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The coupling impact of hybrid uncertain errors on the machine precision is complex, as a result of which the designing method with multiple independent error sources under uncertainties remains a challenge. For the purpose of precision improvement, this paper focuses on the robot design and aims to present an assembly precision design method based on uncertain hybrid tolerance allocation (UHTA), to improve the positioning precision of the mechanized robot, as well as realize high precision positioning within the workspace.

The fundamentals of the parallel mechanism are introduced first to implement concept design of a 3-R(4S) &3-SS parallel robot. The kinematic modeling of the robot is carried out, and the performance indexes of the robot are calculated via Jacobian matrix, on the basis of which, the 3D spatial overall workspace can be quantified and visualized, under the constraints of limited rod, to avoid the singular position. The error of the robot is described, and a probabilistic error model is hereby developed to classify the hybrid error sensitivity of each independent uncertain error source by Monte Carlo stochastic method. Most innovatively, a methodology called UHTA is proposed to optimize the robot precision, and the tolerance allocation approach is conducted to reduce the overall error amplitude and improve the robotized positioning precision, on the premise of not increasing assembly cost.

The proposed approach is validated by digital simulation of medical puncture robot. The experiment highlights the mathematical findings that the horizontal plane positioning error of the parallel robotic mechanism can be effectively reduced after using UHTA, and the average precision can be improved by up to 39.54%.

The originality lies in UHTA-based precision design method for parallel robots. The proposed method has widely expanding application scenarios in industrial robots, biomedical robots and other assembly automation fields.

The layer section of laser additive manufacturing (AM) can be rasterized. Subsequently, the rasterized layer section can be converted into sparse matrix. However, large storage space is occupied due to the high manufacturing resolution. In order to reduce the storage space, the purpose of this research is to propose a lossless compression method to compress the sparse matrix.

A lossless compression method for additive manufacturing is proposed. According to manifold and irregularity feature of the object of laser AM, a lossless compression method called continuous rows compressed storage (CRCS) based on continuous rows is innovatively proposed. In particular, the better direction strategy of compression method is selected based on the side-projected area per layer.

Take human teeth as an example, compared with compressed sparse row (CSR), the CRCS has advantage up to 98.88% in storage space. Compared with block compressed sparse row (BCSR), the CRCS has advantage up to 60.04% in storage space.

The proposed CRCS could be employed to compress the sparse matrixes of rasterized layer sections of laser AM. Compared with common lossless compression method of sparse matrix, the compression ratio of CRCS is greater. CRCS is propitious to reduce the storage space usage, thereby improving transmission efficiency.

This work aims to provide a rapid robust optimization design solution for parallel robots or mechanisms, thereby circumventing inefficiencies and wastage caused by empirical design, as well as numerous physical verifications, which can be employed for creating high-quality prototypes of parallel robots in a variety of applications.

A novel subregional meta-heuristic iteration (SMI) method is proposed for the optimization of parallel robots. Multiple subregional optimization objectives are established and optimization is achieved through the utilisation of an enhanced meta-heuristic optimization algorithm, which roughly employs chaotic mapping in the initialization strategy to augment the diversity of the initial solution. The non-dominated sorting method is utilised for updating strategies, thereby achieving multi-objective optimization.

The actuator error under the same trajectory is visibly reduced after SMI, with a maximum reduction of 6.81% and an average reduction of 1.46%. Meanwhile, the response speed, maximum bearing capacity and stiffness of the mechanism are enhanced by 63.83, 43.98 and 97.51%, respectively. The optimized mechanism is more robust and the optimization process is efficient.

The proposed robustness multi-objective optimization via SMI is more effective in improving the performance and precision of the parallel mechanisms in various applications. Furthermore, it provides a solution for the rapid and high-quality optimization design of parallel robots.

Most rapid prototyping (RP) relies on energy fields to handle materials, among which electricity has been much more utilized, resulting in distinctive responsiveness of non-linear, overshoot, variable inertia, etc. The purpose of this paper is to eliminate the drawbacks of array nozzle clogging, stringing, melt sagging, particularly in multi-material RP, by focusing on the electrothermal response so as to adaptively distribute thermal more accurate, rapid and balanced.

This paper presents an electrothermal response optimization method of nozzle structure for multi-material RP based on fuzzy adaptive control (FAC). The structural, physical and control model are successively logically built. The fractional order electrothermal model is identified by Riemann Liouville fractional differential equation, using the bisection method to approximate the physical model via least square method to minimize residual sum of squares. The FAC is thereafter implemented by defining fuzzy proportion integration differentiation control rules and fuzzy membership functions for fuzzy inference and defuzzification.

The transient thermodynamic and structural statics, as well as flow field analysis, are conducted. The response time, mean temperature difference and thermal deformation can be found using thermal-solid coupling finite element analysis. In physical experimental research, temperature change, together with material extrusion loading, were measured. Both numerical and physical studies have revealed findings that the electrothermal responsiveness varies with the three-dimensional structure, materials and energy sources, which can be optimized by FAC.

The proposed FAC provides an optimization method for extrusion-based multi-material RP between the balance of thermal response and energy efficiency through fulfilling potential of the hardware configuration. The originality may be widely adopted alongside increasing requirements on high quality and high efficiency RP.

A biomechanical design method of lightweight full contacted insole based on structural anisotropy bespoke (SAB) is proposed, which can better redistribute the stress distribution of SAB designed personalized insole.

The reconstructed joint biomechanics are simulated using finite element analysis (FEA) to develop a lightweight full contact insole. Innovatively, the anisotropic properties of the triply periodic minimal surface (TPMS) structure, which contribute to reducing insole weight, are considered to optimize stress distribution. Additionally, porosity and manufacturing time are included as design objectives. To validate the lightweight insole design, FEA is employed to simulate the stress distribution of the ergonomic insole, which can be fabricated by additive manufacturing (AM) with TPU.

With a little 0.924% loss in porosity, the maximum stress of lightweight SAB designed insoles is extremely decreased by 19.2917%.

The biomechanical design of the lightweight full contact insole based on SAB can effectively redistribute stress, avoid stress concentration and improve the mechanical properties of the ergonomic individual insole.

Compared with cusp height and area deviation ratio, volume error (VE) caused by the layer height could represent the stair-case effect more comprehensively. The proposed relative volume error (RVE)-based adaptive slicing method takes VE rather than cusp height as slicing criteria, which can improve part surface quality for functionalized additive manufacturing.

This paper proposes a volumetric adaptive slicing method of manifold mesh for rapid prototyping based on RVE. The pre-height sequences of manifold mesh are first preset to reduce the SE by dividing the whole layer sequence into several parts. A breadth-first search-based algorithm has been developed to generate a solid voxelization to get VE. A new parameter RVE is proposed to evaluate the VE caused by the sequence of the layer positions. The RVE slicing is conducted by iteratively adjusting the layer height sequences under different constraint conditions.

Three manifold models are used to verify the proposed method. Compared with uniform slicing with 0.2 mm layer height, cusp height-based method and area deviation-based method, the standard deviations of RVE of all three models are improved under the proposed method. The surface roughness measured by the confocal laser scanning microscope proves that the proposed RVE method can greatly improve part surface quality by minimizing RVE.

This paper proposes an RVE-based method to balance the surface quality and print time. RVE could be calculated by voxelized parts with required accuracy at a very fast speed by parallel.

This paper aims to explore how enterprise microblogging can influence consumer loyalty and thus generate business value for firms. The study aims to expand traditional brand community theory.

The paper is based on brand community theory, social identity theory and usage and gratifications theory. Using a pre-survey of the fans of an enterprise microblog and a random sample survey of such fans on Sina Weibo, the authors tested the structural equation model with LISREL, which includes multiple fit indices.

The paper provides empirical insights about how enterprise microblogging can influence consumer loyalty and thus generate business value for firms. It suggests that consumers’ perceived value could strengthen their microblog identification, which will influence their perceived relationship with the enterprise and its products directly and indirectly through the mediation of enterprise identification. Perceived relationship can further influence purchase and recommendation intentions.

Because of the chosen data collecting approach, the research results may be still subjective. Moreover, the study overlooks the effects of the different types of enterprise microblogging and consumers.

Enterprises should operate their official microblogging from the perspective of maintaining brand community to improve consumer loyalty. They can generate more value for consumers through their microblogging and predict the operating performance by evaluating the degree of consumers’ relationship perception.

This paper considers enterprise microblogging as a new form of virtual brand community and identifies its features, and expands theories of brand community, and social media/IT business value, social identity theory and gratifications theory.

Emerging markets face the developmental circumstances of a weak foundation in both manufacturing and services. Although servitization is viewed as an opportunity to realise industry transformation and upgrading, ways for emerging market firms to implement a high-level servitization strategy is still understudied. This study examines combinations of causal conditions for emerging market firms to implement a high level of servitization.

Anchored in the strategy tripod model, this study examines the configurations for implementing a high-level servitization strategy by using fuzzy-set qualitative comparative analysis (fsQCA) and data from the China Stock Market and Accounting Research Database (CSMAR).

The findings identify three kinds of configurations for achieving a high-level servitization strategy: market-cultivational servitization, competition-driven servitization and government-related servitization. Furthermore, the mechanisms for implementing a high-level servitization strategy differ within the regional marketization level and state-owned equity. Specifically, the improvement of the regional marketization level helps manufacturing firms realise a high level of servitization by strengthening service capacity, and state-owned equity helps firms gain distinctive legitimacy to integrate suppliers and providers into the servitization context.

The proposed multilevel perspective frameworks enable manufacturing firms in emerging markets to achieve a high level of servitization strategy.

This paper explores the impact of institutional environment, industry conditions and firm-level microfoundations on servitization, therefore providing a reference framework for emerging market firms interested in implementing high-level servitization strategies.

The purpose of this paper is to assess the application of the nascent corporate opportunity doctrine in China by comparison with its well-established English counterpart; in particular, it evaluates whether the fine balance between business integrity and business efficiency has been struck.

It is argued that the scope of application of the corporate opportunity doctrine in China should be extended, and the rules on the burden of proof should be amended. Moreover, a stricter approach should be adopted by the Chinese judiciary for the purpose of protecting the company’s interests and enhancing business integrity.

This paper mainly focuses on the corporate opportunity doctrine. It does not discuss other duties of directors in detail.

It is useful for directors in balancing business integrity and business efficiency.

It is an original piece of work which assesses the corporate opportunity doctrine by making comparison with English law.

This paper endeavors to create a predictive model for the energy consumption associated with the multi-material fused deposition modeling (FDM) printing process.

An online measurement system for monitoring power and temperature has been integrated into the dual-extruder FDM printer. This system enables a comprehensive study of energy consumption during the dual-material FDM printing process, achieved by breaking down the entire dual-material printing procedure into distinct operational modes. Concurrently, the analysis of the G-code related to the dual-material FDM printing process is carried out.

This work involves an investigation of the execution instructions that delineate the tooling plan for FDM. We measure and simulate the nozzle temperature distributions with varying filament materials. In our work, we capture intricate details of energy consumption accurately, enabling us to predict fluctuations in power demand across different operational phases of multi-material FDM 3D printing processes.

This work establishes a model for quantifying the energy consumption of the dual-material FDM printing process. This model carries significant implications for enhancing the design of 3D printers and advancing their sustainability in mobile manufacturing endeavors.