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Near-net-shaped processes of jet engine blade have better performance in both reducing the material waste during production and improving work reliability in service, while the geometric features of blade, both sculptured surface and thin-walled shape, make the precise machining of blade challenging and difficult owing to its dynamics behaviors under complex clamping and machining loads. This paper aims to present a fundamental approach on modeling and performance analysis of the blade–fixture system.

A computerized framework on the complex blade–fixture dynamic behavior has been developed. Theoretical mechanic analysis on blade fixturing and machining is proposed with an especial emphasis on the boundary conditions of the blade–fixture system. Then the finite element analysis (FEA) method is used to simulate the variation trend of preloads, stiffness and blade distortion. The strong influence of parameters of workpiece–fixture configuration on blade distortion and machining error is investigated.

With a case of real jet engine blade machining, the experimental results and theoretical predictions suggest good agreement on their variation tendency. The loaded pressure of clamps has a critical influence on the total stiff performance of the blade–fixture system, and the profile error of the blade contributes much to the inconsistency in geometric dimension and surface integrity of blades’ machining. In the end, the results also validate the effectiveness of this methodology to predict and improve the performance of the blade–fixture configuration design.

The adaptive machining of near-net-shaped jet engine blade is a new high-performance manufacturing technology in aerospace production. This study provides a fundamental methodology for the performance analysis of blade-fixture system, to clear the variation law of blade distortion during preloading and machining, which will contribute to minimize the machining error and improve productivity.

The paper aims to propose a novel dual-stage shape memory alloy (SMA) actuated gripper (DAG), of which the grasp performance is improved through primary and secondary actuation.

This paper presents a method of integrating the design of dual-stage actuation modules based on the SMA bias actuation principle to enhance the grasping shape adaptability and force modulation of a DAG. The actuation angle range and grasping performance of the DAG are investigated by thermomechanical analysis and the finite element method based numerical simulation.

The results of present experiments and simulations indicate that the actuation angle scope of the DAG is about 20° under no load, which enables the grasping space occupied by an object in the DAG from 60 mm to 120 mm. The grasping force adjusted by changing the input power of the primary main actuation module and secondary fine-tuning actuation module can reach a maximum of 2 N, which is capable of grasping objects of various sizes, weights, shapes, etc.

The contribution of this paper is to design a DAG based on SMA, and establish the solution methods for the primary main actuation module and secondary fine-tuning actuation module, respectively. It lays a foundation for the research of lightweight and intelligent robotic grippers.

The purpose of this paper is to build a System Dynamics model to reveal the structure and dynamics of knowledge coupling affecting firms' innovation results in the digital context.

Drawing on the recombined view of innovation, this paper divides knowledge coupling into two dimensions: component knowledge coupling and architectural knowledge coupling. Then, the authors build a system dynamics model to identify the interaction of knowledge coupling factors and use the professional Vensim PLE to conduct simulation analysis to capture the dynamic interaction of motivation factors in knowledge coupling system.

The results show that both technology resources and digital dynamic capability play positive effects in the mechanism of knowledge coupling influencing firms' innovation results, while organizational inertia negatively affects the process of knowledge coupling to achieve innovation outcomes.

This study develops a holistic system dynamics model to reveal and elaborate on the complex dynamic mechanism of knowledge coupling impacting firms' innovation results in the context of digitization and provides a theoretical reference for companies to effectively adopt digital technology to carry out knowledge coupling strategy.

This paper aims to demonstrate how to make emergency decision when decision makers face a complex and turbulent environment that needs quite different decision-making processes from conventional ones. Traditional decision techniques cannot meet the demands of today’s social stability and security.

The main work is to develop an instance-driven classifier for the emergency categories based upon three fuzzy measures: features for an instance, solution for the instance and effect evaluation of the outcome. First, the information collected from the past emergency events is encodes into a prototype model. Second, a three-dimensional space that describes the locations and mutual distance relationships of the emergency events in different emergency prototypes is formulated. Third, for any new emergency event to be classified, the nearest emergency prototype is identified in the three-dimensional space and is classified into that category.

An instance-driven classifier based on prototype theory helps decision makers to describe emergency concept more clearly. The maximizing deviation model is constructed to determine the optimal relative weights of features according to the characteristics of the new instance, such that every customized feature space maximizes the influence of features shared by members of the category. Comparisons and discusses of the proposed method with other existing methods are given.

To reduce the affection to economic development, more and more countries have recognized the importance of emergency response solutions as an indispensable activity. In a new emergency instance, it is very challengeable for a decision maker to form a rational and feasible humanitarian aids scheme under the time pressure. After selecting a most suitable prototype, decision makers can learn most relevant experience and lessons in the emergency profile database and generate plan for the new instance. The proposed approach is to effectively make full use of inhomogeneous information in different types of resources and optimize resource allocation.

The combination of instances can reflect different aspects of a prototype. This feature solves the problem of insufficient learning data, which is a significant characteristic of emergency decision-making. It can be seen as a customized classification mechanism, while the previous classifiers always assume key features of a category.

This study aims to review the recent advancements in high entropy alloys (HEAs) called high entropy materials, including high entropy superalloys which are current potential alternatives to nickel superalloys for gas turbine applications. Understandings of the laser surface modification techniques of the HEA are discussed whilst future recommendations and remedies to manufacturing challenges via laser are outlined.

Materials used for high-pressure gas turbine engine applications must be able to withstand severe environmentally induced degradation, mechanical, thermal loads and general extreme conditions caused by hot corrosive gases, high-temperature oxidation and stress. Over the years, Nickel-based superalloys with elevated temperature rupture and creep resistance, excellent lifetime expectancy and solution strengthening L12 and γ´ precipitate used for turbine engine applications. However, the superalloy’s density, low creep strength, poor thermal conductivity, difficulty in machining and low fatigue resistance demands the innovation of new advanced materials.

HEAs is one of the most frequently investigated advanced materials, attributed to their configurational complexity and properties reported to exceed conventional materials. Thus, owing to their characteristic feature of the high entropy effect, several other materials have emerged to become potential solutions for several functional and structural applications in the aerospace industry. In a previous study, research contributions show that defects are associated with conventional manufacturing processes of HEAs; therefore, this study investigates new advances in the laser-based manufacturing and surface modification techniques of HEA.

The AlxCoCrCuFeNi HEA system, particularly the Al0.5CoCrCuFeNi HEA has been extensively studied, attributed to its mechanical and physical properties exceeding that of pure metals for aerospace turbine engine applications and the advances in the fabrication and surface modification processes of the alloy was outlined to show the latest developments focusing only on laser-based manufacturing processing due to its many advantages.

It is evident that high entropy materials are a potential innovative alternative to conventional superalloys for turbine engine applications via laser additive manufacturing.

Purpose: The purpose of this study is to assess the main and interaction effects of activity-based costing (ABC), internal information systems integration (IISI), and external information systems integration (EISI) on manufacturing plant operational performance, controlling for plant characteristics.

Methodology/approach: The study uses survey data from a cross-section of 369 U.S. manufacturing plants. Data were analyzed using hierarchical regression model.

Findings and implications: The results indicate partial support for the main and two-way interaction effects on plant operational performance. The three-way interaction effects are significant and positive, suggesting that deploying all three resources (i.e., ABC, IISI, and EISI) leads to the higher plant operational performance.

Originality/value: The paper significantly extends prior research and contributes to the understanding of the main and interaction effects of ABC, IISI, and EISI on manufacturing plant operational performance. The paper would also be of interest to practitioners interested in keeping up with academic literature.

In developed markets, emerging market multinational enterprises (EMNEs) seem to be more discriminated by host country nationals than foreign developed market multinational enterprises (DMNEs). They are challenged with host country nationals’ prejudices and face a stigma of being from emerging markets. While literature agrees that EMNEs suffer from additional disadvantages due to their country-of-origin, research fails to identify those factors that may lead to a higher discrimination against EMNEs than against foreign DMNEs.

Based on institutional theory, we look at institutional-related and resource-related antecedents that have an impact on various forms of direct and indirect discrimination by host country nationals.

Our framework analyzes the crucial differences between host country nationals’ perception of EMNEs and foreign DMNEs and the resulting challenges for EMNEs in the developed world. It enhances our understanding of the importance of institutional environments in explaining differences in host country nationals’ discrimination against foreign MNEs.

This paper aims to study the effect of laser energy on the formability, microstructure and mechanical properties of AZ61D alloy to assist systematic study of laser additive manufacturing of magnesium alloys.

In this study, porous magnesium alloy samples were prepared by using different laser parameters. The changes of the formability and microstructure were observed by SEM, and the mechanical properties were tested. The above results were analyzed to obtain optimized laser parameters.

When the laser power is between 85 and 95 W (pulse width 3.0 ms, frequency 40 Hz), the surface morphology of the selective laser-melted (SLMed) porous samples are smooth and even. At 80 W, SLMed porous samples have a maximum relative density of 99.2 per cent. Because of the “solute capture” effect and the evaporization of magnesium, the fraction of ß-Mg17Al12 increases from 42.1 to 52.1 per cent when power rises from 80 to 105 W. The ultimate compressive strength of SLMed porous magnesium alloys is strengthened with the increase of laser power.

The effect of laser parameters on microstructure and mechanical properties of porous magnesium alloys prepared by SLM has not been reported.

This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO₂ emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.

To better understand contributing factors and mediating mechanisms related to team dynamics in isolated, confined, and extreme (ICE) environments.

Literature review.

Our primary focus is on cohesion and adaptation – two critical aspects of team performance in ICE environments that have received increased attention in both the literature and funding initiatives. We begin by describing the conditions that define ICE environments and review relevant individual biological, neuropsychiatric, and environmental factors that interact with team dynamics. We then outline a unifying team cohesion framework for long-duration missions and discuss several environmental, operational, organizational, and psychosocial factors that can impact team dynamics. Finally, we end with a discussion of directions for future research and countermeasure development, emphasizing the importance of temporal dynamics, multidisciplinary integration, and novel conceptual frameworks for the inherently mixed work and social setting of long-duration missions in ICE environments.

A better understanding of team dynamics over time can contribute to success in a variety of organizational settings, including space exploration, defense and security, business, education, athletics, and social relationships.

We promote a multidisciplinary approach to team dynamics in ICE environments that incorporates dynamic biological, behavioral, psychological, and organizational factors over time.