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This study aims to evaluate and assess the elastoplastic properties of Ti-6Al-4V alloy manufactured by Arcam Q20 Plus electron beam melting (EBM) machine by a tensile test campaign and micro computerized tomography (microCT) imaging.

ASTM E8 tensile test specimens are designed and manufactured by EBM at an Arcam Q20 Plus machine. Surface quality is improved by machining to discard the effect of surface roughness. After surface machining, hot isostatic pressing (HIP) post-treatment is applied to half of the specimens to remove unsolicited internal defects. ASTM E8 tensile test campaign is carried out simultaneously with digital image correlation to acquire strain data for each sample. Finally, build direction and HIP post-treatment dependencies of elastoplastic properties are analyzed by F-test and t-test statistical analyses methods.

Modulus of elasticity presents isotropic behavior for each build direction according to F-test and t-test analysis. Yield and ultimate strengths vary according to build direction and post-treatment. Stiffness and strength properties are superior to conventional Ti-6Al-4V material; however, ductility turns out to be poor for aerospace structures compared to conventional Ti-6Al-4V alloy. In addition, micro CT images show that support structure leads to dense internal defects and pores at applied surfaces. However, HIP post-treatment diminishes those internal defects and pores thoroughly.

As a novel scientific contribution, this study investigates the effects of three orthogonal build directions on elastoplastic properties, while many studies focus on only two-build directions. Evaluation of Poisson’s ratio is the other originality of this study. Furthermore, another finding through micro CT imaging is that temporary support structures result in intense defects closer to applied surfaces; hence high-stress regions of structures should be avoided to use support structures.

Structural health monitoring (SHM) has become an attractive subject in aerospace engineering field considering the opportunity to avoid catastrophic failures by detecting damage in advance and to reduce maintenance costs. Fibre Bragg Grating (FBG) sensors are denoted as one of the most promising sensors for SHM applications as they are lightweight, immune to electromagnetic effects and able to be embedded between the layers of composite structures. The purpose of this paper is to research on and demonstrate the feasibility of FBG sensors for SHM of composite structures.

Applications on thin composite beams intended for SHM studies are presented. The sensor system, which includes FBG sensors and related interrogator system, and manufacturing of the beams with embedded sensors, are detailed. Static tension and torsion tests are conducted to verify the effectiveness of the system. Strain analysis results obtained from the tests are compared with the ones obtained from the finite element analyses conducted using ABAQUS® software. In addition, the comparison between the data obtained from the FBG sensors and from the strain gauges is made by also considering the noise content. Finally, fatigue test under torsion load is conducted to observe the durability of FBG sensors.

The results demonstrated that FBG sensors are feasible for SHM of composite structures as the strain data are accurate and less noisy compared to that obtained from the strain gauges. Furthermore, the convenience of obtaining reliable data between the layers of a composite structure using embedded FBG sensors is observed.

Observing the advantages of the FBG sensors for strain measurement will promote using FBG sensors for damage detection related to the SHM applications.

This paper presents applications of FBG sensors on thin composite beams, which reveal the suitability of FBG sensors for SHM of lightweight composite structures.

The purpose of this paper is to detail the design of a fractional controller which was developed for the suppression of the flexural vibrations of the first mode of a smart beam.

During the design of the fractional controller, in addition to the classical control parameters such as the controller gain and the bandwidth; the order of the derivative effect was also included as another design parameter. The controller was then designed by considering the closed loop frequency responses of different fractional orders of Continued Fraction Expansion (CFE) method.

The first, second, third and fourth order approximations of CFE method were studied for the performance analysis of the controller. It was determined that the increase in the order resulted in better vibration level suppression at the resonance. The robustness analysis of the developed controllers was also conducted.

The experimentally obtained free and forced vibration results indicated that the increase in the order of the approximations yielded better performance around the first flexural resonance region of the smart beam and proved to yield better performance than the classical integer order controllers.

Evaluation of the performance of a developed fractional controller was realized by using different approach orders of the CFE method for the suppression of the flexural vibrations of a smart beam.

The COVID-19 pandemic and its related economic meltdown and social unrest severely challenged most countries, their societies, economies, organizations, and individual citizens. Focusing on both more and less successful country-specific initiatives to fight the pandemic and its multitude of related consequences, this chapter explores implications for leadership and effective action at the individual, organizational, and societal levels. As international management scholars and consultants, the authors document actions taken and their wide-ranging consequences in a diverse set of countries, including countries that have been more or less successful in fighting the pandemic, are geographically larger and smaller, are located in each region of the world, are economically advanced and economically developing, and that chose unique strategies versus strategies more similar to those of their neighbors. Cultural influences on leadership, strategy, and outcomes are described for 19 countries. Informed by a cross-cultural lens, the authors explore such urgent questions as: What is most important for leaders, scholars, and organizations to learn from critical, life-threatening, society-encompassing crises and grand challenges? How do leaders build and maintain trust? What types of communication are most effective at various stages of a crisis? How can we accelerate learning processes globally? How does cultural resilience emerge within rapidly changing environments of fear, shifting cultural norms, and profound challenges to core identity and meaning? This chapter invites readers and authors alike to learn from each other and to begin to discover novel and more successful approaches to tackling grand challenges. It is not definitive; we are all still learning.

This chapter aims to identify integrated marketing communication (IMC) in the context of business to business to consumer (B2B2C) and empirically test a number of hypotheses related to the selected constructs. A model of the IMC was tested in a survey conducted among stakeholders in the selected field. Professionals responsible for communication and branding activities need to evaluate the relative contributions of the IMC in the B2B2C perspective.

The purpose of this paper is to study the way in which family ties influence the entrepreneurial preparedness of the diaspora family business owner.

In-depth interviews were carried out with 15 Cypriot family business owners hosted in various countries. The paper draws on social capital theory and uses an abductive analytical approach.

The findings of this paper illustrate that family ties coming from the family across borders play a significant role for diaspora family business owners’ entrepreneurial preparedness. Hidden values deriving from the interpersonal relationships within the family across borders drive the diaspora family business owners to learn upon self-reflection and become entrepreneurially prepared, led by both urgency and esteem.

This study provides practical implications for the entrepreneurial preparedness of diaspora family business owners and those who wish to become family business owners in a diaspora context.

This study contributes theoretically through the conceptualization of “family across borders social capital” and “diaspora entrepreneurial preparedness”. It also contributes empirically to the fields of diaspora family business, entrepreneurial learning and diaspora entrepreneurship through new knowledge regarding the role of family across borders social capital in the entrepreneurial preparedness of the diaspora family business owner.

Expert systems are computer-based systems that mimic the logical processes of human experts or organizations to give advice in a specific domain of knowledge. Fuzzy expert systems use fuzzy logic to handle uncertainties generated by imprecise, incomplete and/or vague information. The purpose of this paper is to present a comprehensive review of the methods and applications in fuzzy expert systems.

The authors have carefully reviewed 281 journal publications and 149 conference proceedings published over the past 37 years since 1982. The authors grouped the journal publications and conference proceedings separately accordingly to the methods, application domains, tools and inference systems.

The authors have synthesized the findings and proposed useful suggestions for future research directions. The authors show that the most common use of fuzzy expert systems is in the medical field.

Fuzzy logic can be used to manage uncertainty in expert systems and solve problems that cannot be solved effectively with conventional methods. In this study, the authors present a comprehensive review of the methods and applications in fuzzy expert systems which could be useful for practicing managers developing expert systems under uncertainty.

The purpose of this paper is to improve autonomous flight performance of a fixed-wing unmanned aerial vehicle (UAV) via simultaneous morphing wingtip and control system design conducted with optimization, computational fluid dynamics (CFD) and machine learning approaches.

The main wing of the UAV is redesigned with morphing wingtips capable of dihedral angle alteration by means of folding. Aircraft dynamic model is derived as equations depending only on wingtip dihedral angle via Nonlinear Least Squares regression machine learning algorithm. Data for the regression analyses are obtained by numerical (i.e. CFD) and analytical approaches. Simultaneous perturbation stochastic approximation (SPSA) is incorporated into the design process to determine the optimal wingtip dihedral angle and proportional-integral-derivative (PID) coefficients of the control system that maximizes autonomous flight performance. The performance is defined in terms of trajectory tracking quality parameters of rise time, settling time and overshoot. Obtained optimal design parameters are applied in flight simulations to test both longitudinal and lateral reference trajectory tracking.

Longitudinal and lateral autonomous flight performances of the UAV are improved by redesigning the main wing with morphing wingtips and simultaneous estimation of PID coefficients and wingtip dihedral angle with SPSA optimization.

This paper originally discusses the simultaneous design of innovative morphing wingtip and UAV flight control system for autonomous flight performance improvement. The proposed simultaneous design idea is conducted with the SPSA optimization and a machine learning algorithm as a novel approach.

The integration of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) is an emerging model, and the global pressure of various stakeholders raises scepticism of any emerging model towards providing sustainability. Therefore, this research aims to identify and rank the potential significant drivers of an integrated model of I4.0 and TPM to guide manufacturing enterprises towards sustainability.

This research follows a four-phase methodology including literature review and expert opinion to select the sustainability indicators and I4.0-integrated TPM key drivers, followed by employing the analytic hierarchy process approach for weight determination of sustainability indicators. The research then deploys the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prioritise the I4.0-integrated TPM key drivers based on their effect on various sustainability indicators. Finally, a sensitivity analysis is conducted to check the robustness of the TOPSIS.

The findings establish the top five most influential key drivers of an I4.0-integrated TPM system, which include top management support, formal I4.0 adoption program, mid-management involvement and support, solid TPM baseline knowledge and high engagement of the production team. These top drives can lead manufacturing firms towards sustainability.

The digitalisation of shop floor practices, such as TPM, could be adapted by shop floor managers and policymakers of manufacturing companies to deliver sustainability-oriented outcomes. In addition, this research may aid decision-makers in the manufacturing sector in identifying the most important drivers of I4.0 and TPM, which will assist them in more effectively implementing an integrated system of I4.0 and TPM to practice sustainability. The scope of TPM applicability is wide, and the current research is limited to manufacturing companies. Therefore, there is a huge scope for developing and testing the integrated system of I4.0 and TPM in other industrial settings, such as the textile, food and aerospace industries.

This research makes a first-of-its-kind effort to examine how an I4.0-integrated TPM model affects manufacturing companies' sustainability and how such effects might be maximised.

Scholars have typically examined family business exposure as an aggregate variable. However, it is probable that this trend oversimplifies the complexity of family exposure and its nuanced influence on entrepreneurial behaviour. Thus, to extend the theoretical boundary, this inquiry investigates distinct dimensions of family exposure in Nigeria while drawing on the theory of planned behaviour.

Data were collected from five public universities in Nigeria. A sample of 1,314 respondents was analysed using a partial least squares structural equation modelling approach to determine the influence of alternate family business exposures.

The results show that entrepreneurial exposure in the forms of parent, family member and work involvement have salient and distinctive influences on implementation intention to the extent that entrepreneurial self-efficacy, attitudes and subjective norms are uniquely impacted.

This study offers novel insights on the predictors of entrepreneurial implementation intention through the distinctive effects of (1) family member exposure, (2) parent exposure and (3) work involvement exposure among students in the family firm context.