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This study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model.

In dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts.

The research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management.

This study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management.

This research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.

Mobile robots with independent wheel control face challenges in steering precision, motion stability and robustness across various wheel and steering system types. This paper aims to propose a coordinated torque distribution control approach that compensates for tracking deviations using the longitudinal moment generated by active steering.

Building upon a two-degree-of-freedom robot model, an adaptive robust controller is used to compute the total longitudinal moment, while the robot actuator is regulated based on the difference between autonomous steering and the longitudinal moment. An adaptive robust control scheme is developed to achieve accurate and stable generation of the desired total moment value. Furthermore, quadratic programming is used for torque allocation, optimizing maneuverability and tracking precision by considering the robot’s dynamic model, tire load rate and maximum motor torque output.

Comparative evaluations with autonomous steering Ackermann speed control and the average torque method validate the superior performance of the proposed control strategy, demonstrating improved tracking accuracy and robot stability under diverse driving conditions.

When designing adaptive algorithms, using models with higher degrees of freedom can enhance accuracy. Furthermore, incorporating additional objective functions in moment distribution can be explored to enhance adaptability, particularly in extreme environments.

By combining this method with the path-tracking algorithm, the robot’s structural path-tracking capabilities and ability to navigate a variety of difficult terrains can be optimized and improved.

This research investigates the capabilities of Cloud-based Building Information Modelling (CBIM) in managing quality asset information, drawing upon software engineers' perspectives. Compelling statistics highlight the relationship between building information and environmental sustainability. However, despite the growing utilisation of CBIM in the Architecture, Engineering and Construction (AEC) industry, a significant knowledge gap remains concerning its effectiveness in maintaining quality asset information.

This study employed an exploratory qualitative approach, utilising semi-structured interviews with thirteen software engineers actively developing technological solutions for the AEC industry. Following thematic analysis, the findings are categorised into four dimensions: strengths, weaknesses, opportunities and technological limitations. Subsequently, these findings are analysed in relation to previously identified information quality problems.

This research reveals that while CBIM improves project coordination and information accessibility, its effectiveness is challenged by the need for manual updates, vulnerability to human errors and dependency on network services. Technological limitations, notably the absence of automated updates for as-built drawings and the risk of data loss during file conversions in the design phase, coupled with its reduced capability to validate context-specific information from the user's viewpoint, emphasise the urgent need for managerial strategies to maximise CBIM's capabilities in addressing information quality problems.

This study augments the understanding of CBIM, highlighting the managerial implications of a robust information management process to safeguard information integrity. This approach fosters sustainable practices anchored in reliable information essential for achieving desired outcomes. The findings also have broader managerial implications, especially for sectors that employ CBIM as an instrumental tool.

The purpose of this paper aims to design a robust wind turbine emulator (WTE) based on a three-phase induction motor (3PIM).

The 3PIM is driven by a soft voltage source inverter (VSI) controlled by a specific space vector modulation. By adjusting the appropriate vector sequence selection, the desired VSI output voltage allows a real wind turbine speed emulation in the laboratory, taking into account the wind profile, static and dynamic behaviors and parametric variations for theoretical and then experimental analysis. A Mexican hat profile and a sinusoidal profile are therefore used as the wind speed system input to highlight the electrical, mechanical and electromagnetic system response.

The simulation results, based on relative error data, show that the proposed reactive power control method effectively estimates the flux and the rotor time constant, thus ensuring an accurate trajectory tracking of the wind speed for the wind emulation application.

The proposed architecture achieves its results through the use of mathematical theory and WTE topology combine with an online adaptive estimator and Lyapunov stability adaptation control methods. These approaches are particularly relevant for low-cost or low-power alternative current (AC) motor drives in the field of renewable energy emulation. It has the advantage of eliminating the need for expensive and unreliable position transducers, thereby increasing the emulator drive life. A comparative analysis was also carried out to highlight the online adaptive estimator fast response time and accuracy.

This case study will help students of business management learn the dynamics of strategic decision-making frameworks in a competitive market. After working through the case and assignment questions, the students will be able to understand the 5C framework for strategic decision-making in the context of sports utility vehicles (SUV) segment of Indian automobile industry; identify the opportunities and challenges of the competitive SUV market for long-term survival and growth; and devise a suitable strategic plan incorporating the factors which drive the change in the dynamic automobile industry.

The case study talks about the dilemma faced by Mahindra and Mahindra (M&M), a subsidiary of Mahindra Group. M&M, one of the leading auto manufacturers and pioneers of SUVs in India, has been facing a storm across its business in the past few years. While M&M is making a concerted effort to go back on the road to success, its rivals are not standing idly either. Consumer behaviour towards the purchase of cars is changing at a fast pace, and sales of utility vehicles have surpassed the sales of passenger vehicles in the recent past. M&M, whose work culture is a blend of being friendly and performance-oriented to “Rise”, is prepared to take advantage of any opportunity presented by shifting market trends. Following the 10% increase in SUV registrations in 2023, the business is making many attempts to reclaim the ground it is losing in the Indian market. After dropping from its highest position of 53% in FY 2012 to 15% in FY 2021, M&M’s market share increased to 18% in FY 2023. M&M launched a new logo for its SUV portfolio in August 2021 and launched many SUVs back-to-back, such as Thar, Bolero, XUV700 and Scorpion-N, to face the competition. In 2023, M&M chartered the first position in SUVs by revenue, with a market share of 19.1% and ready for 2024 with six new SUVs. The way M&M performed in 2023 is evidence of its primary objective, which is to offer authentic SUVs to lead the SUV market in revenue share. However, there are still many obstacles in the way. When consumers have so many options from rivals such as Hyundai, KIA Motors and TATA Motors, would it be easy for M&M to bring back its SUVs to the market?

The case study is designed for use in a postgraduate-level course in the subjects – strategic management/marketing management. The case study provides an opportunity to discuss how a company can create a unique selling proposition for its product to sustain its growth in a competitive market, when consumers have so many options from rivals.

Teaching notes are available for educators only.

CSS 11: Strategy

This work examines a repairable machining system’s reliability by considering multiple failure scenarios, including individual component failures, hardware and software malfunctions, failures resulting from shared causes and failures caused by human error. When a system is susceptible to several modes of failure, the primary goal is to forecast availability and other reliability metrics as well as to calculate the expected profit of the repairable machining system.

The process of recovering after a system failure involves inspecting the system and fixing any malfunctions that may have occurred. The repair procedures for all kinds of faults are taken to follow a general distribution to represent real-time circumstances. We develop a non-Markovian stochastic model representing different system states that reveal working, failed, degraded, repair and delayed repair states. Laplace transformation and the supplementary variable technique are used to assess the transient states of the system.

Analytical expressions for system performance indices such as availability, reliability and cost-benefit analysis are derived. The transient probabilities when the system experiences in different states such as failed, degraded and delayed states are computed. The results obtained are validated using Mathematica software by performing a numerical illustration on setting default values of unknown parameters. This ensures the accuracy and reliability indices of the analytical predictions.

By methodically examining the system in its several states, we will be able to spot possible problems and offer efficient fixes for recovery. The system administrators would check to see if a minor or major repair is needed, or if a replacement is occasionally taken into consideration to prevent recurring repairs.

The proposed use of unlatched, reverse swing flappy doors is becoming widespread in the design of residential common corridor smoke control systems. This article explores the conceptual arguments for and against the use of these systems.

This article relies on industry experience, with reference to relevant building design practices, standards and research literature, to categorise arguments. These are collated into four common areas of concern relating to compartmentation, reliability, depressurisation and modelling practices. A final comparison is made between different common corridor smoke control system types for these four areas.

The article highlights several concerns around the use of flappy door systems, including the enforced breaches in stair compartmentation, uncertainties around system reliability, the reliance on door closers as a single point of failure, the impact of day-to-day building use on the system performance and the false confidence that modelling assessments can provide in demonstrating adequacy. The article concludes in suggesting that alternative smoke control options be considered in place of flappy door systems.

Discussion on the use of flappy door smoke control systems has been ongoing within the fire engineering community for several years, but there is limited public literature available on the topic. By collating the common arguments relating to these systems into a single article, a better understanding of their benefits and pitfalls has been provided for consideration by building design and construction professionals.

This study aims to understand how employability capitals’ dynamics foster self-perceived employability (SPE) among students and graduates, which is still being empirically explored. Building upon the Employability Capital Growth Model and the Social Cognitive Career Theory’s career self-management model, we aimed to understand how different capitals associate by testing a serial mediation model connecting career identity (reflecting career identity capital) and SPE through the serial mediation of cultural capital and job interview self-efficacy (ISE) (an element of psychological capital).

We adopted a two-wave design involving 227 Italian University students and graduates. We recruited participants through multi-channel communication. The hypothesised relationships were analysed employing the structural equation modelling approach with the SPSS AMOS statistical package.

The results indicated that career identity, cultural capital, ISE and SPE are meaningfully related. In particular, in line with our expectations, we observed that career identity predicts cultural capital, which is positively associated with ISE which, ultimately, impacts SPE.

Our work adds to existing research by advancing the understanding of employability capitals, explaining how they interact and influence SPE, which is crucial for a sustainable transition into the workforce. At a practical level, our findings call upon, and guide, efforts from various stakeholders in the graduate career ecosystem (i.e. universities and their partners) to offer students and graduates meaningful experiences to form and use their employability capitals.

This paper aims to propose the automatic carrier landing system with the fault-tolerant ability for carrier-based aircraft in the presence of deck motion, external airwake disturbance and actuator fault, which consists of the reference trajectory generation module and flight control module.

The longitudinal and lateral basic controllers are designed based on the optimal preview control (OPC), which can ensure favorable tracking performance and anti-disturbance ability of system. Furthermore, based on the OPC, the robust fault-tolerant preview control scheme is proposed to attenuate the impact of actuator fault on system, which ensures the safe landing of carrier-based aircraft in case of actuator failure.

Both the Lyapunov method and simulations prove that the tracking errors can converge to zero and system states can be asymptotically stable both in normal and fault operations.

The fault-tolerant control strategy is introduced into preview control to deal with actuator fault, which combines feedforward control based on future previewable information and feedback control based on current information to improve the system performance.

This work aims to provide a rapid robust optimization design solution for parallel robots or mechanisms, thereby circumventing inefficiencies and wastage caused by empirical design, as well as numerous physical verifications, which can be employed for creating high-quality prototypes of parallel robots in a variety of applications.

A novel subregional meta-heuristic iteration (SMI) method is proposed for the optimization of parallel robots. Multiple subregional optimization objectives are established and optimization is achieved through the utilisation of an enhanced meta-heuristic optimization algorithm, which roughly employs chaotic mapping in the initialization strategy to augment the diversity of the initial solution. The non-dominated sorting method is utilised for updating strategies, thereby achieving multi-objective optimization.

The actuator error under the same trajectory is visibly reduced after SMI, with a maximum reduction of 6.81% and an average reduction of 1.46%. Meanwhile, the response speed, maximum bearing capacity and stiffness of the mechanism are enhanced by 63.83, 43.98 and 97.51%, respectively. The optimized mechanism is more robust and the optimization process is efficient.

The proposed robustness multi-objective optimization via SMI is more effective in improving the performance and precision of the parallel mechanisms in various applications. Furthermore, it provides a solution for the rapid and high-quality optimization design of parallel robots.