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The purpose of this paper is to investigate the effects of parameters on the liquid phase migration (LPM) during the freeze-form extrusion fabrication (FEF) process.

To carry out this study, three factors were systematically investigated using orthogonal design of experiments. These three parameters are the extrusion velocity, the extrusion interval time and the extrusion head length. An orthogonal array with nine test units was selected for the experiments. Range analysis and analysis of variance were used to analyze the data obtained by the orthogonal experiments to identify the order of significant factors on LPM.

It was found that the LPM decreased with the increase of extrusion velocity and increased with the lengthening of extrusion interval time and the length of the extrusion nozzle. The order of significant factors for the LPM were found to be extrusion velocity > extrusion nozzle length > extrusion interval time.

Using an orthogonal design of experiments and a statistical analysis method, the liquid content of extrudate can be predicted and appropriate process parameter values can be selected. This leads to the minimization of LPM during the FEF process. Also, this analysis method could be used to study the LPM in other paste extrusion processes.

This paper suggests that the factors have significant impact on LPM during FEF process. The following analysis in this paper is useful for FEF users when prediction of LPM is needed. This methodology could be easily applied to different materials and initial conditions for optimization of other FEF-type processes. The research can also help to get better understanding of LPM during the FEF process.

During the process of the robotic grinding and polishing operations on aero-engine blades, the key problem of calibration error lies in fixture error and uneven margin. To solve this problem, this paper aims to propose a novel method to achieve rapid online calibration of the workpiece coordinate system through laser-based measurement techniques.

The authors propose a calibration strategy based on point cloud registration algorithm. The main principle is presented as follows: aero blade mounted on clamping end-effector is hold by industry robot, the whole device is then scanned by a 3D laser scanner to obtain its surface point cloud, and a fast segmentation method is used to acquire the point cloud of the workpiece. Combining Super4PCS algorithm with trimmed iterative closest point, we can align the key points of the scanned point cloud and the sampled points of the blade model, thus obtaining the translation and rotation matrix for calculating the workpiece coordinate and machining allowance. The proposed calibration strategy is experimentally validated, and the positioning error, as well as the margin distribution, is finally analyzed.

The experimental results show that the algorithm can well accomplish the task of cross-source, partial data and similar local features of blade point cloud registration with high precision. The total time spent on point cloud alignment of 100,000 order of magnitude blade is about 4.2 s, and meanwhile, the average point cloud alignment error is reduced to below 0.05 mm.

An improved point cloud registration method is proposed and introduced into the calibration process of a robotic system. The online calibration technique improves the accuracy and efficiency of the calibration process and enhances the automation of the robotic grinding and polishing system.

The application of thermal barrier coatings (TBCs) allows aero-engine blades to operate at higher temperatures with higher efficiency. The preparation of the TBCs increases the surface roughness of the blade, which impacts the thermal cycle life and thermal insulation performance of the coating. To reduce the surface roughness of blades, particularly the blades with small size and complex curvature, this paper aims to propose a method for industrial robot polishing trajectory planning based on on-site measuring point cloud.

The authors propose an integrated robotic polishing trajectory planning method using point cloud processing technical. At first, the acquired point cloud is preprocessed, which includes filtering and plane segmentation algorithm, to extract the blade body point cloud. Then, the point cloud slicing algorithm and the intersection method are used to create a preliminary contact point set. Finally, the Douglas–Peucker algorithm and pose frame estimation are applied to extract the tool-tip positions and optimize the tool contact posture, respectively. The resultant trajectory is evaluated by simulation and experiment implementation.

The target points of trajectory are not evenly distributed on the blade surface but rather fluctuate with surface curvature. The simulated linear and orientation speeds of the robot end could be relatively steady over 98% of the total time within 20% reduction of the rest time. After polishing experiments, the coating roughness on the blade surface is reduced dramatically from Ra 7–8 µm to below Ra 1.0 µm. The removal of the TBCs is less than 100 mg, which is significantly less than the weight of the prepared coatings. The blade surface becomes smoothed to a mirror-like state.

The research on robotic polishing of aero-engine turbine blade TBCs is worthwhile. The real-time trajectory planning based on measuring point cloud can address the problem that there is no standard computer-aided drawing model and the geometry and size of the workpiece to be processed differ. The extraction and optimization of tool contact points based on point cloud features can enhance the smoothness of the robot movement, stability of the polishing speed and performance of the blade surface after polishing.

Private firms in China are like the third child in a family, constantly struggling to establish their position in an environment favoring their state-owned and collective siblings. The purpose of this paper is to discover some long-term-oriented legitimacy building strategies for private firms in China.

This paper examines the effect of both internal and external institutional factors on long-term legitimacy for private enterprises. The authors integrate stakeholder perspective and institutional theory to provide a framework of building sustainable legitimacy.

The authors’ framework delineates that a private company can build sustainable legitimacy through catering long-term legitimacy conferring to constituents such as customers, social responsibility and patriotism in the external institutional environment.

The authors’ framework further indicates how private firms could leverage internal institutional environment through developing appropriate mission, culture, leadership and human resources practices in conformity to the demands of constituents for gaining long-term legitimacy.

This paper is the first to address the short-term nature of legitimacy building strategies proposed in the past literature. In addition, it is also the first attempt to explore the multiplicity in legitimacy in China in search of long-term legitimacy building approaches.

The purpose of this paper is to optimize a new thin-walled cellular configurations with crashworthiness criteria, so as to improve the crashworthiness of components of a vehicle body.

ANSYS Parametric Design Language is used to create the parameterized models so that the design variables can be changed conveniently. Moreover, the surrogate technique, namely response surface method, is adopted for fitting objective and constraint functions. The factorial design and D-optimal criterion are employed to screen active parameters for constructing the response functions of the specific energy absorption and the peak crushing force. Finally, sequential quadratic programming-NLPQL is utilized to solve the design optimization problem of the new cellular configurations filled with multi-cell circular tubes under the axial crushing loading.

Two kinds of distribution modes of the cellular configurations are first investigated, which are in an orthogonal way and in a diamond fashion. After comparing the optimized configurations of the rectangular distribution with the annular distribution of the multi-cell fillers, it is found that the orthogonal way seems better in the aspects of crashworthiness than the diamond fashion.

The two new thin-walled cellular configuration are studied and optimized with the crashworthiness criteria. Study on the new cellular configurations is very valuable for improving the crashworthiness of components of a vehicle body. Meanwhile, the factorial design and the factor screening are adopted in the process of the crashworthiness optimization of the new thin-walled cellular configurations.

This paper aims to deal with the problems such as epistemic uncertainty, common cause failure (CCF) and dynamic fault behaviours that arise in complex systems and develop an effective fault diagnosis method to rapidly locate the fault when these systems fail.

First, a dynamic fault tree model is established to capture the dynamic failure behaviours and linguistic term sets are used to obtain the failure rate of components in complex systems to deal with the epistemic uncertainty. Second, a β factor model is used to construct a dynamic evidence network model to handle CCF and some parameters obtained by reliability analysis are used to build the fault diagnosis decision table. Finally, an improved Vlsekriterijumska Optimizacija I Kompromisno Resenje algorithm is developed to obtain the optimal diagnosis sequence, which can locate the fault quickly, reduce the maintenance cost and improve the diagnosis efficiency.

In this paper, a new optimal fault diagnosis strategy of complex systems considering CCF under epistemic uncertainty is presented based on reliability analysis. Dynamic evidence network is easy to carry out the quantitative analysis of dynamic fault tree. The proposed diagnosis algorithm can determine the optimal fault diagnosis sequence of complex systems and prove that CCF should not be ignored in fault diagnosis.

The proposed method combines the reliability theory with multiple attribute decision-making methods to improve the diagnosis efficiency.

This paper tries to examine attitude toward knowledge sharing (KS) for improving the innovation in medical services. So, this paper aims to analyze the influence of information technology (IT), staff, hospital cultures and patients and their families on the attitude toward KS and also examine the influence of attitude toward KS on innovation in medical services.

This paper presented a project plan that contains five research hypotheses, with attitude toward KS as a mediating construct. In this paper, Smart PLS 3.0 is implemented to study the calculation. The hypotheses are tested on data collected using structural equation modeling. Data was collected using questionnaires from a hospital in Iran. The statistical population of this research is unlimited. Through using the sample measurement method, the sample size for structural equations has come to be 384.

The results showed that all theories of the project are proved. Also, they indicated the importance of IT as an important factor in attitude toward KS and the latter's influence on the innovation in medical services. Furthermore, the attitude toward KS influences positively on innovation in medical services. As a general result, the managers of health organizations should empower employees to participate in decision-making and encourage them to resolve problems together and share medical information to promote innovation in medical services.

This research must be carefully defined and accepted because the study information had special restrictions. At first, a prejudice was created, because the sample was self-selected. Second, the participants were living in Iran. There were different cultures and lifestyles among countries. Third, this research sample consisted only of hospital staff and managers. Moreover, little empirical research has been conducted on this topic in Iran. Iran’s culture is considerably different from Western culture, and it is unknown whether the same questionnaire that is used in the Iran context can be used in the Western context. In further studies, this research could be extended to contain other psychosocial elements that permit KS in institutions and increase innovation.

The medical industry is knowledge-intensive, remains a competitive advantage and accumulates knowledge, and the hospitals are the main subject. The role of this research according to providing a functional-theoretical plan enables authorities and practitioners to access thoughts about efficient stimulation attitude toward KS on innovation in medical services in the health sector. Also, the findings of this study at the same time are implemented to study relations between knowledge-sharing elements such as enablers, processes and firm innovation capability.

Modern study design enables the relations between IT and other influential elements on attitude toward KS and innovation in medical services to be analyzed. This design determines the coexistence of the participation and contest relations among participants, which is not studied in past researches. From a management point of view, this research determined various elements essential to a successful attitude toward KS and investigated the usage of these elements for improving innovation in medical services.

An increasing number of Chinese enterprises are involved in cross-border mergers and acquisitions (M&As). However, few Chinese enterprises have achieved successful integration, which plays a critical role in enhancing performance. The important field of cultural integration is currently facing major challenges. To identify the reasons for these challenges, studies have analyzed why cultural integration succeeds or fails and have suggested that cultural differences between acquiring and acquired enterprises are the primary obstacles to cultural integration. However, it is unclear how success can be achieved. The paper aims to focus on cultural integration from the perspective of acculturation to describe the penetration of cultural elements in M&As.

In adopting acculturation as our theoretical lens, the authors use the case study method to answer the following research question: “how can the cultural integration of Chinese enterprises be successfully achieved?” Two typical cases are examined: Lenovo’s cultural integration with IBM’s personal computer (PC) division and Haier’s cultural integration with Sanyo home appliance. First, using the exploratory case study method, the Lenovo–IBM PC division case is analyzed. The characteristics and relationships between cultural environments, employee adoption methods and acculturation patterns are summarized to reveal a cultural integration path. Second, the Haier–Sanyo home appliance case is analyzed using the confirmative case study method to test the findings of the Lenovo–IBM PC division case.

The results indicate that it is critical to achieve a dynamic fit between cultural environments, employee adoption methods and acculturation patterns during each stage of cultural integration (exploration, experimentation, reinforcement and fixing). The three constructs of these stages reflect the following evolutionary paths: “isolate-introduce-learning-chance taking”, “detecting-icebreaking-interacting-remodeling” and “specialized sections-senior managers-managers-employees”.

These findings contribute to the development of cultural integration and acculturation theories and serve as a reference for Chinese enterprises wishing to implement cultural integration strategies.

This study aims to examine the relationship between employees’ psychological contract breach and two types of voice behavior based on the social exchange theory. Additionally, the study explores the role of globally responsible business leadership in buffering the negative impacts of psychological contract breach on voice.

Survey data was collected from Chinese full-time employees and the final sample size is 337. Partial least squares structural equation modeling was used to test the hypotheses.

Findings indicate that psychological contract breach (PCB) has a positive and significant impact on employee aggressive voice behavior (AVB), while its relationship with constructive voice behavior (CVB) is not significant. Furthermore, globally responsible business leadership (GRBL) weakens the negative relationship between PCB and CVB, while strengthens the positive relationship between PCB and AVB.

The findings assist organizations in better recognizing the detrimental consequences of psychological contract breach. Second, the findings serve as a reminder to managers of the benefits of displaying globally responsible business leadership. Third, managers should recognize the complexities of globally responsible business leadership.

First, this study sheds new light on the impact of PCB on employees’ desirable and undesirable proactive behaviors by investigating how and when psychological contract breach affects two types of voice behavior. Second, the moderating role of GRBL further enriches our understanding of how to buffer negative effects of PCB and the desirable function of GRBL. Third, this study enriches the social exchange theory by investigating whether the leader−employee relationship will compensate for the failure of organization−employee relationship.

This paper aims to design a multi-layer convolutional neural network (CNN) to solve biomimetic robot path planning problem.

At first, the convolution kernel with different scales can be obtained by using the sparse auto encoder training algorithm; the parameter of the hidden layer is a series of convolutional kernel, and the authors use these kernels to extract first-layer features. Then, the authors get the second-layer features through the max-pooling operators, which improve the invariance of the features. Finally, the authors use fully connected layers of neural networks to accomplish the path planning task.

The NAO biomimetic robot respond quickly and correctly to the dynamic environment. The simulation experiments show that the deep neural network outperforms in dynamic and static environment than the conventional method.

A new method of deep learning based biomimetic robot path planning is proposed. The authors designed a multi-layer CNN which includes max-pooling layer and convolutional kernel. Then, the first and second layers features can be extracted by these kernels. Finally, the authors use the sparse auto encoder training algorithm to train the CNN so as to accomplish the path planning task of NAO robot.