Future Manufacturing Research Articles

Mechanical Characterization and Computational Analysis of TPU 60A: Integrating Experimental Testing and Simulation for Performance Optimization

This study investigates the mechanical properties of thermoplastic polyurethane (TPU) 60A, which is a flexible material that can be used to produce soft robotic grippers using additive manufacturing. Tensile tests were conducted under ISO 37 and ISO 527 standards to assess the effects of different printing orientations (0°, 45°, −45°, 90°, and quasi-isotropic) and test speeds (2 mm/min, 20 mm/min, and 200 mm/min) on the material’s performance. While the printing orientations at 0° and quasi-isotropic provided similar performance, the quasi-isotropic orientation demonstrated the most balanced mechanical behavior, establishing it as the optimal choice for robust and predictable performance, particularly for computational simulations. TPU 60A’s flexibility further emphasizes its suitability for handling delicate objects in industrial and agricultural applications, where damage prevention is critical. Computational simulations using the finite element method were conducted. To verify the accuracy of the models, a comparison was made between the average stresses of the tensile test and the computational predictions. The relative errors of force and displacement are lower than 5%. So, the constitutive model can accurately represent the material’s mechanical behavior, making it suitable for computational simulations with this material. The analysis of strain rates provided valuable insights into optimizing production processes for enhanced mechanical strength. The study highlights the importance of tailored printing parameters to achieve mechanical uniformity, suggesting improvements such as biaxial testing and G-code optimization for variable thickness deposition. Overall, the research study offers comprehensive guidelines for future design and manufacturing techniques in soft robotics.

Development and characterization of quinoa protein-fucoidan emulsion gels with excellent rheological properties for 3D printing and curcumin encapsulation stability.

Using of low-fat emulsion gels stabilized by quinoa protein (QP) for 3D food printing was limited by their defective rheological properties. The study was to explore the feasibility of using fucoidan (FU) to improve the printability and curcumin encapsulation stability of QP emulsion gel. The gels with 0.5-0.75% FU incorporated were proved to be the most promising ink. Rheological analysis confirmed their great printing potential from the three-stages simulated 3D printing process. The incorporation of FU into emulsions induced more QP molecules adsorbed at the oil-water interface and smaller droplets size. When gel was induced by gluconate δ-lactone, these electrostatic interactions transformed into electrostatic attraction, resulting in a denser gel network. Adding FU to the gel improved its textural properties. Moreover, the gels with FU incorporated exerted better curcumin storage stability. This study provides a simple way to develop and improve the edible 3D printing inks for future food manufacturing.

Inverse and Forward Kinematics and CAD-Based Simulation of a 5-DOF Delta-Type Parallel Robot with Actuation Redundancy

This article introduces a novel modification of a Delta-type parallel robot. The robot has five degrees of freedom and provides its end-effector with a 3T2R motion pattern (three translational and two rotational degrees of freedom). The fifth degree of freedom (rotation) is kinematically decoupled from the other four motions, and it is controlled by two drives. Thus, the proposed robot has a redundant actuation. In this article, we present an algorithm to solve the inverse kinematics of this robot and apply it to a path modeling example of a spiral-like trajectory. Numerical simulations illustrate the algorithm and show how the actuated coordinates change along the considered trajectory. Forward kinematics follows next, and an approach is introduced to determine all end-effector configurations for the specified displacements in the actuated joints. A numerical example presents four assembly modes of the robot corresponding to four real solutions of the forward kinematic problem. Finally, this article demonstrates a computer-aided design and analysis of the proposed robot: we describe a procedure for analyzing inverse kinematics and calculating actuation torques. This study forms the basis for the future manufacturing and experimental analysis of a robot prototype.

Inductance and penetration depth measurements of polycrystalline NbN films for all-NbN single flux quantum circuits

Abstract In this paper, we report on a systematic study of the inductance and magnetic field penetration depth (λ) of polycrystalline NbN superconducting thin films. By employing a four-metal-layer fabrication process specifically designed for all-NbN single-flux-quantum circuits, we constructed a superconducting quantum interference device loop composed of two parallel NbN SNS junctions, NbN microstrips, and NbN ground planes for precise inductance measurement. At 4.2 K, as the linewidth increases from 1 μm to 30 μm, the inductance per unit length (L u) of NbN microstrips significantly decreases, for example, the L u of 250 nm thick NbN microstrips drops from 0.907 pH/μm to 0.047 pH/μm. Compared to Nb, the L u of polycrystalline NbN microstrips is approximately two to three times that of Nb, offering an advantage for manufacturing smaller superconducting inductors. Furthermore, we conducted simulation analysis using InductEx software to extract the λ of NbN films of varying thicknesses. The results indicate that as the film thickness increased from 45 nm to 600 nm, λ initially decreased sharply and then stabilized, with values ranging from 430 nm to 323 nm. Notably, once the film thickness exceeded 200 nm, λ remained essentially constant, even at a temperature of 10 K, where it showed good stability, albeit with a slight increase (about 50 nm) compared to 4.2 K. This dependence of λ on thickness is reasonably explained by considering the effects of NbN film thickness on the superconducting critical temperature and residual resistivity. These research findings not only deepen our understanding of the characteristics of superconducting films but also lay a solid foundation for the future design and manufacture of more compact superconducting circuits at the higher temperature of 10 K.

A novel method for high-temperature microwave 3D printing of golden thread surimi: Combination of thermally reversible gelatin and κ-carrageenan

Microwave 3D printing of surimi has temperature limitations and transglutaminase dependence. The current study aimed to achieve microwave 3D printing of surimi at higher temperatures (45–80 °C) with the combination of thermally reversible gelatin and κ-carrageenan to eliminate reliance on the transglutaminase and improve the molding capacity of products. Our results showed single surimi cannot be stacked when printed at 45 °C while it can be successfully extruded and molded at 80 °C after adding a combination of gelatin and κ-carrageenan to surimi paste. According to rheological data, κ-carrageenan provided the surimi paste with good elastic properties while gelatin lowered the paste's viscosity when heated. Particularly, the microwave 3D printed surimi with 4.5% κ-carrageenan and 1.5% gelatin at 80 °C exhibited relatively optimum gel strength and mechanical characteristics. The results concerning water distribution and microstructure suggested that the microwave printing process could limit the flow of water and enhance the ability of the products to retain moisture, meanwhile, the products printed at 80 °C displayed a relatively more comprehensive gel network structure. Furthermore, molecular force analysis showed hydrophobic and disulfide bond contents increased significantly with the increase of κ-carrageenan at 80 °C, suggesting the promoted protein-colloid cross-linking during microwave heating. In general, gelatin and κ-carrageenan can effectively regulate the surimi gel process during microwave 3D printing at higher temperatures, and improve the molding capacity of final products, which provide a new pattern for the future food manufacturing.

(Invited) Integrating Molecular Recognition Nanosensors with Bioprocesses for Real-Time, Non-Destructive, and Multivariate Process Analytics

As biological and chemical production processes become more sophisticated and evolve in various forms, there is a critical need for the development of new biochemical analysis systems capable of qualifying the versatile synthesis variables and product quality at each site. Despite traditional instrumental analyses including spectroscopy, mass spectrometry, or chromatography, being utilized as the gold standard providing precision, they are not suitable for smart process analytical technology (PAT) for future chemical and biological manufacturing, which should enable real-time, non-destructive, and on-site multivariate process monitoring without complicated sample preparations. Many optoelectronic sensors based on nanotechnology have been showing potential for this with very high sensitivity and selectivity, yet they have not been integrated into actual PAT systems due to abscence of a form factor design, sensor materials integration, and data processing techniques.In this talk, we will introduce our recent approach on a label-free and multivariate real-time sensor system based on a unique molecular recognition array for smart biological process monitoring. We designed a wide library of 3D corona interfaces of near-Infrared (nIR) fluorescent single-walled carbon nanotube (SWCNT) transducers for the multivariate biochemical molecules as process quality attributes. We integrated this nIR fluorescent sensor array with a new mobile form factor based on microfluidics and fiber optics, and developed a remote nano-biophotonic signal transducing technique. With this, we can analyze biological production samples online, allowing for the simultaneous extraction of rich molecular data in real-time wihtout any sample preparation and labeling steps. We will introduce two representative molecular recognition based PAT systems: i) physicochemical heterogeneity analysis of therapeutic cells production for reliable treatment efficacy, and ii) Chinese hamster ovary (CHO) cell based bioreactor for a high-performance antibody production.

(Invited) metal Organic Framework Templates for the Fabrication of High Performance Photoanodes

The study of structure property/relationships in advanced materials is promising towards obtaining systems with desired functionalities. Such systems can then be used as building blocks for the fabrication of various emerging technologies. In particular, nanostructured materials synthesized via the bottom–up approach present an opportunity for future generation low cost manufacturing of devices. We focus in particular on recent developments in solar technologies that aim to address the energy challenge [1-5].Here we present the use of Metal Organic Frameworks (MOFs) as templates for the fabrication of high performance photoanodes in next generation solar technologies. In particular, we describe the realization of NiO, mixed phase TiO2 and In2O3/CuO p-n heterojunction composite photoelectrodes, obtained using MOFs [6-8], for photoelectrochemical hydrogen generation from water.[1] Nano Energy 79, 105416 (2021); [2] Chem. Eng. J. 446, 137312 (2022); [3] ACS Appl. Mater. Int. 15, 56413 (2023); [4] Small Meth. 8, 2300133 (2024); [5] J. Mater. Chem. A 11, 23821 (2023); [6] Appl. Cat. B 263, 118317 (2020); [7] Small 18, 2201815 (2022); [8] Small 19, 2300606 (2023).

Device for automated aseptic sampling: Automated sampling solution for future cell and gene manufacturing.

Cell sampling is a key step performed regularly throughout the cell manufacturing process to gather cell samples for cell growth, progress, and characteristics analysis. While the current method of sampling by pipetting in a biosafety cabinet is commonly used, it is labour-intensive and susceptible to contamination risks. We have developed Device for Automated Aseptic Sampling (DAAS), to enable automated, small volume (0.02-1.00mL) aseptic sampling with minimal dead volume primarily for cell and gene therapy manufacturing. The aim of DAAS is to enable an accurate and consistent sampling process, with minimal contamination risks and interruption to the cells in culture. DAAS can potentially interface with other automated solutions to enable automated and streamlined cell manufacturing workflow and reduce overall manufacturing costs. DAAS has been verified as an aseptic sampling solution via repeated microbial ingression tests. It has also been tested for achieving comparable cell density and viability compared to manual pipetting, with negligible cross-sample carryover when used to sample Jurkat cells of different cell concentrations. The application of using DAAS to sample cell periodically and monitor cell growth and viability continuously for prolonged cell culture was successfully demonstrated with Jurkat cell culture in a static culture flask and donor T cell culture in an automated bioreactor system over a culture duration of 10days in a Biosafety Level-2 laboratory. Overall, DAAS presents great potential as an automated and aseptic sampling solution, offering cell and gene therapy manufacturers easier and more frequent access to cell samples with minimal interruptions to the cell culture. This enables close monitoring of cell culture and a more automated, connected and cost-effect cell and gene therapy manufacturing process.

Towards atomic-scale smooth surface manufacturing of β-Ga2O3 via highly efficient atmospheric plasma etching

Abstract The highly efficient manufacturing of atomic-scale smooth β-Ga2O3 surface is fairly challenging because β-Ga2O3 is a typical difficult-to-machine material. In this study, a novel plasma dry etching method named plasma-based atom-selective etching (PASE) is proposed to achieve the highly efficient, atomic-scale, and damage-free polishing of β-Ga2O3. The plasma is excited through the inductive coupling principle and carbon tetrafluoride is utilized as the main reaction gas to etch β-Ga2O3. The core of PASE polishing of β-Ga2O3 is the remarkable lateral etching effect, which is ensured by both the intrinsic property of the surface and the extrinsic temperature condition. As revealed by density functional theory-based calculations, the intrinsic difference in the etching energy barrier of atoms at the step edge (2.36 eV) and in the terrace plane (4.37 eV) determines their difference in the etching rate, and their etching rate difference can be greatly enlarged by increasing the extrinsic temperature. The polishing of β-Ga2O3 based on the lateral etching effect is further verified in the etching experiments. The Sa roughness of β-Ga2O3 (001) substrate is decreased from 14.8 to 0.057 nm within 120 s, and the corresponding material removal rate reaches up to 20.96 μm/min. The polished β-Ga2O3 displays significantly improved crystalline quality and photoluminescence intensity, and the polishing effect of PASE is independent of the crystal faces of β-Ga2O3. In addition, the competition between chemical etching and physical reconstruction, which is determined by temperature and greatly affects the surface state of β-Ga2O3, is deeply studied for the first time. These findings not only demonstrate the high-efficiency and high-quality polishing of β-Ga2O3 via atmospheric plasma etching but also hold significant implications for guiding future plasma-based surface manufacturing of β-Ga2O3.

Research on the Application of Additive Manufacturing Technology in the Digital Field of Oral Medicine

In recent years, additive manufacturing technology has developed rapidly in oral healthcare. Especially in the application of preoperative models, navigationtemplates, denture and orthodontic device manufacturing, the accuracy of surgery has been improved, treatment time has been shortened, and good restoration effects have been achieved. Oral medicine is considered one of the most promising fields for future additive manufacturing technology, and its application in oral medicine will become an inevitable trend.

REFRIGERANT CHARGING UNIT FOR THE RESIDENTIAL AIR CONDITIONERS: AN EXPERIMENT

In the present work, an automatic R410A refrigerant charger for residential air conditioners is fabricated and tested. The charger operates on the throttling principle and uses the suction pressure of the compressor to estimate the refrigerant charge level. This helps to reduce the risk of compressor damage and ensures the correct composition ratio of R410A refrigerant when charged into the machine. The charging process is controlled by the LabVIEW platform, which provides adequate control and visualization of the charging process. The developed charger meets expectations in solving the technical problems encountered when charging R410A refrigerant for residential air conditioners. It is compact, portable and can be directly controlled through the LabVIEW interface, allowing real-time visualization of the charging process. The present work is expected to make a significant practical contribution, serving as a useful reference for the future manufacturing of compact portable equipment in the residential air conditioning field.

Aluminum Circular Economy in the Bicycle Industry

Abstract From a traditional perspective, Bicycles are considered low-carbon emission transportation tools for commuting and traveling. This study analyzes aluminum recycling pathways within the bicycle manufacturing process to illustrate the bicycle circular economy model for the industry stakeholders to better understand the roadmap for improving from manufacturing to recycling. The goal is to promote the bicycle industry's sustainable development by achieving economic benefits and environmental protection. A comprehensive analysis of the entire lifecycle of the bicycle manufacturing process including production, usage, and recycling, was conducted for future application and manufacturing improvement. This research identifies existing technical barriers, policy limitations and restrictions, and issues related to market acceptance. In response to these challenges, a framework is proposed to draw a roadmap for the industry to make informed decisions on circular-economy-centered practices. This approach encourages companies to improve carbon emission efficiency to contribute to the long-term sustainability of the bicycle industry. JEL classification numbers: L11, M10. Keywords: Carbon Emission Efficiency, Circular Economy, Aluminum Recycling, Sustainability.

Research on Disruptive Technology and Future Manufacturing Developments

Industrial transformations, that are triggered by disruptive technologies, have the property of persisting over time. They may represent new ways to do existing activities, or they may represent genuinely new activities. In order to occupy a dominant position in future developments, many different countries, around the world, are actively embracing disruptive technologies. This is manifested by the pre-emptive incubation of new industries. The present paper is based upon an extensive literature search. It is argued that disruptive technologies, in particular, those that are associated with synthetic biology, aerospace manufacturing, and zero-carbon manufacturing, have been selected from a strategic perspective. Through a combination of qualitative descriptions and case studies, the significance and importance of the roles played by biomanufacturing, aerospace manufacturing and green/low-carbon manufacturing, in modern life, are elaborated upon. This allows the case to be made about the three modes of manufacturing that are noted above, that they are subverting traditional manufacturing. Indeed, they are gradually (and sometimes quickly) becoming new manufacturing models. In addition, we note that manufacturing based on new energy sources, intelligent (i.e., robotic) manufacturing and virtual (i.e., data based) manufacturing, (delete the space) are also likely to become highly important topics, and they will be worthy of attention in future considerations.

Multicomponent alloys designed to sinter

Powder sintering is a low-energy, net-shape processing route for many new products in the additive manufacturing space. We advance the viewpoint that for future manufacturing, alloys should be designed from materials science principles to sinter quickly at lower temperatures and with controlled final microstructures. Specifically, we illustrate the computational design of multinary Ni-base alloys, whose chemistries permit a low-temperature solid-state sintering scheme without any pressure- or field-assistance, as well as heat-treatability after sintering. The strategy is based on sequential phase evolutions designed to occur during sintering. The reactions involve rapid reorganization of matter to full density in cycles up to just 1200 °C, while conventional Ni alloys sintered in the solid-state require about ten times longer, or more than 250 °C degrees higher temperature. Our approach yields an alloy that benefits from precipitation hardening, has an increased strength ~\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim$$\\end{document}50% higher than solid-state processed commercial Ni alloys, and yet exhibits extensive plasticity beyond 35% uniaxial strain. The results point to a generalizable design scheme for many other alloys designed for solid-state powder processing that can enable greater value from additive manufacturing.

Effect of sintering temperature on feature resolution and flexural strength of ceramics fabricated through vat photopolymerization additive manufacturing

PurposeAlthough ceramic additive manufacturing (AM) could be used to fabricate complex, high-resolution parts for diverse, functional applications, one ongoing challenge is optimizing the post-process, particularly sintering, conditions to consistently produce geometrically accurate and mechanically robust parts. This study aims to investigate how sintering temperature affects feature resolution and flexural properties of silica-based parts formed by vat photopolymerization (VPP) AM.Design/methodology/approachTest artifacts were designed to evaluate features of different sizes, shapes and orientations, and three-point bend specimens printed in multiple orientations were used to evaluate mechanical properties. Sintering temperatures were varied between 1000°C and 1300°C.FindingsDeviations from designed dimensions often increased with higher sintering temperatures and/or larger features. Higher sintering temperatures yielded parts with higher strength and lower strain at break. Many features exhibited defects, often dependent on geometry and sintering temperature, highlighting the need for further analysis of debinding and sintering parameters.Originality/valueTo the best of the authors’ knowledge, this is the first time test artifacts have been designed for ceramic VPP. This work also offers insights into the effect of sintering temperature and print orientation on flexural properties. These results provide design guidelines for a particular material, while the methodology outlined for assessing feature resolution and flexural strength is broadly applicable to other ceramics, enabling more predictable part performance when considering the future design and manufacture of complex ceramic parts.

Magnetic and ultrasonic vibration dual-field assisted ultra-precision diamond cutting of high-entropy alloys

Despite the remarkable achievements in single-energy field-assisted diamond cutting technology, its performance remains unsatisfactory for processing high-entropy alloys (HEAs), targeted for next-generation large-scale industrial applications due to their exceptional properties. The challenge lies in overcoming the limitations of current single-energy field-assisted processing to achieve ultra-precision manufacturing of these advanced materials. This study proposes a multi-energy field-assisted ultra-precision machining technology, the magnetic and ultrasonic vibration dual-field assisted diamond cutting (MUVFDC), to address the current challenges. The phenomenological aspects of the dual-field coupling effect on HEAs are explored and investigated through comprehensive characterization of the workpiece material, ranging from macroscopic surface morphology to microscopic structural features. These analyses are performed based on experimental results from four different processing technologies: non-energy field, magnetic field, ultrasonic vibration field, and dual-field assisted machining. Research results demonstrate that MUVFDC technology effectively combines the advantages of a vibration field, which enhances cutting stability, and a magnetic field, which improves the machinability of materials. Additionally, this coupling technology addresses the challenges associated with single-energy field machining: it mitigates the difficulty of controlling surface scratches caused by tiny hard particles in a vibration field and suppresses the rapid tool wear encountered in a magnetic field. Furthermore, the gradient evolution of the subsurface microstructure reveals that the vibration field suppresses the severe matrix deformation induced by magnetic excitation. Simultaneously, the magnetic field reduces the size inhomogeneity of recrystallized grains caused by intermittent cutting. Overall, MUVFDC technology enhances surface quality, suppresses tool wear, smooths chip morphology, and reduces subsurface damage compared to single-energy field or non-energy-assisted machining. This work breaks through the performance limitations of traditional single-energy field-assisted processing and advances the understanding of the dual-field coupling effects in HEAs machining. It also presents a promising processing technology for the future ultra-precision manufacturing of advanced materials.

Development workflow based on in situ synchrotron investigations to optimize laser processing of copper pins

To design future laser manufacturing processes for welding of copper materials, more and more high-end analysis methods are required. A fundamental process understanding by analyzing cause-and-effect relations of process dynamics using inline in situ diagnostics allows for an improved description of laser material interaction. Strategies for a reliable and robust welding process are derived from the findings. In this study, a four-step advanced methodical approach is presented and discussed. In the first step, a fundamental process description of the geometry of the vapor capillary and the formation of weld defects is developed. Therefore, welds on electrolytic tough pitch copper (Cu-ETP) and CuSn6 are carried out to analyze the temporal and spatial vapor capillary dynamics depending on laser power, welding speed, and focal diameter. This fundamental process understanding is transferred to the welding of copper pins in the form of I-pins. For this purpose, impurities and imperfections were applied to the pin surface to investigate the effects on the process result. As a third step, strategies by means of laser intensity distributions were adapted to compensate for imperfections in the welding process. Finally, a sensor vision system is adapted for ideal welding results. Investigations are based on in situ synchrotron analysis at Petra III, DESY in Hamburg. For the experiments, a TRUMPF TruDisk laser (100/400 μm fiber diameter), a TRUMPF TruFiber 6000P (50/100 μm fiber diameter), and a single-mode fiber laser (14 μm fiber diameter) were used. The focal diameter was adjusted with the optical system depending on the investigation.

Cognitive Workload Evaluation of Onsite Workers Collaborating with a Teleoperated Robot during Assembly Tasks Using Heart Rate

Incorporating collaborative robots in modern industry has given rise to the synergistic collaboration between humans and robots. Working along with a teleoperated robot enables completion of tasks across geographical boundaries and has the potential to address the skills gap in manufacturing by enhancing future distributed manufacturing environments. In this study, we investigated cognitive demands of onsite workers in two different collaboration scenarios: (1) Human-Human (HH) and (2) Teleoperator-Robot-Human (tRH), during wire assembly tasks with varying physical and cognitive workloads. Under an additional cognitive task condition, the perceived effort (measured by NASA-TLX) for HH (57.8 ± 26.4) was significantly higher than for tRH (31.6 ± 26.5). However, no significant differences in heart rate were found between HH and tRH. These findings suggest that tRH might not introduce additional cognitive demands compared to HH collaboration, despite the lack of in-person and/or less direct communication.

Optimization Algorithms and Their Applications and Prospects in Manufacturing Engineering.

In modern manufacturing, optimization algorithms have become a key tool for improving the efficiency and quality of machining technology. As computing technology advances and artificial intelligence evolves, these algorithms are assuming an increasingly vital role in the parameter optimization of machining processes. Currently, the development of the response surface method, genetic algorithm, Taguchi method, and particle swarm optimization algorithm is relatively mature, and their applications in process parameter optimization are quite extensive. They are increasingly used as optimization objectives for surface roughness, subsurface damage, cutting forces, and mechanical properties, both for machining and special machining. This article provides a systematic review of the application and developmental trends of optimization algorithms within the realm of practical engineering production. It delves into the classification, definition, and current state of research concerning process parameter optimization algorithms in engineering manufacturing processes, both domestically and internationally. Furthermore, it offers a detailed exploration of the specific applications of these optimization algorithms in real-world scenarios. The evolution of optimization algorithms is geared towards bolstering the competitiveness of the future manufacturing industry and fostering the advancement of manufacturing technology towards greater efficiency, sustainability, and customization.

An ethical framework for human-robot collaboration for the future people-centric manufacturing: A collaborative endeavour with European subject-matter experts in ethics

Envisioning humans and (smart) robots collaboratively working on the manufacturing shop floor, sharing spaces, tasks and objectives, reflects the ambitious goal that the ideal factory of the future aspires to attain. However, ensuring the effective implementation of this novel form of labour organisation remains an ongoing area of research. Key aspects such as the future role of workers, potential psychological risks, and the overall ethical considerations of human-robot (H-R) collaboration warrant further investigation until the underpinning safety challenges have been addressed. This study presents a novel ethical framework for H-R collaboration in manufacturing, which involved 30 subject-matter experts in ethics within the European context in a collaborative design process conducted through a year-long three-round data collection qualitative Delphi study. The ethical framework adopts a human-centric approach, recognising the influences that expand beyond the specific context of H-R dynamics on the shop floor, towards organisational and societal governance for a more responsible integration of (smart) robotics into the professional settings. Ethics, in this regard, aims to foster ethical awareness and accountability in the processes and practices of design and innovation, involving all stakeholders who play a role in shaping the future of Industry 5.0.