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This paper is devoted to prepare micro-cone structure with variable cross-section size by Stereo Lithography Appearance (SLA)-based 3D additive manufacturing technology. It is mainly focused on analyzing the forming mechanism of equipment and factors affecting the forming quality and accuracy, investigating the influence of forming process parameters on the printing quality and optimization of the printing quality. This study is expected to provide a µ-SLA surface preparation technology and process parameters selection with low cost, high precision and short preparation period for microstructure forming.

The µ-SLA process is optimized based on the variable cross-section micro-cone structure printing. Multi-index analysis method was used to analyze the influence of process parameters. The process parameter influencing order is determined and validated with flawless micro array structure.

After the optimization analysis of the top diameter size, the bottom diameter size and the overall height, the influence order of the printing process parameters on the quality of the micro-cone forming is: exposure time (B), print layer thickness (A) and number of vibrations (C). The optimal scheme is A1B3C1, that is, the layer thickness of 5 µm, the exposure time of 3000 ms and the vibration of 64x. At this time, the cone structure with the bottom diameter of 50 µm and the cone angle of 5° could obtain a better surface structure.

This study is expected to provide a µ-SLA surface preparation technology and process parameters selection with low cost, high precision and short preparation period for microstructure forming.

Aircraft structures are mainly connected by riveting joints, whose quality and mechanical performance are directly determined by vertical accuracy of riveting holes. This paper proposed a combined vertical accuracy compensation method for drilling and riveting of aircraft panels with great variable curvatures.

The vertical accuracy compensation method combines online and offline compensation categories in a robot riveting and drilling system. The former category based on laser ranging is aimed to correct the vertical error between actual and theoretical riveting positions, and the latter based on model curvature is used to correct the vertical error caused by the approximate plane fitting in variable-curvature panels.

The vertical accuracy compensation method is applied in an automatic robot drilling and riveting system. The result reveals that the vertical accuracy error of drilling and riveting is within 0.4°, which meets the requirements of the vertical accuracy in aircraft assembly.

The proposed method is suitable for improving the vertical accuracy of drilling and riveting on panels or skins of aerospace products with great variable curvatures without introducing extra measuring sensors.

Focusing on the specific context of two European old industrial regions – South Yorkshire (UK) and North Region of Portugal – this paper aims to identify and conceptualise a set of relational capabilities that business leaders perceive to play a key role in industrial rejuvenation.

A qualitative research design operationalised via case studies was followed for the empirical analysis. Data collection was developed through in-depth interviews with managing directors in small and medium-sized enterprises (SMEs) belonging to the metal and engineering industry and the textile and footwear sectors in the two old industrial regions. Data analysis followed the techniques of data categorisation, within case-analysis and cross-case analysis.

The study identifies relational capabilities that firms use to identify, access and leverage new knowledge: frequent meetings with customers; frequent meetings with suppliers; dialogue with government to influence policy that encourages research and technology transfer; partnership actions for the commercialisation of products and services; active membership with sector associations; immersion in science and technological parks; intentionally establishing links with entrepreneurship-supporting entities; human resources development by technical training institutions; and systematic links with the University. The relational capabilities identified require structured communication processes and alliance management practices to enable and support absorptive capacity and learning in inter-organisational networks.

The relational capabilities identified can help position regions in specific markets and value chains, contribute to improving regions’ internal and external connections and assist in combining regions’ strengths to create industrial capability in high-growth-potential areas.

This paper highlights the role of relational capabilities as a way to secure access to knowledge and competencies needed for firms’ innovation and avoidance of competency traps. This is particularly relevant in the context of European smart specialisation policy, where key regional stakeholders collectively engage in the identification of areas of competitive strength, enhanced coordination and strategic alignment of resources. The study is not without limitations, as findings are based on case studies of SMEs operating in the manufacturing industry and the analysis of relational capabilities is focused on knowledge novelty.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

Molecular dynamics is an emerging simulation technique in the field of machining in recent years. Many researchers have tried to simulate different processing methods of various materials with the theory of molecular dynamics (MD), and some preliminary conclusions have been obtained. However, the application of MD simulation is more limited compared with traditional finite element model (FEM) simulation technique due to the complex modeling approach and long computation time. Therefore, more studies on the MD simulations are required to provide a reliable theoretical basis for the nanoscale interpretation of grinding process. This study investigates the crystal structures, dislocations, force, temperature and subsurface damage (SSD) in the grinding of iron-nickel alloy using MD analysis.

In this study the simulation model is established on the basis of the workpiece and single cubic boron nitride (CBN) grit with embedded atom method and Morse potentials describing the forces and energies between different atoms. The effects of grinding parameters on the material microstructure are studied based on the simulation results.

When CBN grit goes through one of the grains, the arrangement of atoms within the grain will be disordered, but other grains will not be easily deformed due to the protection of the grain boundaries. Higher grinding speed and larger cutting depth can cause greater impact of grit on the atoms, and more body-centered cubic (BCC) structures will be destroyed. The dislocations will appear in grain boundaries due to the rearrangement of atoms in grinding. The increase of grinding speed results in the more transformation from BCC to amorphous structures.

This study is aimed to study the grinding of Fe-Ni alloy (maraging steel) with single grit through MD simulation method, and to reveal the microstructure evolution within the affected range of SSD layer in the workpiece. The simulation model of polycrystalline structure of Fe-Ni maraging steel and grinding process of single CBN grit is constructed based on the Voronoi algorithm. The atomic accumulation, transformation of crystal structures, evolution of dislocations as well as the generation of SSD are discussed according to the simulation results.

This paper aims to carry out tribological experiments to explore the applications of femtosecond laser surface texturing technology on rock bit sliding bearing to enhance the lifetime and working performance of rock bit sliding bearing under high temperature and heavy load conditions.

Surface textures on beryllium bronze specimen were fabricated by femtosecond laser ablation (800 nm wavelength, 40 fs pulse duration, 1 kHz pulse repetition frequency), and then the tribological behaviors of pin-on-disc configuration of rock bit bearing were performed with 20CrNiMo/beryllium bronze tribo-pairs under non-Newtonian lubrication of rock bit grease.

The results showed that the surface texture on beryllium bronze specimens with specific geometrical features can be achieved by optimizing femtosecond laser processing via adjusting laser peak power and exposure time; more than 52 per cent of friction reduction was obtained from surface texture with a depth-to-diameter ratio of 0.165 and area ratio of 5 per cent at a shear rate of 1301 s−1 under the heavy load of 20 MPa and high temperature of 120°C, and the lubrication regime of rock bit bearing unit tribo-pairs was improved from boundary to mixed lubrication, which indicated that femtosecond laser ablation technique showed great potential in promoting service life and working performance of rock bit bearing.

Femtosecond laser-irradiated surface texture has the potential possibility for application in rock bit sliding bearing to improve the lubrication performance. Because proper micro dimples showed good lubrication and wear resistance performance for unit tribo-pairs of rock bit sliding bearing under high temperature, heavy load and non-Newtonian lubrication conditions, which is very important to improve the efficiency of breaking rock and accelerate the development of deep-water oil and gas resources.

Smart factory is the most important feature of the fourth industrial revolution in the manufacturing field. In this paper, we introduce smart factory solutions suggested by the major solution providers. Furthermore, we classify solutions by the category of three value-chain activities: product development activity, product manufacturing activity, and sales activity. In addition, the status-of-art and best practices of the smart factory solutions are introduced. To examine the current trends of smart factories, we classified the manufacturing industries into four groups based on two factors: product variety and production volumes, and suggest directions for the successful application of smart factories in each industry group. Finally, we suggest strategies to improve the actual manufacturing competitiveness of factories.

Straightness measurement of rail weld joint is of essential importance to railway maintenance. Due to the lack of efficient measurement equipment, there has been limited in-depth research on rail weld joint with a 5-m wavelength range, leaving a significant knowledge gap in this field.

In this study, the authors used the well-established inertial reference method (IR-method), and the state-of-the-art multi-point chord reference method (MCR-method). Two methods have been applied in different types of rail straightness measurement trollies, respectively. These instruments were tested in a high-speed rail section within a certain region of China. The test results were ultimately validated through using traditional straightedge and feeler gauge methods as reference data to evaluate the rail weld joint straightness within the 5-m wavelength range.

The research reveals that IR-method and MCR-method produce reasonably similar measurement results for wavelengths below 1 m. However, MCR-method outperforms IR-method in terms of accuracy for wavelengths exceeding 3 m. Furthermore, it was observed that IR-method, while operating at a slower speed, carries the risk of derailing and is incapable of detecting rail weld joints and low joints within the track.

The research compare two methods’ measurement effects in a longer wavelength range and demonstrate the superiority of MCR-method.

This paper aims to examine how long-lived firms can further develop through digitalisation in terms of actions, conditions and effects from a competitiveness perspective.

This exploratory study follows an inductive approach based on a survey conducted via interviews undertaken with nine long-lived Italian firms. The dimensions of the model (command, continuity, community, connection), elaborated by Miller and Le Breton-Miller (2005) in relation to longevity factors, were chosen to analyse digitalisation’s contribution to these long-lived firms’ development.

The digitalisation implemented by the analysed firms contributed in a variety of ways: (1) improved the efficiency and effectiveness of their business processes, (2) enhanced the understanding of customer experience, (3) supported their craftsmanship and the transmission of the knowledge included in the entrepreneurial path, (4) increased the awareness of the cultural value of the firms’ heritage and (5) allowed for the development of cutting-edge design skills by experimenting with content on different digital platforms and devices.

This study suggests managers of long-lived firms develop digital skills that allow them to interact with the rapid evolution of this context and understand how to effectively implement digitalisation in their specific firm. From this perspective, it is strategic to establish or strengthen collaborative network relationships to acquire such necessary skills.

This study provides novel empirical evidence on how long-lived firms are facing the challenge of digitalisation in terms of actions, conditions and effects to improve their competitiveness and ensure their survival.

The purpose of this paper is to communicate a method to perform simultaneous topology optimization of component and support structures considering typical metal additive manufacturing (AM) restrictions and post-print machining requirements.

An integrated topology optimization is proposed using two density fields: one describing the design and another defining the support layout. Using a simplified AM process model, critical overhang angle restrictions are imposed on the design. Through additional load cases and constraints, sufficient stiffness against subtractive machining loads is enforced. In addition, a way to handle non-design regions in an AM setting is introduced.

The proposed approach is found to be effective in producing printable optimized geometries with adequate stiffness against machining loads. It is shown that post-machining requirements can affect optimal support structure layout.

This study uses a simplified AM process model based on geometrical characteristics. A challenge remains to integrate more detailed physical AM process models to have direct control of stress, distortion and overheating.

The presented method can accelerate and enhance the design of high performance parts for AM. The consideration of post-print aspects is expected to reduce the need for design adjustments after optimization.

The developed method is the first to combine AM printability and machining loads in a single topology optimization process. The formulation is general and can be applied to a wide range of performance and manufacturability requirements.