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The purpose of this paper is to present a Design for Additive Manufacturing (DfAM) methodology that connects several methods, from geometrical design to post-process selection, into a common optimisation framework.

A design methodology is formulated and tested in a case study. The outcome of the case study is analysed by comparing the obtained results with alternative designs achieved by using other design methods. The design process in the case study and the potential of the method to be used in different settings are also discussed. Finally, the work is concluded by stating the main contribution of the paper and highlighting where further research is needed.

The proposed method is implemented in a novel framework which is applied to a physical component in the case study. The component is a structural aircraft part that was designed to minimise weight while respecting several static and fatigue structural load cases. An addition goal is to minimise the manufacturing cost. Designs optimised for manufacturing by two different AM machines (EOS M400 and Arcam Q20+), with and without post-processing (centrifugal finishing) are considered. The designs achieved in this study show a significant reduction in both weight and cost compared to one AM manufactured geometry designed using more conventional methods and one design milled in aluminium.

The method in this paper allows for the holistic design and optimisation of components while considering manufacturability, cost and component functionality. Within the same framework, designs optimised for different setups of AM machines and post-processing can be automatically evaluated without any additional manual work.

This paper presents first sight on the longitudinal control strategy for an aircraft in the tandem wing configuration. It is an aerodynamic strongly coupled configuration that needs a lot of detailed aerodynamic analysis which describes the mutual impact of the main parts of the aircraft. The purpose of this paper is to build the numerical model that allows to make an analysis of necessary flaps (front and rear) deflection and prepare the control strategy for this kind of aircraft.

Aircrafts’ aerodynamic characteristics were obtained using the MGAERO software which is a commercial computing fluid dynamics tool created by Analytical Methods, Inc. This software uses the Euler flow model. Results from this software were used in the static stability evaluation and trim condition analysis. The trim conditions are the outcome of the optimisation process whose goal was to find the best front and rear flap deflection to achieve the best lift to drag (L/D) ratio.

The main outcome of this investigation is the proposal of strategy for the front and rear flap deflection which ensured the maximum L/D ratio and satisfied the trim condition. Moreover, the analysis of the mutual impact of the front and rear wings and the analysis of the control surface impact on the aerodynamic characteristic of the aircraft are presented.

In terms of aerodynamic computation, MGAERO software uses an inviscid flow model. However, this research is for the conceptual stage of the design and the MGAERO software grantee satisfied accurate respect to relatively low time of computations.

The ultimate goal is to build an aircraft in a tandem wing configuration and to conduct flying tests or wind tunnel tests. The presented result is one of the milestones to achieve this goal.

The aircraft in the tandem wing configuration is an aerodynamic-coupled configuration that needs detailed analysis to find the mutual interaction between the front and rear wings. Moreover, the mutual impact of the front and rear flaps is necessary too. Obtaining these results allowed this study to build the numerical model of the aircraft in the tandem wing configuration. It allows to find the best strategy of flap deflection, which allows to obtain the maximum L/D ratio and satisfy the trim condition.

The paper aims to investigate the comfort-related performances of an innovative solar shading solution based on a new composite patented material that consists of a cement-based matrix coupled with a stretchable three-dimensional textile. The paper’s aim is, through a performance-based generative design approach, to develop a high-performance static shading system able to guarantee adequate daylit spaces, a connection with the outdoors and a glare-free environment in the view of a holistic and occupant-centric daylight assessment.

The paper describes the design and simulation process of a complex static shading system for digital manufacturing purposes. Initially, the optical material properties were characterized to calibrate radiance-based simulations. The developed models were then implemented in a multi-objective genetic optimization algorithm to improve the shading geometries, and their performance was assessed and compared with traditional external louvres and overhangs.

The system developed demonstrates, for a reference office space located in Milan (Italy), the potential of increasing useful daylight illuminance by 35% with a reduced glare of up to 70%–80% while providing better uniformity and connection with the outdoors as a result of a topological optimization of the shape and position of the openings.

The paper presents the innovative nature of a new composite material that, coupled with the proposed performance-based optimization process, enables the fabrication of optimized shading/cladding surfaces with complex geometries whose formability does not require ad hoc formworks, making the process fast and economic.

The purpose of this paper is to achieve intelligent superstore site selection. Yonghui Superstores partnered with Cardinal Operations to incorporate a tremendous amount of site-related information (e.g. points of interest, population density and features, distribution of competitors, transportation, commercial ecosystem, existing own-store network) into its store site optimization.

This paper showcases the integration of regression, optimization and machine learning approaches in site selection, which has proven practical and effective.

The result was the development of the “Yonghui Intelligent Site Selection System” that includes three modules: business district scoring, intelligent site engine and precision sales forecasting. The application of this system helps to significantly reduce the labor force required to visit and investigate all potential sites, circumvent the pitfalls associated with possibly biased experience or intuition-based decision making and achieve the same population coverage as competitors while needing only half the number of stores as its competitors.

To our knowledge, this project is among the first to integrate regression, optimization and machine learning approaches in site selection. There is innovation in optimization techniques.

Tandem wing aircrafts belong to an unconventional configurations group, and this type of design is characterised by a strong aerodynamic coupling, which results in lower induced drag. The purpose of this paper is to determine whether a certain trend in the wingspan impact on aircraft dynamic stability can be identified. The secondary goal was to compare the response to control of flaps placed on a front and rear wing.

The aerodynamic data and control derivatives were obtained from the computational fluid dynamics computations performed by the MGAERO software. The equations of aircraft longitudinal motion in a state space form were used. The equations were built based on the aerodynamic coefficients, stability and control derivatives. The analysis of the dynamic stability was done in the MATLAB by solving the eigenvalue problem. The response to control was computed by the step response method using MATLAB.

The results of this study showed that because of a strong aerodynamic coupling, a nonlinear relation between the wing size and aircraft dynamic stability proprieties was observed. In the case of the flap deflection, stronger oscillation was observed for the front flap.

Results of dynamic stability of aircraft in the tandem wing configuration can be found in the literature, but those studies show outcomes of a single configuration, while this paper presents a comprehensive investigation into the impact of wingspan on aircraft dynamic stability. The results reveal that because of a strong aerodynamic coupling, the relation between the span factor and dynamic stability is nonlinear. Also, it has been demonstrated that the configuration of two wings with the same span is not the optimal one from the aerodynamic point of view.

The purpose of this paper is to investigate the potential integration of deep learning (DL) and digital twins (DT), referred to as (DDT), to facilitate Construction 4.0 through an exploratory analysis.

A mixed approach involving qualitative and quantitative analysis was applied to collect data from global industry experts via interviews, focus groups and a questionnaire survey, with an emphasis on the practicality and interoperability of DDT with decision-support capabilities for process optimization.

Based on the analysis of results, a conceptual model of the framework has been developed. The research findings validate that DL integrated DT model facilitating Construction 4.0 will incorporate cognitive abilities to detect complex and unpredictable actions and reasoning about dynamic process optimization strategies to support decision-making.

The DL integrated DT model will establish an interoperable functionality and develop typologies of models described for autonomous real-time interpretation and decision-making support of complex building systems development based on cognitive capabilities of DT.

The research explores how the technologies work collaboratively to integrate data from different environments in real-time through the interplay of the optimization and simulation during planning and construction. The framework model is a step for the next level of DT involving process automation and control towards Construction 4.0 to be implemented for different phases of the project lifecycle (design–planning–construction).

Industry 4.0 is dramatically affecting businesses behaviours and strategies, transforming products design, manufacture, operations and services. An outcome of this transformation is digital servitization. This paper aims to contribute to the extant literature about digital servitization in B2B contexts by analysing how I4.0-based servitization affects the quality of supplier–customer relationships.

The authors adopted a qualitative methodology based on an exploratory multiple case study. In particular, the study included 22 Italian B2B manufacturing firms whose I4.0-based digital servitization approaches are described and, then, analysed in relation to the quality of supplier–customer relationships.

The access to customers and data is critical to enable advanced digital services and for improving relationship quality; the levels of relational intimacy and informational openness lead to two subsequent levels of data-driven efficiency and data-driven effectiveness, impacting significantly on relationship quality and enabling relational innovation.

The research explores the link, so far underestimated, between digital servitization and relationship quality in industrial contexts.

Given that online search visibility is influenced by various determinants, and that influence may vary across industries, this study aims in investigating the major predictors of online search visibility in the context of blood banks.

To formalize the online visibility, the authors have found theoretical foundations in activity theory, while to quantify online visiblity the authors have used the search engine optimization (SEO) Index, ranking, and a number of visitors. The examined model includes ten hypotheses and was tested on data from 57 blood banks.

Results challenge shallow domain knowledge. The major predictors of online search visibility are Alternative Text Attribute (ALT) text, backlinks, robots, domain authority (DA) and bounce rate (BR). The issues are related to the number of backlinks, social score, and DA. Polarized utilization of SEO techniques is evident.

The methodology can be used to analyze the online search visibility of other industries or similar not-for-profit organizations. Findings in terms of individual predictors can be useful for marketers to better manage online search visibility.

The acute blood donation problems may be to a certain degree level as the information flow between donors and blood banks will be facilitated.

This is the first study to analyze the blood bank context. The results provide invaluable inputs to marketers, managers, and policymakers.

Honeycombs enjoy wide use in various engineering applications. The emergence of additive manufacturing (AM) as a method of customisable of parts has enabled the reinvention of the honeycomb structure. However, research on in-plane compressive performance of both classical and new types of honeycombs fabricated via AM is still ongoing. Several important findings have emerged over the past years, with significance for the AM community and a review is considered necessary and timely. This paper aims to review the in-plane compressive performance of AM honeycomb structures.

This paper provides a state-of-the-art review focussing on the in-plane compressive performance of AM honeycomb structures, covering both polymers and metals. Recently published studies, over the past six years, have been reviewed under the specific theme of in-plane compression properties.

The key factors influencing the AM honeycombs' in-plane compressive performance are identified, namely the geometrical features, such as topology shape, cell wall thickness, cell size and manufacturing parameters. Moreover, the techniques and configurations commonly used for geometry optimisation toward improving mechanical performance are discussed in detail. Current AM limitations applicable to AM honeycomb structures are identified and potential future directions are also discussed in this paper.

This work evaluates critically the primary results and findings from the published research literature associated with the in-plane compressive mechanical performance of AM honeycombs.

Digital transformation affected modern society influencing how businesses cooperate and produce value. In this context, Artificial Intelligence plays a critical role. This study aims to explore the role of Artificial Intelligence in organisational positioning within the market, influencing firms' competitiveness. In this vein, this research seeks to respond to the following research question: How does AI impact the competitive advantage of healthcare organizations?.

To tackle the research question, an explorative analysis using the case study method to investigate an international healthcare center in Dubai was conducted. Nine semi-structured interviews were conducted with the head and the members of the robotic surgery team in CMC Dubai to thoroughly understand what the components of the robotic approach are and how the arrangement before the introduction of this innovative technique while shedding light on the added value and the advantages of adopting such technique on both patient safety and patient satisfaction. Additionally, archival data and online documentation (e.g. industry reports, newspaper articles and internal documents) were analyzed to obtain data triangulation.

The results highlight three primary outcomes influenced by implementing AI in organizational processes: clinical, financial and technological outcomes. The study will offer interesting non-studied insights about the implementation of Artificial Intelligence tools in the healthcare sector and specifically robotic surgeries, and to which extent this will contribute and represent a competitive advantage. Results will hopefully insert a brick in the wall of the impact of AI tools on the quality and the results of surgical operations while emphasizing the benefits of integrating AI in surgical practice.

This study offers interesting theoretical and practical implications. It opens a new perspective to understand and manage AI tools in service. This research is not without limits providing valuable insights for future research.