Wangyu Liu, Dong Sun, Aimin Tang and Mingke Li
Hydrogel is an excellent material for the fabrication of porous scaffold by mask-prototyping method. Different from the common commercial resin, hydrogel is hydrophilic and…
Abstract
Purpose
Hydrogel is an excellent material for the fabrication of porous scaffold by mask-prototyping method. Different from the common commercial resin, hydrogel is hydrophilic and hyperelastic, so that it cannot bear the conventional post-curing process to improve its mechanical properties. The purpose of this paper is to put forward a method to improve the curing bonding strength at the weak juncture of the porous hydrogel scaffold.
Design/methodology/approach
The working curve of the resin was obtained through the single layer cure experiment, and the energy accumulation model has been set up by MATLAB. Aimed at the specificity of material, a new method of partial curing on different kind of structure has been proposed. Under the same condition, only the tn2 needs to be changed to fabricate different test specimens with different accumulated energy between two layers. The tensile test is carried out with the authors’ preferred equipment.
Findings
The analysis reveals that accumulated energy can be changed by adjusting the key parameters, and the tensile test shows that when the accumulated energy is bigger, the ultimate tensile strength is higher.
Research limitations/implications
Subject to the equipment accuracy and specificity of material, some errors coming from the experiment and test might exist, but the authors believe they will not change their findings and conclusions in this paper.
Practical implications
The research provides a method which is different from the common methods but friendlier to improve the bonding strength of the hydrogel scaffold.
Social implications
This work can help to adjust the mechanical property of the scaffold used in tissue engineering.
Originality/value
This method can improve the bonding strength at weak juncture and give a direction for the design of porous scaffold.
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Mingke Li and Wangyu Liu
The purpose of this paper is to present the novel parameterized digital-mask generation method which is aimed at enhancing bio-scaffold’s fabricating efficiency with digital…
Abstract
Purpose
The purpose of this paper is to present the novel parameterized digital-mask generation method which is aimed at enhancing bio-scaffold’s fabricating efficiency with digital micro-mirror device (DMD)-based systems.
Design/methodology/approach
A method to directly generate the digital masks of bio-scaffolds without modeling the entire 3D scaffold models is presented. In most of the conventional methods, it is inefficient to dynamically modify the size of the structural unit cells during design, because it relies more or less on commercial computer aided design (CAD) platforms. The method proposed in this paper can achieve high efficient parameterized design, and it is independent from any CAD platforms. The generated masks in binary bitmap format can be used by the DMD-based to achieve scaffold’s additive manufacture. In conventional methods, the Boolean operation of the external surface and the internal architectures would result in the damage of unit cells in boundary region. These damaged unit cells not only lose its original mechanical property but also cause numbers of gaps and isolated features that would reduce the geometric accuracy of the fabricated scaffolds; the proposed method in this paper provides an approach to tackle this defect.
Findings
The results show that the proposed method can improve the digital masks generation efficiency.
Practical implications
The proposed method can serve as an effective supplement to the slicing method in additive manufacture. It also provides a way to design and fabricate scaffolds with heterogeneous architectures.
Originality/value
This paper gives supports to fabricate bio-scaffold with DMD-based systems.
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Wangyu Liu and Mingke Li
This paper aims to propose the new two-step adaptive direct slicing method for building bio-scaffold with digital micro-mirror device (DMD)-based MPμSLA systems.
Abstract
Purpose
This paper aims to propose the new two-step adaptive direct slicing method for building bio-scaffold with digital micro-mirror device (DMD)-based MPμSLA systems.
Design/methodology/approach
In this paper, the authors proposed a new approach to directly slice a scaffold’s CAD model (i.e the three-dimensional model built by computer-aided design platforms) and save the slices’ data as BMP (bitmap, i.e. the data format used in DMD) files instead of other types of two-dimensional patterns as an intermediary. The proposed two-step strategy in this paper, i.e. a CAD model’s exterior surface and internal architecture were sliced, respectively, at first, and then assembled together to obtain one intact slice. The assembly process is much easier and convenient based on the slice data in BMP format. To achieve the adaptive slicing for both the exterior part and internal part, two new indices, the exterior surface-dominated index and internal architecture-dominated index, are, respectively, utilized as the error estimation indices. The proposed approach in this paper is developed on SolidWorks platform, but it can also be implemented on other platforms.
Findings
The authors found that the approach is not only more accurate but also more efficient by avoiding the repeated running of those inefficient rasterization programs. The approach is able to save computer resource and time, and enhance the robustness of slicing program, as well as is appropriate for the scaffolds’ model with internal pore architecture and external free-form surface.
Practical implications
Bio-scaffolds in tissue engineering require precise control over material distribution, such as the porosity, connectivity, internal pore architecture and external free-form surface. The proposed two-step adaptive direct slicing approach is a good balance of slicing efficiency and accuracy and can be useful for slicing bio-scaffolds’ models.
Originality/value
This paper gives supports to build bio-scaffold with DMD-based MPμSLA systems.
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Mingke Ouyang, Jianfei Li, Bei Li, Kun Tang and Fuhua Huang
In the new retail era, the supply chain synergy produced by quality integration has become the new direction of service supply chain research. The purpose of this paper is to…
Abstract
Purpose
In the new retail era, the supply chain synergy produced by quality integration has become the new direction of service supply chain research. The purpose of this paper is to study how to promote the sustainable development of the retail service supply chain (RSSC) by comparing and analyzing the optimal quality behavior, optimal returns, and the combination of conditions and strategies of the participating members of the RSSC.
Design/methodology/approach
From the perspective of quality function development and service quality concern, this paper considers RSSC as a two-level supply chain structure composed of functional service provider and retail service integrator. In this paper, a dynamic optimization model of quality input-cooperation-coordination of RSSC is proposed under two quality cooperation modes of decentralization and integration. This paper adopts the differential game method to compare and analyze the optimal quality behavior, optimal income, forming conditions and strategic combination of the participating members of the RSSC in different situations.
Findings
(1) Compared with quality dispersion, quality integration has more significant Pareto improvement effect on quality behavior and optimal revenue of RSSC. (2) In the case of quality integration, the optimal revenue obtained by the service sharing model is generally better than that obtained by the retail alliance collaboration model. (3) Benefit distribution ratio and quality cost allocation determine the optimal quality behavior of participating members of the RSSC, and also become the key factors for participating members to choose the collaborative mode in the case of quality integration.
Originality/value
Based on the quality function development of RSSC, this paper introduces the concept of steady service quality, and discusses the relationship between the quality cooperation stability and the mode selection of RSSC. This provides a theoretical basis for how to build a RSSC with efficient operation and stable quality.
Details
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Xufan Zhang, Xue Fan and Mingke He
The challenges faced by China's high-end equipment manufacturing (HEEM) industry are becoming clearer in the process of global supply chain (GSC) reconfiguration. The purpose of…
Abstract
Purpose
The challenges faced by China's high-end equipment manufacturing (HEEM) industry are becoming clearer in the process of global supply chain (GSC) reconfiguration. The purpose of this study is to investigate how China's HEEM industry has been affected by the GSC reconfiguration, as well as its short- and long-term strategies.
Design/methodology/approach
The authors adopted a multi-method approach. Interviews were conducted in Phase 1, while a three-round Delphi survey was conducted in Phase 2 to reach consensus at the industry level.
Findings
The GSC reconfiguration affected China's HEEM supply chain (SC). Its direct effects include longer lead times, higher purchasing prices and inconsistent supply and inventory levels of key imported components and materials. Its indirect effects include inconsistent product quality and cash flows. In the short term, China's HEEM enterprises have sought to employ localized substitutes, while long-term strategies include continuous technological innovation, industry upgrades and developing SC resilience.
Originality/value
This study not only encourages Chinese HEEM enterprises to undertake a comprehensive examination of their respective industries but also provides practical insights for SC scholars, policymakers and international stakeholders interested in how China's HEEM industry adapts to the GSC reconfiguration and gains global market share.
Details
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Mingke Gao, Zhenyu Zhang, Jinyuan Zhang, Shihao Tang, Han Zhang and Tao Pang
Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and…
Abstract
Purpose
Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.
Design/methodology/approach
This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.
Findings
This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.
Originality/value
It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.
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Tao Pang, Wenwen Xiao, Yilin Liu, Tao Wang, Jie Liu and Mingke Gao
This paper aims to study the agent learning from expert demonstration data while incorporating reinforcement learning (RL), which enables the agent to break through the…
Abstract
Purpose
This paper aims to study the agent learning from expert demonstration data while incorporating reinforcement learning (RL), which enables the agent to break through the limitations of expert demonstration data and reduces the dimensionality of the agent’s exploration space to speed up the training convergence rate.
Design/methodology/approach
Firstly, the decay weight function is set in the objective function of the agent’s training to combine both types of methods, and both RL and imitation learning (IL) are considered to guide the agent's behavior when updating the policy. Second, this study designs a coupling utilization method between the demonstration trajectory and the training experience, so that samples from both aspects can be combined during the agent’s learning process, and the utilization rate of the data and the agent’s learning speed can be improved.
Findings
The method is superior to other algorithms in terms of convergence speed and decision stability, avoiding training from scratch for reward values, and breaking through the restrictions brought by demonstration data.
Originality/value
The agent can adapt to dynamic scenes through exploration and trial-and-error mechanisms based on the experience of demonstrating trajectories. The demonstration data set used in IL and the experience samples obtained in the process of RL are coupled and used to improve the data utilization efficiency and the generalization ability of the agent.