incorporating gamification techniques. Gamifying the process, users engage more with the data, leading to higher awareness and deeper insights. The application offers an intuitive user interface displaying resource consumption by calculating the environmental impact of the production. The live data integration allows for immediate monitoring of the effect of adaptions to the production process, that helps to create a better understanding of contributions to resource consumption. The use of the application is highlighted in a case study of industrial complexity. [ABSTRACT FROM AUTHOR]

The environmental impact of new products and production processes is one of the most important indicators of the current time. Many methods exist to estimate ecological metrics, such as the Product Carbon Footprint (PCF) in the individual product development phases with stand-alone software. However, methods to integrate the PCF in the entire process chain with the possibility to interact in the process are missing. This paper presents a new approach to measuring the ecological impact of an Additive Manufacturing production process, exemplified by the Material Extrusion (MEX) process. The novelty of the approach lies in implementing a single software for machine control, processing, and visualization of sensor signals, parameter variation, and reporting functions to enable comprehensive PCF management. The workflow includes a model-based prediction of the PCF based on the G-code, live monitoring during the production phase, and a subsequent automated evaluation at a central interface. Critical points can be identified, and approaches for optimizing the MEX process can be designed. Uncertainty evaluation of the PCF based on the combination of uncertainty of the sensors and the Life Cycle Assessment is included in the method. The developed prototype software can be used in the design phase for prediction and in the process phase for optimization, enabling seamless PCF management for the MEX process. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) technologies give more and more design freedom to designers and engineers to define and fabricate highly complex functional geometries and material compositions by using advanced Design for AM (DfAM) methods, such as generative design, lattice structure configuration, and bio-inspired design. However, it is still hard for designers to realize a complex design with ensured manufacturability via the use of a single DfAM method, especially for some complex functional lightweight structures. To fully exploit the advantages of AM processes, this paper proposes a new hybrid generative design method, which combines many existing DfAM methods and printing preparation optimization methods. Firstly, functional features are designed and analyzed with the use of AM processing knowledge and numerical simulation. Then, lattice structure configuration is used to achieve a lightweight and qualified part consolidation. In this process, to avoid the cumbersome AM preprocessing stages, support point determination and bio-inspired support generation methods are integrated into the part consolidation design stage. Finally, multiple designed volumes, realized by using different methods, are combined into a complete single structure. To demonstrate the applicability of the proposed method, a design case of a complex functional hydraulic component is presented at the end of the paper. [ABSTRACT FROM AUTHOR]

In comparison to conventional manufacturing technologies, additive manufacturing (AM) offers great design freedom, the integration of functions into components, new lightweight design concepts and high material efficiency. In aerospace and turbomachinery, this technology is increasingly coming into focus, especially the laser-based powder bed fusion of metals (PBF-LB/M) process. PBF-LB/M is already used for some aerospace components, which are often exposed to high thermal and mechanical loads. Dependent on the component geometry, support structures are required for AM, which then usually have to be removed by machining. One suitable support structure is the use of material with specifically induced porosity. This ensures good heat dissipation and thus homogeneous component properties, high retention forces and short process times in PBF-LB/M. However, the machinability of porous, additively manufactured material has hardly been researched so far. One preliminary investigation of milling porous, additively manufactured Inconel 718, though, showed significantly poorer machinability of the porous material compared to the dense material. To further examine this phenomenon, this paper presents the results of fundamental machinability studies with porous, additively manufactured Inconel 718 in orthogonal cutting. The investigations with tungsten carbide cutting tools on a special fundamental test rig include the analysis of the cutting force, the chip geometry, the chip temperature and the surface quality. The research results provide explanations for the poorer machinability of the porous material and derived approaches for improving the machinability in future studies. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) processes can now produce components with homogeneous mechanical properties, but the physical phenomena involved during the build make AM surfaces not always suitable to be used as-is. This paper first focuses on the properties of as build AM surfaces and highlights the need to employ post-processing techniques to improve these properties and meet the function requirements. Besides High Speed Machining, which is the usually chosen process, others can be interesting candidates. Waterjet finishing and laser polishing can be employed to smooth peaks and valleys that characterize AM surface and to remove unmelted particles. In addition, these processes are also used for surface texturing. Friction Stir Processing promises a high productivity. The results of several experimental campaigns carried out in the laboratory are provided in this paper. The major interests and drawbacks of the studied processes are identified with the view to define performance windows. [ABSTRACT FROM AUTHOR]

In additive manufacturing with metallic base material, Laser Powder Bed Fusion (L-PBF) is an industrially established technology for tool-free production of complex and individualized components and products by applying material layer by layer. In addition to in-processing, the L-PBF process chain consists of several other process steps in pre- and post-processing. A holistic view of the additive manufacturing process chain shows that many process steps currently involve non-value-adding (NVA) operations and that there is generally great potential for reducing throughput times and costs. Due to the great importance of efficiency in industrial manufacturing process chains, this paper proposes a concept for analyzing the L-PBF process chain and deriving measures to eliminate NVA operations and increase the efficiency of value-adding (VA) operations. First, this paper presents a methodology for identifying VA and NVA operations that encompasses the entire chain. After the process mapping, the process steps are divided into sub-tasks to subsequently analyze them with regard to the level of automation. This analysis is the basis for selecting the appropriate automation strategy and optimizing the individual process steps by applying automation-aligned lean production methods to increase the proportion of VA operations. The potential for a significant increase in the productivity of the additive manufacturing process chain is demonstrated through systematic analysis and requirements-based optimization of the level of automation. The approach is structured in an adaptive manner so that, beyond the possibilities of lean production and automation, other optimization alternatives from further disciplines, such as digitization and networking, can be integrated. [ABSTRACT FROM AUTHOR]

COVID-19 and global crises/events are driving governments to rethink their national manufacturing strategies. The drastic change of societal conditions has exposed our reliance on a constrained set of production practices. Furthermore, the future manufacturing landscape indicates - supply chain crises, trade agreements and natural disasters - a high level of volatility which requires a response that is far from being achieved. While these emergent challenges have called the efficacy of established practices into question, new manufacturing technologies, such as Additive Manufacturing (AM), present the capability to provide a solution. One proposal is agent-based brokering of AM which could be a method for tackling local, regional, national, and international production needs. However, to achieve the reality of brokered AM, it is imperative that the diversity of AM capability is considered. Diversity that existing homogeneous modelling of AM and manufacturing systems rarely consider or capture. This paper conceptualizes the reality of AM systems and elucidates parameters that are necessary for successful modelling and subsequent co-ordination. Having presented the required parameters the paper continues to discuss requisite levels of abstraction, suitable performance metrics and the role of humans in agent-based manufacturing systems. [ABSTRACT FROM AUTHOR]

AVL List GmbH (AVL) is the world's largest independent company for development, simulation and testing in the automotive industry, and in other sectors. The business unit Instrumentation and Test Systems (ITS) is focusing on the development, realization and manufacturing of high-precision measurement, development and test solutions for automotive components and systems. While the focus of in-house production at ITS is on assembly processes, manufacturing of the required components is mainly outsourced to external suppliers. With the foundation of the AVL Additive Manufacturing (AM) Initiative in 2017, manufacturing was partially in-sourced again. Since then, several activities have been conducted to successfully integrate AM as enabling technology. This paper presents how AM was methodically implemented and how AM contributes to the ITS value chain. For research and (pre-) development, Design for Additive Manufacturing (DfAM) enables novel and innovative measurement concepts with advanced functionalities. Feasibility studies, including experimental results on key performance indicators, are described and the proof of concept is discussed. Going further, design departments benefit from rapid realization of prototypes with in-house AM production. Especially since the Covid-19 pandemic, long delivery times from external suppliers influence the development process. This paper shows how AM has contributed during this phase in terms of speed, innovation and costs but also the importance of relevant know-how to start an AM transformation. Besides rapid prototyping, the existing AM machines already produce 65 serial parts for AVL's measurement devices. First results show that not only delivery times were reduced by 80% but also substantial cost savings of up to 40% - compared to the external purchasing - could be achieved. With that in mind, the in-house AM production ecosystem will be further expanded to bring value and manufacturing know-how into the company. [ABSTRACT FROM AUTHOR]

Models of distributed agent-based Additive Manufacturing (AM) systems have suggested that considerable productivity, reactivity, and resiliency gains can be realised. However, there remains scepticism and real-world validation is required to demonstrate the benefits, practicalities, and challenges of implementing agent-based manufacturing systems. It is only then that potential gains can be evidenced and the Return on Investment fully appraised. This paper discusses the underlying communication architecture required for the creation of a hardware technology demonstrator that enables the evaluation of distributed, agent-based, AM. Three architectures to create the desired network (Host-Client, Peer-to-Peer, and Digital Shadow) are discussed, with a focus on implementation and operational factors. The paper continues by describing the future development needed for the creation of a demonstrator aimed at exploring the ease of adoption of agent-based approaches and the potential for integration into existing AM workflows. The planned demonstrator is to be implemented at the University of Bristol to co-ordinate production across multiple sites in order to support their education and research activities as well as provide a platform for public and industry engagement. [ABSTRACT FROM AUTHOR]

This study presents and discusses the possibility of using 3D printed polymer tools to achieve a flexible metal forming production line. An example is given of the design of a sheet metal part from tool printing to the actual forming and evaluation of the achieved precision of the formed part. The time spent by the engineer/operator during the full process cycle is documented and compared to the time it would take to make the corresponding tool by conventional metal machining. The time savings revealed in the paper are relevant for a low number of parts to be formed in a flexible manufacturing environment, while it is less relevant in mass production where metal forming is conventionally an attractive process. Besides the time invested by the engineer/operator, it is also important to keep the costs of the tools at a minimum in flexible manufacturing. Therefore, the paper also presents a comparison of the costs for printed tools as compared to conventional tools made from metal machining. This analysis considers the cost of raw materials, machine time and electricity consumption. The environmental aspects of metal forming are also considered, with the lubricating oils and greases typically used to improve frictional conditions being replaced by the polymers, which themselves have anti-friction properties. Finally, the recyclability of the tools is significant when they are only used to form a few parts. Different types of polymers and printing strategies are discussed in relation to recyclability and compared to the alternative metal tools. [ABSTRACT FROM AUTHOR]

Additive Manufacturing with Continuous Fibers (AM-CFRP) results in products with high strength/stiffness at low mass. As such the process holds great promise to be part of obtaining goals in fuel economy for automobiles and aircrafts. AM is able to create products with highly complex 3D geometries, not possible with other production processes. However, there are still many drawbacks to AM process variants with continuous fibers like shape limitations and high void content and low delamination resistance in the printed product. At the University of Twente research has been dedicated on using commingled yarns as a feedstock for AM-CFRP. Before using the yarn, pultrusion is used to transform it to a consolidated filament, which allows for using a FDM-type deposition setup in the AM-CFRP process. The resulting filaments thermal and mechanical properties differ from standard AM-CFRP feedstock, affecting process settings and deposition results. This paper describes the research on the interaction between feedstock, nozzle design and print settings on microstructure, mechanical performance and dimensional stability of extruded feedstock and printed products. It is shown that nozzle designs developed for thermoplastic materials function suboptimal and that the nozzles to be designed should be conceptually different regarding shaping, heating and depositing the filament. [ABSTRACT FROM AUTHOR]

Modern manufacturing requires businesses to be adaptive in order to remain operational within a disruptive environment. One strategy towards increased responsiveness is the adoption of additive manufacturing technologies. However, the proper introduction of additive manufacturing into existing value chains requires a broad knowledge base. Potential non-expert adopters searching to obtain such knowledge are faced with an overwhelming amount of information, typically unstructured, regarding specific value transformation processes required to achieve the respective aim. For example, value transformations afforded by additive manufacturing range from technical, social, and environmental to economical. It is proposed that a map which systematizes and simplifies the various capabilities and their enabling processes could be applied as an effective knowledge transfer medium. This paper addresses the enabling of potential adopters to navigate and familiarize themselves with the core technical capabilities of laser powder bed fusion that allows for part value transformation. An input-process-output approach was followed to group and map capabilities according to fundamental laser powder bed fusion process steps. Whilst providing a holistic view of the capabilities and processes involved, the map serves as a tool for identifying the specific capabilities, its elements, their enabling processes and combinations required to achieve the desired value transformation. Examples from in-house work, spanning different industries, were used to demonstrate the usefulness of the proposed map. Results are presented as a summary in a table format. The simplified capability map proved beneficial to identify the combinations of capability elements used in the respective examples towards developing a solution. This contributes to reducing the complexity of identifying initial additive manufacturing process requirements for a potential adopter. [ABSTRACT FROM AUTHOR]

The direct additive manufacturing, such as Direct Ink Writing (DIW), of silicone parts holds cost and complexity advantages. However, for extruding strands of low viscosity heat curing silicone rubbers, a build plate temperature of up to 90°C is used, which comes with the challenge of early vulcanization inside the printhead. Thus, this paper presents a thermoelectric cooler for universal printheads. At a build plate temperature of 90°C it prolongates vulcanization by 198.5 % (∆t pot life = 508.8 s), which allows a reduction of print speed for higher quality. Additionally, the influence of external temperature is reduced and the viscosity can be controlled. [ABSTRACT FROM AUTHOR]

One of the major advantages of additive manufacturing (AM) is often cited as freedom of design. In comparison to traditional manufacturing processes, this is valid because an increase in geometric complexity is not equally followed by an increase in costs. However, there are numerous challenges in this regard, since the proposed freedom of design is often presented in an undifferentiated manner, neglecting the various processes and principles of this technology. A comparison of different AM-processes (e.g., powder bed fusion and material extrusion of polymers) shows that the geometry to be generated sometimes has significant effects on the production effort in terms of building time and costs. However, these effects are insufficiently explored at the present stage. This paper addresses the aforementioned issues in order to evaluate the impact of geometric complexity on the manufacturing process. The methodology is demonstrated using the process of selective laser sintering (SLS) for polymers. The study is conducted with a thermoplastic polyurethane (TPU) powder. The main focus lies on the analysis of geometrical influencing factors, parameters of the manufacturing process as well as resulting production efforts. Building on these theoretical findings, the relationships are proven experimentally. For this purpose, a variety of complex geometric shapes are produced with two different SLS systems in order to analyse generation time. While maintaining typical component criteria such as height and volume, it is shown that the generation time can be changed by more than 30 % by varying the complexity. Compared to existing work, new insights into the productivity of the manufacturing process are gained regarding component design, component orientation as well as the layout of build jobs. [ABSTRACT FROM AUTHOR]

The design freedom of additive manufacturing (AM) enables not only complex geometries to improve the performance of the component, but also allows the integration of features to enhance subsequent process steps. Consequently, design for AM, but also design for necessary subsequent process steps, e.g. machining, should be taken into consideration. This includes adapted support structures, clamping and probing geometries. This paper addresses these challenges and proposes a framework of design rules for the additive-subtractive process chain (ASM) with the focus on machining. The subtractive processes of sawing, drilling, reaming, and milling are examined. In contrast to conventional allowance and support structure definitions, productivity improvements are achieved with design for ASM features, included during the design stage. [ABSTRACT FROM AUTHOR]

Metal additive manufacturing (AM) enables the production of complex and individualized designs. However, most AM parts require postprocessing with subtractive manufacturing processes, which can account for a significant percentage of the total manufacturing cost of an AM part. Positioning and clamping of complex AM parts within post-processing machines often lead to increased prestresses and reduced tool accessibility. One concept to address this problem is the integration of clamping interfaces in the part. But this leads to the new design challenge of optimal and material-saving placement of clamping interfaces on the part. To overcome this challenge new design tools are desired that facilitate this work and automatically generate the design of clamping interfaces. A recently developed clamping system uses bolts that are directly printed onto parts as clamping interfaces. These printed bolts and the clamping jaws of the system enable a unique spatial positioning and rigid clamping of AM parts for post-processing. This work introduces a design workflow that supports the positioning of bolts using a knowledge-based engineering (KBE) approach. The workflow thus allows the user to easily find a feasible clamping configuration and automatically generates the geometries of the bolt-shaped clamping interfaces. As input, the workflow uses the part geometry and an AM build direction. During the workflow, the user can modify the position of the clamping system relative to the part and find feasible positions for bolts. The bolt geometries are then generated automatically, and the part can be exported. This paper describes the workflow in detail and provides a vision for future developments of the tool and its potential for the AM process chain. [ABSTRACT FROM AUTHOR]

This paper improves on the performance of the Deep Learning Additive Manufacturing driven Topology Optimization (DL-AM-TO) approach that was proposed in [4]. DL-AM-TO is a data-driven generative method that integrates the mechanical and geometrical constraints concurrently at the same conceptual level and generates a 2D design accordingly. Furthermore, DL-AM-TO tailors the design's geometry to comply with manufacturing criteria, which facilitates the designer's interpretation phase and prevents him/her from getting stuck in a loop of drawing the CAD and testing its performance. The geometry needs less support structure and hence is printed faster. Consequently, DL-AM-TO accelerates the Design for AM process. [ABSTRACT FROM AUTHOR]

Lattice structures are an adaption of the microscopic crystalline structures in chemistry to the mesoscopic design space of material science and mechanical engineering. They are structures created through the tessellation of unit cells in three dimensions. They present an appealing alternative to solid materials and other geometric design due to the ability to directly customise their performance and behaviour through modification of their design parameters – enabling a greater range of possible material properties when compared to solid materials – as well as showing multifunctional capabilities. While Additive Manufacturing has enabled the production of these structures and thus a resulting increase in research, a similar level of adoption has not been seen in industry. A key factor for this is the current lack of a methodology by which lattice design parameters can be selected based on the performance required from the component. To facilitate this selection, it is integral to understand the relationship between the lattice design parameters and the resulting material properties. In this paper, empirical models are developed by using several lattice types to quantify the relations between lattice design and materials. Test results show that the developed models accurately predict the relations between materials and lattice structures for designers to incorporate them into their designs. [ABSTRACT FROM AUTHOR]

Engineering Design and Additive Manufacturing (AM) technologies play a significant enabling role for business models with a proposed contribution to lifecycle management strategies for extending product life and enabling more efficient production via the digitisation of product design and production processes. This paper demonstrates a strategic approach for reverse engineering (RE) to support new business models capitalising on economic and organisational contexts such as on-demand and decentralised manufacturing and digital automation without the requirement for tooling. Additionally, it integrates a decision-making tool to evaluate the strategy of the various RE processes. This study provides an informed comparison between workflows of non-contact data acquisition using photogrammetry, metrology grade laser scanner, and 3D re-modelling using scanned data as a reference. This approach creates a digital thread for end-of-life (EOL) parts and enables remanufacturing using AM processes. The workflows are documented and assessed based on the manufacturing triangle of cost, time, and quality as application-relevant design pillars for evaluating the suitability of the business case proposed, namely, remanufacturing of parts for classic car restoration projects. The calculated and measured results based on the three different approaches were assessed through a Multi-Criteria-Decision-Making (MCDM) process, more precisely, the Analytic Hierarchy Process (AHP). The outcome of the study shows the general applicability of the proposed workflow. The combination of the measured and calculated data of the remanufactured parts and the decision-making tool provided the following ranking of the proposed work to the practitioner: (1) laser scanning, (2) 3D modelling, and (3) photogrammetry. [ABSTRACT FROM AUTHOR]

While additive manufacturing (AM) offers the ability to produce complex, customized structures, it still faces limitations when it comes to printing large structures with different material sections. For the production of big-sized structures or products, traditional processes still hold the advantage in terms of cost, manufacturing time, and material compatibility. Additionally, identifying suitable parts for AM, particularly for a single AM process, can be challenging, especially those with large sizes and different material compositions. This paper proposes a modular hybrid AM solution that combines different AM processes to address the challenges associated with large-scale structure printing in AM. The study presents a case in which a metallic powder-bed-fusion process and a stereolithography process were used in combination to produce large-scale wind tunnel experimental models. A comparative analysis was conducted between the proposed approach and traditional manufacturing methods. The results demonstrate that, for large-scale cases such as wind tunnel models, a combination of multiple AM processes has the potential to improve performance/quality, reduce costs, and save time when compared to traditional processes. However, it is crucial to emphasize that the success of the hybrid approach depends heavily on the design and process planning. [ABSTRACT FROM AUTHOR]

Microwave-assisted 3D printing based on the fused filament fabrication (FFF) method is an emerging technology to print lightweight continuous carbon fiber reinforced thermoplastics (CCFRP) at high speed. Different from traditional FFF, microwave offers selective and volumetric heating properties to melt thermoplastic materials instantaneously, and the microwave printing head and nozzle remain at room temperature. These advantages can increase the printing speed of CCFRP significantly, while the belt slippage of a printing bed is noticed during microwave-assisted 3D printing. The slippage of the moving belt happens because the cold nozzle moves at high speed and encounters resistance from the rough surface of the printed filament. To solve this problem, this paper presents a hierarchical digital twin (DT) framework, consisting of core and basic DTs, for the prevention of belt slippage induced printing malfunction. The core DTs use MATLAB Simscape multibody models to simulate the printing process virtually and the printing G-code is corrected before printing. In addition, an accelerometer installed on the printing bed is connected to the core DTs. Abnormal vibration signals due to belt slippage can be measured and communicated with core DTs for interrupting and correcting the process. By monitoring the temperature of the heated filament and the output microwave power, the service life of the nozzle and microwave cable are evaluated in the basic DTs. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) offers great potentialities in the medical sector, particularly when part customization is sought after. Maxillofacial surgery has to deal with complex bone fractures and facial reconstructions, hence the need of metallic prostheses to help in the process of bone growth and fracture healing. Commercial prostheses, even if available in different sizes, might not fit the patient's anatomy, and thus should be adapted directly in the operating room. This paper provides an insight on how AM approach, by designing and producing customized prosthesis from computer tomography scan data, can lead to predictable and reliable results reducing the stress on both surgeons and patients. [ABSTRACT FROM AUTHOR]

Laser Powder Directed Energy Deposition (LP-DED) process involves complex physical phenomena, which considerably affect the deposition quality. In process optimization, it is a general approach to firstly analyze single tracks to identify process parameters that guarantee an adequate adhesion to the substrate. This paper aims to evaluate the deposition efficiency and the contact angle of AISI 316L single tracks as process parameters vary. Thus, experiments were performed by varying laser power, travel speed, and feeder rotation. Results help both in clarifying the relationship between process parameters and single tracks characteristics and identifying the best combination of process parameters to enhance deposition quality and process efficiency. [ABSTRACT FROM AUTHOR]

By combining the additive manufacturing (AM)-process with digital concepts, such as the digital twin (DT) or the digital part file (DPF), the competitiveness of additive manufacturing is increased. A quantitative approach to evaluate the usage of a DPF in AM will be introduced within this paper. The focus is set on the production as an early lifecycle-phase, which means that the AM-production process gets analyzed regarding potential advantages of using a DPF. These advantages are transferred into a monetary value with our approach. By calculating the total costs of the DPF, a monetary overall value is obtained [ABSTRACT FROM AUTHOR]

Extrusion-based Additive Manufacturing (AM) processes have recently gained increasing attention in the scientific and industrial communities because of the wide range of processible materials (from thermoplastics to composite and biomaterials), printable volumes, and industrial applications. As for many other AM processes, the actual problems with process stability and repeatability are still limiting the industrial process adoption, as these problems can significantly impact on the final part quality. In this framework, a latest research trend aims at developing in-situ monitoring solutions for inline defect detection, in a zero-waste production perspective. Among the existing in-situ sensing techniques, many studies showed that in-situ thermography represents a viable solution to describe the temperature dynamic and validate the thermal models but very few approaches have been proposed to quantitively study the temperature evolution to quickly detect process instabilities. This paper presents a new approach to quickly analyse the temporal dynamic of temperature in the printed layer while providing a spatial mapping of the temperature homogeneities. Compared with previous methods, the current one has the main novelty feature of combining both the spatial and temporal signature in a synthetic mapping that allows to detect unstable or unusual problems. In order to show the effectiveness of the proposed solution, a real case study of Big Area Additive Manufacturing (BAAM) for composite materials is considered. The study shows that the provided method can clearly enhance defect detection and represents a new solution for detecting anomalous areas where thermal profiles behave differently with respect to the surrounding areas. The same methodology underlined the thermal evolution complexity in the BAAM case study and enabled the detection of local flaws, i.e., hot and cold spots. [ABSTRACT FROM AUTHOR]

Additive manufacturing is gaining a significant place in Industry 4.0-driven environments, primarily due to the requirements for smoothly and quickly generatively designed components as opposed to multiple machining processes. The internal structure of the manufactured components has different geometric specifications depending on the filling density (80% to 100%) and filling pattern (lines, grid, triangles, etc.). This paper attempts to define the porosity of the additively manufactured parts depending on the infill parameters that affect the mechanical characterization of the parts using industrial computed tomography and observe the internal lattice structures and pattern-to-pore ratios of the manufactured parts. [ABSTRACT FROM AUTHOR]

Directed Energy Deposition (DED) processes are a category of Additive Manufacturing (AM) processes that can be combined with six degrees of freedom multi-axis technologies to manufacture parts with complex internal geometries without support material, while ensuring the local distance requirements. This paper provides a numerical method to compute such a path, using both a facetized file of a part and substrates locations as inputs. Topological concepts are first described to introduce the method. The algorithm is then detailed into three steps: mesh refinement, next layer points search and connection edges computing. Application to different facetized files validates the method. [ABSTRACT FROM AUTHOR]

The use of technical ceramics is growing thanks to their high mechanical properties. To attain the tolerances and surface finish, operations including machining or grinding are performed. Due to the risk of fracture, they are limited to low material removal rates. One promising option is to rely on the hybridization of manufacturing process. This paper is linked to the project HyProPAM that combines additive and substractive techniques. An experimental methodology to determine the optimal milling parameters parts in Zirconia is proposed. Cutting forces and surface topography are used as indicator to determine the quality of the operation. [ABSTRACT FROM AUTHOR]

Informed decision-making for sustainable manufacturing requires accurate manufacturing process environmental impact models with uncertainty quantification (UQ). For emerging manufacturing technologies, there is often insufficient process data available to derive accurate data-driven models. This paper explores an alternative mechanistic modeling approach using easy-to-access data from a given machine to perform Bayesian inference and reduce the uncertainty of model parameters. First, we derive mechanistic models of the cumulative energy demand (CED) for making aluminum (AlSi10) and nylon (PA12) parts using laser powder bed fusion (L-PBF). Initial parametric uncertainty is assigned to the model inputs informed by literature reviews and interviews with industry experts. Second, we identify the most critical sources of uncertainty using variance-based global sensitivity analyses; therefore, reducing the dimension of the problem. For metal and polymer L-PBF, critical uncertainty is related to the adiabatic efficiency of the process (a measure of the efficiency with which the laser energy is used to fuse the powder) and the recoating time per layer between laser scans. Data pertinent to both of these parameters include the part geometry (height and volume) and total build time. Between three and eight data points on part geometry and build time were collected on two different L-PBF machines and Bayesian inference was performed to reduce the uncertainty of the adiabatic efficiency and recoating time per layer on each machine. This approach was validated by subsequently taking direct parameter measurements on these machines during operation. The delivered electricity uncertainty is reduced by 40-70% after performing inference, highlighting the potential to construct accurate energy and environmental impact models of manufacturing processes using small easy-to-access datasets without interfering with the operations of the manufacturing facility. [ABSTRACT FROM AUTHOR]

The potential applications of Additive Manufacturing technologies are capturing the interest of researchers and industries. Many researchers are now focusing on additive manufacturing and its potential to change the industrial paradigm in terms of economic, environmental, and social sustainability. One of the most promising areas for additive manufacturing adoption is maintenance, more specifically, manufacturing of spare parts. The customization potential, and excellent small series capabilities of AM can lead to reductions in size of central and local storages, eliminate the need to locate uncommon spare parts in the distribution network, shorten supply chains and diminish the duration and cost of logistics. The case for replacing conventional spare parts with additive manufactured equivalents has been the discussed in various studies focused of the aeronautic sector, however, its potential in other industries remains relatively unexplored. The continuous process industry is characterized by extremely high production volumes with costly machines and downtime. The combination of these characteristics with intermittent spare part demand patterns and the predominance of reactive maintenance, drives companies to keep large spare parts stock, which makes the case for introducing AM in process industry maintenance very appealing. This study focuses on how AM could change maintenance activities/supply chain in process industries and its economic impact using process based cost models. To further illustrate and study the problem, this paper contains a detailed evaluation of AM's potential and impacts in a case study from the paper and pulp industry. [ABSTRACT FROM AUTHOR]

Metal additive manufacturing has been developed rapidly for its capability to produce metallic objects with complex structure directly. In metal additive manufacturing, the heat source is an important factor determining forming properties, and laser, electron beam and arc plasma are used as main heat sources currently. However, some problems should be noted. When laser is used as heat source, the forming of some powder materials, such as copper alloys and aluminum alloys, is difficult due to their high reflectivity. For the case of electron beam, vacuum environment is necessary resulting in high cost. As for current arc additive manufacturing, it is difficult to achieve high accuracy as a result of high energy and wire material used. This paper developed a new method for metal additive manufacturing. In this method, voltage is applied between the tool electrode and metal powder bed to cause the breakdown of the dielectric forming the micro arc plasma, which is adequate to melt the metal powder, and parts can be formed layer by layer. With this method, the better accuracy can be obtained by means of smaller current and powder bed. In addition, the plasma can be generated easily with less environmental requirements making lower cost. In this paper, the forming principle of this method was studied, and the prototype device was set up. The single point and single pass discharge melting experiments were carried out, and the influence of processing parameters on forming quality was investigated. The feasibility of this method can be verified. [ABSTRACT FROM AUTHOR]

This paper presents a model to approach the selection of temperature control measures for polymer-made additive injection molds. Such molds are used in manufacturing of close-to-series prototype, but are still limited to small volumes, low production rates and standard polymer materials. Measures of temperature control can increase the applicability of those molds. The measures allow maintaining the optimal process parameters for the desired application. This paper aims to summarise possible measures, their current state of research and argues for a comprehensive model supporting a selection process. [ABSTRACT FROM AUTHOR]

An Indoor Air Quality (IAQ) monitoring and assessment is necessary in order to safeguard the well being of the occupants. This research addresses this issue in an Additive Manufacturing (AM) platform of an educational institute. Performing air monitoring requires quantifying the platform user exposures. Regulations, local policies, as well as ISO standards are well developed for office environments and industrial sites. However the indicators and the pollution levels allowed for new tools and technologies are yet to be defined. This is specifically the case in France for AM educational purpose. A practical IAQ assessment protocol is addressed in this research questioning: the type of emissions to measure, and the way to measure them on an AM platform. The method includes a selection of the assessment parameters for the IAQ, the associated IAQ indicators and the associated sensors to measure emissions rates. The assessment protocol has been applied to GINOVA S.mart Grenoble-Alps educational FabLab for students and researchers. Emissions have been measured from a variety of AM technologies, merging material and gas input resources. The choice of sensor and measurement method is discussed in this paper. The measurement results cover a variety of particles and gas emissions. This paper concludes on the limits and the opportunities of an IAQ dynamic assessment protocol to make an emerging manufacturing platform eager to develop the number of machines using various materials types, a cleaner environment for its users. The Makers community could be interested to use such a protocol in any standard FabLab. [ABSTRACT FROM AUTHOR]

A significant barrier to the broad adoption of Additive Manufacturing is the lack of quality and repeatability on the manufactured part. A promising approach to overcome this limitation is process monitoring and real-time process control. This paper provides an overview of current works related to the in-situ monitoring of the properties related to material (e.g. geometry, surface, or thermal property) in AM processes using optical sensors. The research contents of these works, such as the parameter under monitoring and the types of sensors, are categorized and summarized. Based on the review, an outlook of future works is presented. [ABSTRACT FROM AUTHOR]

In this paper, a new CAM planning strategy for removal of support structures is presented. Since such a task is usual in post-processing of parts fabricated with additive manufacturing, the developed approach is about a toolpath planning algorithm suitable for generic robotic cells that can be equipped with a chiseling holder. The 6-axis toolpath generation was used to define spatial paths of the tool tip and proper orientation of the chisel tool. The chisel can be orientated with a certain angle to the machined surface ensuring a gouge-free and collision-free positioning. Removability of different support structures was experimentally validated. [ABSTRACT FROM AUTHOR]

This work presents a synthetic geometrical performance index that combines all dimensional and geometrical deviations of a printed part to express its quality. Smaller is the value of this index, greater is the part quality. The paper demonstrates the effectiveness of this index by printing a set of parts through Fused Filament Fabrication in a biological polymer. These parts, characterized by representive hollows, were measured by optical scanning technology. The proposed methodology shows the advantages of this index, thus future work can focus on further printing techniques and varying process parameter values. [ABSTRACT FROM AUTHOR]

Nowadays Additive Manufacturing processes are increasingly utilized for manufacturing parts with complex shapes in numerous fields such as internal-channel parts in aerospace and automobile industries. However, the geometrical quality of internal channel is still an unsolved problem. In order to provide guidance for the manufacturing of internal-channel parts via Selective Laser Melting process, this paper studies the influence of process parameters, such as build orientation, laser power, scanning speed, layer thickness and scanning strategy. A group of simulations are carried out with Design of Experiments, and the results show the build orientation is the parameter with significant impact. The impact trend and the optimal parameter combination for internal-channel part geometrical quality are analyzed, which is beneficial for high-fidelity internal-channel parts manufacturing. [ABSTRACT FROM AUTHOR]

Despite its potentials, geometrical inaccuracies remain a major shortcoming for Additive Manufacturing in general and especially for Fused Layer Modeling, even though much research effort is put in enhancing mechanical properties and reducing process-specific deviations by optimizing process parameters. Novel slicing and path planning algorithms, such as non-planar printing, are suitable tools for addressing these problems and thus for improving geometrical part accuracy, but are subject of current research and only partly applicable. With the aim to show and evaluate the potential of these algorithms in the context of tolerancing, this paper proposes an approach for applying one pre-processing technique to 3D-printed parts. The exemplary application shows the applicability and the high potential of advanced slicing and path planning algorithms. The findings therefore indicate that aspects of pre-processing should be matched with the parts geometry and therefore have to be frontloaded into the product and the tolerance design for their consideration. [ABSTRACT FROM AUTHOR]

Due to the complex physical state changes during Additive Manufacturing processes, geometric deviations of part surface are unavoidable. In order to assist the study of part geometric deviation from the perspective of physical mechanism, according to the characteristics of layer-wise and line-wise printing in additive manufacturing, a method to describe the in-plane geometric deviation is presented in this paper. The geometric deviation coordinate system is established based on the scanning toolpath and its feed wire as well as the orthogonal direction of the baseline and the feed line in this method. The in-plane geometric deviation can be expressed through scanning toolpath mapping function considering the deviation factors. The geometric deviation representation method is preliminarily verified by the case study of Fused Deposition Modeling parts with a cylinder shape. [ABSTRACT FROM AUTHOR]

Among a broad spectrum of AM technologies, electron beam melting (EBM) is widely applied in AM process for producing titanium alloy parts. In general, AMed metal products have very rough surface of more than 200µm R z, since relatively large beads are arranged on their surface by scanning electron beam. Moreover, surface irregularities such as spatter and cavity are also generated on the surface. Rough surface and surface irregularities would lead to reduction in surface strength and poor appearance. Therefore, post surface finishing processes are required to smooth the surface of AMed metal products. One of the common surface smoothing processes is abrasive blasting. Large surface roughness can be decreased by abrasive blasting, and compressive residual stress can be introduced to the surface. However, there is a limitation to reduction of surface roughness. On the other hand, in large-area electron beam (large-area EB, LEB) irradiation method developed recently, mold steel surface can be finished by melting it in a few minutes. However, it is not easy to smooth surface with large initial surface roughness, and a tensile residual stress may be generated on the surface. In this paper, surface smoothing of AMed titanium alloy by combination of abrasive blasting and large-area EB irradiation was proposed. At first, the AMed titanium alloy surface was blasted to reduce the initial large surface roughness to some extent and change the surface topography. Then, large-area EB was irradiated to the blasted surface. It is made clear that surface roughness significantly decreases when large-area EB is irradiated to the blasted surface with small mean width. Moreover, tensile residual stress generated in large-area EB irradiation can be reduced by abrasive blasting. Therefore, combination of abrasive blasting and large-area EB irradiation is effective for efficient reduction of large surface roughness of AMed titanium alloy. [ABSTRACT FROM AUTHOR]

Laser powder bed fusion (LPBF) as an additive manufacturing (AM) process allows for sophisticated geometries to be produced. With optimized process parameters high densities of the metal parts can be achieved. The locally concentrated melting and fast solidification leads to a fine dendritic microstructure depending on the melt pool size. In this dendritic structure the layer wise build-up is still visible. It is well known that this leads to an anisotropic material behavior. In this paper the influence of the build-up orientation relative to the cutting vector on the cutting process is studied. For this objective, specimens out of maraging steel with different build-up directions are build and subsequently examined utilizing an orthogonal cut. During the cut, forces, vibrations and acoustic emission are used to investigate the cutting behavior. Furthermore, the chips are analyzed for the geometric characteristic values. With this, the anisotropic behavior could be demonstrated. Depending on the build-up orientation α, cutting force varies by up to 6 % and thrust force by up to 8. Chip thickness also varies depending on α by up to 18,6 %. Based on the findings, a regression model is developed which maps the specific material properties. This makes it possible to predict resulting cutting forces and chip volume, based on the layer penetration angle. Finally, this leads to a better understanding of the interactions between the additive subtractive process chain. [ABSTRACT FROM AUTHOR]

The scope of this paper is the systematic investigation and conceptual design of a process based on the principle of electrophotography for the application of particles on a build plate with the focus on powder bed based fusion of metals by means of a laser beam (PBF-LB/M). The influence parameters for the particle transfer from the photoconductor to the build plate are investigated using a prototype based on the stamp principle. In this setup the process is extended for the first time by the sequence of powder deposition compared to [ 1 , 2 ]. The investigations of this work concentrate exclusively on a full-area attraction on the photoconductor´s surface and its deposition. The attraction of the powder to be deposited is performed without an exposure sequence. Significant parameters for the system are identified and measures to ensure a reproducible deposition are derived. Within the scope of experimental investigations, the PBF-LB/M typical powder 1.7147 (20MnCr5) with a particle size distribution of 15 to 56 µm is tested with regard to the deposition quality (surface coverage density and layer thickness) in a single- and multi-layer deposition. The stacking of the particle layers not only increases the area coverage density, but also demonstrates the basic transferability for generating a powder bed, which is required for additive manufacturing. [ABSTRACT FROM AUTHOR]

Electron beam melting (EBM) made feasible γ-titanium aluminide (TiAl) alloys. However, the surface roughness resulting from EBM is poor, and the high mechanical properties make γ-TiAl difficult to be machined. Electro-Chemical Machining (ECM) is gaining interest as a finishing process to achieve low surface roughness. Based on the anodic dissolution mechanism, ECM realises a contactless material removal and results particularly suitable for difficult-to-cut materials. The paper investigates the use of ECM for the finishing of Ti-48Al-2Nb-2Cr, a γ-TiAl alloy made by EBM. The effects of current, voltage, feed rate and duty ratio have been accounted for under pulsed machining conditions. [ABSTRACT FROM AUTHOR]

Under the circular economy paradigm, de- and remanufacturing systems are more relevant than ever. However, such systems present specific challenges related to the system structure, automation, and recovery of complex products. At present, operations such as disassembly and quality assessment of returned products largely depend on manual labor and the high variety of returned products makes restoring disassembled parts demanding. This paper proposes a framework for de- and remanufacturing systems based on Human-Cyber-Physical Systems (HCPS) that includes additive manufacturing for refurbishing damaged parts during the remanufacturing process. The framework is illustrated using MANULAB at NTNU. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) as a service is already offered to consumers, as well as to business customers in industry. Various service platforms exist. AM as a service for the healthcare domain is a rather new concept. In this paper we provide an overview of challenges and special requirements of providing AM as a service for medical applications such as implants, anatomic models, and medical tools. We discuss these aspects, based on a practical case of an AM lab operated in a hospital and present the design of such a platform and its specific challenges in the healthcare domain. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) has been experiencing considerable growth in recent years, especially for metal application. Directed Energy Deposition (DED) is one of the emerging technologies in metal AM. DED selectively deposits material and melts it with a focused high-energy source. Accurate numerical modelling of the DED technique is an important step for the comprehension and the technological improvement of the process, providing significant gains in terms of time and costs. This paper aims to review the existing knowledge on DED numerical simulation, highlighting principal advantages and limitations of different approaches. The key inputs required to model the process properly, and the predictable outcomes are discussed. [ABSTRACT FROM AUTHOR]

Despite the powerful capabilities of the Laser Powder Directed Energy Deposition (LP-DED) process, the applications are limited almost to feasibility analyses of simple case studies. This arises from the knowledge gap in the process parameters identification and optimization of the deposition quality. A practical approach is to delineate the process parameters window by producing single tracks with different sets of parameter levels. This paper aims to study, through statistical analysis, the effect of process parameters on the characteristic dimensions of IN718 single tracks. Results will allow empirical relations to be identified between track geometry and the analysed parameters. These relations will support process optimization. [ABSTRACT FROM AUTHOR]