For heat-triggered shape-changing 3D prints, active and restrictive segments need to be 3D printed next to each other to obtain the desired morphing of an object. Current single-material methods rely on locally controlling the orientation of the printing lines to adjust the amount and direction of shrinkage. This approach, however, limits design freedom as it restricts the shape and fabrication of the objects. Moreover, it results in undesirable deformations in more complex and larger designs. Addressing these challenges, we introduce Foam2Form, a method that forms active and restrictive segments by programming the shape-memory properties of foaming PLA during the printing process.We propose to use the material in a non-foamed state for active segments and in a foamed state for restrictive and passive segments, which results in more stable 4D designs free from unwanted deformations. We present the first results of this low-cost 4D printing method and demonstrate its capabilities with various application examples.

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Materiality of artefacts holds the potential to intricately and dynamically shape our daily practices. We posit this capacity can be harnessed in fostering creative unfolding of everyday care practices towards living artefacts. To explore this premise, we designed a cyanobacterial living artefact with air purifying capacity, and invited eight participants to live with and care for it for two weeks. The artefact can be situated in diverse locations within domestic spaces, wherever the participant would consider air purification necessary and certain lighting conditions beneficial for the artefact’s vitality. This versatility is supported by the artefact’s colour-changing, pliable, adhesive, and suspendable nature. We analysed visual documentation and semi-structured interviews of participants’ experiences of the artefact. Our findings suggest distinct roles of materiality for care regarding labour, knowledge, and exploration. We further highlight the intricate design space encompassing openness, temporalities and semantic fitness towards nurturing mutualistic care in human-microbe interactions.@en

Anyone who has watched a child play with soft semi-liquid materials like honey, frosting, or slime, sees the fascinating interplay between design and physics. Many of us remember these experiences from our own childhood (or maybe not that long ago). These materials dribble and coil as they stack upon themselves when we drop them onto surfaces like cakes from small heights. This ludic behavior represents a physical phenomenon known as rope coiling. Recent research in 3D printing of clay and plastic has started to wonder how rope coiling can be leveraged to create new textures and textile-like structures through non-planar 3D Printing. These provide new tactile experiences in objects like cups and visual experiences in things like lamps. In this demonstrator, we invite researchers and practitioners to return to their childhood and dribble edible materials to understand how to advance additive manufacturing through interactive printing.@en

Structural electronics has garnered significant attention in the past decade. However, there remains a lack of a systematic approach in designing and manufacturing sensors that leverage both mechanical and electronic properties of materials for different applications. In this paper, we introduce a method for designing piezoresistive force sensors utilizing structural electronics and 3D printing techniques. Based on the principles of piezoresistive force sensing, we defined the geometric profile of the sensor by simultaneously maximizing strain and ensuring as uniform as possible stress distribution across the geometry. CAD models of the sensors were then formulated based on the optimized profile and fabricated using conductive filaments and the material extrusion 3D printing technique. Subsequently, we evaluated the accuracy, the sensitivity, and part-to-part variations of the sensors during loading and unloading. The influence of environmental temperature and humidity on the sensor's response were also investigated and compensated. Experiment results demonstrated the feasibility of the proposed method and revealed potential application domains, as well as limitations of the sensors.

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This interactive textbook provides an educational resource into computational design for (industrial) designers. The book focusses on the use of computational design of products/artifacts at a human scale, which might be contrasted by the architectural/build environment scale – a domain which also extensively utilizes computational design principles and tools. Throughout the book, we make use of (commercial) computer-aided-design software, namely Rhinoceros®, and specifically the (build-in) module Grasshopper®. The lessons and knowledge base offered in this book focus on topics that are specifically relevant for and/or attuned to product design (scale), which are categorized in relation to its goal (e.g. design for personalized fit/comfort/aesthetics), by its means (e.g. design for digital fabrication), or for its role in the design process (e.g. for design exploration or design simulation). The book is intended for students both at bachelor and master level. As we believe in a learning-by-doing approach, we aimed for a hands-on, easy-to-get-started set of introductory lessons, which is complemented with a knowledge base. The introductory lessons do not assume any specific prior skills or knowledge (in general or with Rhino Grasshopper) to get started. Yet, (some) experience with computer-aided design (CAD), programming, data processing, and/or mathematics will likely be helpful to really delve into the more complex topics, such as those covered in the knowledge base. The book is currently used as course material in two courses taught at Industrial Design Engineering: “Prototyping with/for Digital Fabrication” (BSc level, part of the Minor Advanced Prototyping), and “Computational design for Digital Fabrication” (MSc level, Elective). The content in this book is in part based on course materials from the above-mentioned courses, which have been been taught to and applied by students with diverse (technical) backgrounds (e.g. industrial design, mechanical engineering, computer science, and electrical engineering). Other parts of the book are inspired by student (graduation) projects and/or follow from research activities by the various contributing authors.@en

The emergence of the field of soft robotics has led to an interest in suction cups as auxiliary structures on soft continuum arms to support the execution of manipulation tasks. This application poses demanding requirements on suction cups with respect to sensorization, adhesion under non-ideal contact conditions, and integration into fully soft systems. The octopus can serve as an important source of inspiration for addressing these challenges. This review aims to accelerate research in octopus-inspired suction cups by providing a detailed analysis of the octopus sucker, determining meaningful performance metrics for suction cups on the basis of this analysis, and evaluating the state-of-the-art in suction cups according to these performance metrics. In total, 47 records describing suction cups are found, classified according to the deployed actuation method, and evaluated on performance metrics reflecting the level of sensorization, adhesion, and integration. Despite significant advances in recent years, the octopus sucker outperforms all suction cups on all performance metrics. The realization of high resolution tactile sensing in suction cups and the integration of such sensorized suction cups in soft continuum structures are identified as two major hurdles toward the realization of octopus-inspired manipulation strategies in soft continuum robot arms.

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We propose a new approach to obtain local property variations in 3D-printed objects using a single-nozzle 3D printer and one filament. We use foaming filaments which expand at different rates due to different temperatures. We present an approach to harness this varying expansion by including parameters of the 3D printing process in the design space. This makes the foaming programmable and allows for achieving a wide variety of properties from a single material. We show how objects with locally varying shade, translucency, gloss, and texture can be fabricated. Our approach turns single-nozzle 3D printers into more versatile systems while eliminating the challenges of multi-material 3D printing. This is in contrast to the drive towards an increasing number of printable materials and more complex 3D printers. We demonstrate the capability of our approach by 3D printing objects with embedded barcodes, QR codes, and varying tactile properties.

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Spare parts availability is crucial for extending the life of consumer products. However, long-term availability could lead to high stocks of spare parts, which might not be used. Instead, on-demand manufacturing of spare parts with additive manufacturing (AM) is a promising alternative. This paper presents a method to evaluate parts on their eligibility for AM spare parts. The parts evaluation is based on AM technology accessibility as well as part requirements. This method was tested by assessing all parts of the Dyson V11 broom-stick vacuum-cleaner and validated by printing and testing a selection of parts. For this, both plastic and metal spare parts were made through fused deposition modelling (FDM), stereolithography (SLA), binder jetting (BJ), material jetting (MJ), selective laser melting (SLM), selective laser sintering (SLS), and multi jet fusion (MJF), using both desktop FDM printers and off-site service providers. Based on these results, we conclude that currently only a small number of parts can be replaced by additive manufactured parts without considerable redesign efforts. AM parts can compete on price with the current stocked parts, but may be more expensive for other products. We also identified additional functional requirements for evaluating the eligibility of a spare part for AM.@en

In this paper, we propose a method to reconstruct a digital 3D model of a stolen/damaged statue using photogrammetric methods. This task is challenging because the number of available photos for a stolen statue is in general very limited – especially the side/back view photos. Besides using standard structure-from-motion and multi-view stereo methods, we match image pairs with low overlap using sliding windows and maximize the normalized cross-correlation (NCC) based patch-consistency so that the image pairs can be well aligned into a complete model to build the 3D mesh surface. Our method is based on the prior of the planar side on the statue’s pedestal, which can cover a large range of statues. We hope this work will motivate more research efforts for the reconstruction of those stolen/damaged statues and heritage preservation.@en

Microbes offer designers opportunities to endow artefacts with environmental sensing and adapting abilities, and unique expressions. However, microbe-embedded artefacts present a challenge of temporal dissonance, reflected by a “time lag” typically experienced by humans in noticing the gradual and minute shifts in microbial metabolism. This could compromise fluency of interactions and may hinder timely noticing and attending to microbes in living artefacts. In addressing this challenge, we introduce Cyano-chromic Interface, in which photosynthetic activity of cyanobacteria (Synechocystis sp. PCC6803) is timely surfaced by an electrochromic (EC) material through its monochromatic display. Grounded through interface performance characterization and design primitives, we developed application concepts through which we instantiate how the interface can be tuned for diverse functional and experiential outcomes in living artefacts. We further discuss the potential of aligning human-microbe temporalities for enriched interactions and reciprocal relationships with microbes, and beyond.@en

Living organisms use functional gradients (FGs) to interface hard and soft materials (e.g., bone and tendon), a strategy with engineering potential. Past attempts involving hard (or soft) phase ratio variation have led to mechanical property inaccuracies because of microscale-material macroscale-property nonlinearity. This study examines 3D-printed voxels from either hard or soft phase to decode this relationship. Combining micro/macroscale experiments and finite element simulations, a power law model emerges, linking voxel arrangement to composite properties. This model guides the creation of voxel-level FG structures, resulting in two biomimetic constructs mimicking specific bone-soft tissue interfaces with superior mechanical properties. Additionally, the model studies the FG influence on murine preosteoblast and human bone marrow-derived mesenchymal stromal cell (hBMSC) morphology and protein expression, driving rational design of soft-hard interfaces in biomedical applications.

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The summer school is realized as a joint teaching project between several partner universities under the auspices of the IDEA League alliance. The school trains students and young researchers on exploring and applying the potential of computational-based strategies in design for additive manufacturing, while engaging in dedicated team working activities. The aim of this work is to report on and discuss the success of the summer school in terms of the learning goals achievement. The work is based on the results of a one-day workshop with the summer school alumni showing how the acquired knowledge, skills and competences impacted their studies, research, and professional careers in a long-term after the course is finished, and outlining possible course content improvements to plan the summer school in 2023 that will take place with physical presence. @en

Durable interfacing of hard and soft materials is a major design challenge caused by the ensuing stress concentrations. In nature, soft-hard interfaces exhibit remarkable mechanical performance, with failures rarely happening at the interface. Here, we mimic the strategies observed in nature to design efficient soft-hard interfaces. We base our geometrical designs on triply periodic minimal surfaces (i.e., Octo, Diamond, and Gyroid), collagen-like triple helices, and randomly distributed particles. A combination of computational simulations and experimental techniques, including uniaxial tensile and quad-lap shear tests, are used to characterize the mechanical performance of the interfaces. Our analyses suggest that smooth interdigitated connections, compliant gradient transitions, and either decreasing or constraining strain concentrations lead to simultaneously strong and tough interfaces. We generate additional interfaces where the abovementioned toughening mechanisms work synergistically to create soft-hard interfaces with strengths approaching the upper achievable limit and enhancing toughness values by 50%, as compared to the control group.

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Personalized designs bring added value to the products and the users. Meanwhile, they also pose challenges to the product design process as each product differs. In this paper, with the focus on personalized fit, we present an overview as well as details of the personalized design process based on design practice. The general workflow of personalized product design is introduced first. Then different steps in the workflow such as human data/parameters acquisition, computational design, design for digital fabrication, and product evaluation are presented. Tools and methods that are often used in different steps in the process are also outlined where in human data acquisition, 3D scanning, and digital human models are addressed. For computational design, the use of computational thinking tools such as abstraction, decomposition, pattern recognition and algorithms are discussed. In design for digital fabrication, additive manufacturing methods (e.g. FDM), and their requirements on the design are highlighted. For product evaluation, both functional evaluation and usability evaluation are considered and the evaluation results can be the starting point of the next design iteration. Finally, several case studies are presented for a better understanding of the workflow, the importance of different steps in the workflow and the deviations in the approach regarding different contexts. In conclusion, we intend to provide designers a holistic view of the design process in designing personalized products as well as help practitioners trigger innovations regarding each step of the process.@en

Bio-inspired composites are a great promise for mimicking the extraordinary and highly efficient properties of natural materials. Recent developments in voxel-by-voxel 3D printing have enabled extreme levels of control over the material deposition, yielding complex micro-architected materials. However, design complexity, very large degrees of freedom, and limited computational resources make it a formidable challenge to find the optimal distribution of both hard and soft phases. To address this, a nonlinear coarse-graining approach is developed, where foam-based constitutive equations are used to predict the elastoplastic mechanical behavior of biomimetic composites. The proposed approach is validated by comparing coarse-grained finite element predictions against full-field strain distributions measured using digital image correlation. To evaluate the degree of coarse-graining on model accuracy, pre-notched specimens decorated with a binarized version of a renowned painting were modeled. Subsequently, coarse-graining is used to predict the fracture behavior of bio-inspired composites incorporating complex designs, such as functional gradients and hierarchical organizations. Finally, as a showcase of the proposed approach, the inverse coarse-graining is combined with a theoretical model of bone tissue adaptation to optimize the microarchitecture of a 3D-printed femur. The predicted properties were in exceptionally good agreement with the corresponding experimental results. Therefore, the coarse-graining method allows the design of advanced architected materials with tunable and predictable properties.

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The geometric shapes and the relative position of coils influence the performance of a three-dimensional (3D) inductive power transfer system. In this paper, we propose a coil design method for specifying the positions and the 3D shapes of a pair of coils to transmit the desired power. Given region of interests (ROIs) for designing the transmitter and the receiver coils on two surfaces, the transmitter coil is generated around the center of its ROI. The center of the receiver coil is estimated as a random seed position in the corresponding 3D surface. At this position, we use the heatmap method with electromagnetic constraints to iteratively extend the coil until the desired power can be transferred via the set of coils. In each step, the shape of the extension, i.e., a new turn of the receiver coil, is found as a spiral curve based on the convex hulls of the 2D projected adjacent turns along their normal direction. Then, the optimal position of the receiver coil is found by maximizing the efficiency of the system. In the next step, the position and the shape of the transmitter coil are optimized based on the fixed receiver coil using the same method. This optimization process iterates until an optimum is reached. Simulations and experiments with digitally fabricated prototypes were conducted and the effectiveness of the proposed 3D coil design method was verified.

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In this paper, we present a new computational pipeline for designing and fabricating 4D garments as knitwear that considers comfort during body movement. This is achieved by careful control of elasticity distribution to reduce uncomfortable pressure and unwanted sliding caused by body motion. We exploit the ability to knit patterns in different elastic levels by single-jersey jacquard (SJJ) with two yarns. We design the distribution of elasticity for a garment by physics-based computation, the optimized elasticity on the garment is then converted into instructions for a digital knitting machine by two algorithms proposed in this paper. Specifically, a graph-based algorithm is proposed to generate knittable stitch meshes that can accurately capture the 3D shape of a garment, and a tiling algorithm is employed to assign SJJ patterns on the stitch mesh to realize the designed distribution of elasticity. The effectiveness of our approach is verified on simulation results and on specimens physically fabricated by knitting machines.

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The publisher regrets that the below equations are published incorrectly in the original article. Equation 1: [Figure presented] Equation 2: [Figure presented] Equation 5: [Figure presented] The publisher would like to apologise for any inconvenience caused.@en

The geometric shapes of coils influence the performance of a 3D IPT system. In this paper, we proposed a 3D coil design method based on (3D) printing electronics. Given a 3D transmitter coil, the center position of the receiver coil is estimated as a random seed position in the corresponding 3D surface first. At this position, we use the heatmap method with electromagnetic constraints to iteratively extend the coil until the desired power can be transferred via the coil. For each extension of the coil, i.e. a new turn, the shape of the coil is optimized by calculating the convex hull of the new turn in the 2D projection plane. Using this method, we are able to generate a receiver coil to transmit “just enough” power at a given seed position. Then, by fixing the receiver coil, the 3D shape of the transmitter coil can be optimized as well. This zig-zag optimization process iterates until there are few changes of the position and 3D shapes in the iteration. Experiment results with Ansys Maxwell verified the effectiveness of the proposed 3D coil design method, and highlighted possible future research directions as well.

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Lattice structures have been widely used in various applications of additive manufacturing due to its superior physical properties. If modeled by triangular meshes, a lattice structure with huge number of struts would consume massive memory. This hinders the use of lattice structures in large-scale applications (e.g., to design the interior structure of a solid with spatially graded material properties). To solve this issue, we propose a memory-efficient method for the modeling and slicing of adaptive lattice structures. A lattice structure is represented by a weighted graph where the edge weights store the struts' radii. When slicing the structure, its solid model is locally evaluated through convolution surfaces in a streaming manner. As such, only limited memory is needed to generate the toolpaths of fabrication. Also, the use of convolution surfaces leads to natural blending at intersections of struts, which can avoid the stress concentration at these regions. We also present a computational framework for optimizing supporting structures and adapting lattice structures with prescribed density distributions. The presented methods have been validated by a series of case studies with large number (up to 100 M) of struts to demonstrate its applicability to large-scale lattice structures.

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