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The purpose of this paper seeks to provide a hybrid framework of sustainable supply chain fuzzy rotation matrix regarding the challenges in today’s business environment and the goals pursued by sustainable supply chain, to prioritize effective infrastructure to manage the challenges in ceramic tile industry in Yazd.

The research offers a hybrid framework of analytical hierarchy process (AHP) and quality function deployment (QFD) model to determine, which one of the goals of a sustainable supply chain can have a greater share in the management of business challenges.

The results indicated government regulations that encourage the implementation of sustainable supply chain and management of the consumption of non-renewable resources are among the most important infrastructures that can be effective to manage the challenges of today’s business.

Given the importance of managing the challenges in today’s business environment and sustainable supply chain management capabilities to enable managers to deal with these challenges, the present research makes effort to offer a hybrid framework of AHP and QFD model, to determine, which one of the goals of a sustainable supply chain can have a greater share in the management of business challenges.

By reviewing the existing research studies in the sustainable supply chain area, it can be found that despite of vast studies, there is no focus on establishing a comprehensive interaction between business challenges management and the fulfillment of sustainable supply chain management goals. So according to this research gap, a new framework was presented in this study to enable tile and ceramic industry managers, to focus on mentioned interaction and manage the businesses challenges in the desired way to achieve sustainable supply chain goals.

The circular economy concepts are useful for resource conservation, eliminating waste and enhancing the efficiency of production to improve the sustainability of the system. The application of CE in Indian manufacturing industry is in nascent stage. India’s manufacturing sector significantly contributes to the economic development of the nation; therefore, this study aims to identify and analyze the sustainability related challenges faced during the implementation of the circularity concept.

Comprehensive survey of literature and the use of Pareto analysis yield ten significant challenges which are further analyzed using fuzzy-Decision-Making Trial and Evaluation Laboratory approach.

Findings revealed that noncompliance of environmental laws, revenue generation, design issues owing to technological limitations and less preference to refurbished and reused product are some of the major challenges to the CE practices in the manufacturing industry.

The results will help the researchers and practitioners in strategic decision-making for the improved application of circularity in the production process.

This paper contributes to the identification and prioritization of sustainability-related challenges faced during the implementation of a novel concept by a developing economy.

This paper aims to critically analyze the engineering education focused on sustainability in supply chain management, in courses offered by Brazilian higher education institutions.

Topics related to sustainable supply chain management were listed from the literature and used as a framework to gather professors’ opinions on how well these topics are covered in engineering courses offered in Brazil. Data analysis was performed via frequency analysis and comparative ordering using the Fuzzy technique for order preference by similarity to ideal solution technique.

It was possible to evidence that most of the topics are superficially presented within other subjects and that there are few associated practical activities that enable greater learning. Comparatively, issues related to ISO standards (related to quality and environmental management systems) and compliance with environmental laws, regulations and standards were highlighted. Additionally, it was possible to verify that there is a need for further study on issues related to energy efficiency, worker training and corporate governance.

No similar study was found in the literature. The findings presented in this paper can contribute to the improvement of engineering education in Brazil and other countries.

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.

The purpose of this paper is to focus on perfect trajectory tracking control of 2 DOF non‐holonomic mobile robots in which the guidance and control commands are imposed through independent driver wheels. Model‐based nonlinear controllers for these robots with unknown parameters require estimation of a specified set of the robot parameters. The effects of the proposed model dynamics in both local and global coordinate systems are fully examined on the parameter estimation and tracking performance.

Design of suitable feedback linearization (FL) controllers for trajectory tracking control of wheeled mobile robots (WMRs) is first reviewed. A FL controller whose parameters are tuned using fuzzy computations (fuzzy if‐then rules) is then developed. In the line of the other contributions of the paper, a pure fuzzy controller that is merely based on fuzzy if‐then rules is proposed to trajectory tracking control of the mobile robots.

Use of global dynamics for designing a suitable FL control system leads to a perfect compensation for initial off‐tracks. Furthermore, the estimated parameters are unbiased because the corresponding regressor/signal matrix indicates a high rank of persistent excitation. Fuzzy tuning of the controller instead of keeping the gains fixed makes the overall system more robust against measurement noises while upper bounds and fluctuations of the input torques are both remarkably reduced. The pure fuzzy controller is naturally independent of the robot dynamics and therefore, the necessity of parameter estimation algorithm is removed.

The paper provides some new nonlinear controllers for WMRs, in order to make perfect trajectory tracking and initial off‐tracks compensation.

The purpose of this paper is to develop a theoretical design for the alternative attitude control of the rotation about the pitch axis for the nadir-pointing spacecraft in the event of inertial actuator faults.

This paper presents a novel and viable solution to that problem using the combined attitude and sun tracking system (CASTS) that was conceived from an engineering problem-solving toolkit called TRIZ. Linear and fuzzy controllers are used to test the spacecraft CASTS architecture. All the relevant governing equations of the control system and disturbance rejection methods are developed.

The performance of the proposed CASTS control strategy is tested through numerical simulations. The results strongly suggest that the novel proposed control scheme is effective and promising for controlling the satellite attitude and sun tracking simultaneously in the presence of disturbance torques.

This work is mainly focused on the rigid body of the spacecraft hub that contains all attitude control hardware and payload instrumentation, and does not deal with the vibrations evolving from the propellant sloshing and large flexible appendages such as the deployable solar panels and synthetic aperture radar antennas.

The results from this work reveal several practical applications worthy of reducing the weight, size of the spacecraft and, therefore, cost of missions while increasing the instrumentation capabilities.

The proposed CASTS solution is a result of looking much wider than one system from a new combination of attitude control and sun tracking, as well as innovative ways of using it.

The purpose of this paper is to consider the process of design and implementation of an enhanced fuzzy H_∞ (EFH_∞) estimation algorithm to determine the attitude and heading angles of ground vehicles, which are frequently affected by considerable exogenous disturbances. To detect the changes of disturbances, a fuzzy system is designed based on expert knowledge and experiences of a navigation engineer. In the EFH_∞ estimator, the intensity bounds of disturbances affecting the measurements are updated using a heuristic combination of three change‐detection indices. Performance of the proposed estimator is evaluated by Monte‐Carlo simulations and field tests of three kinds of vehicles using a manufactured attitude‐heading reference system (AHRS). In both simulations and real tests, the proposed estimator results in a superior performance compared to those of the recently developed and standard H_∞ estimators.

Design, implementation and real tests of the EFH_∞ estimator are considered for an AHRS specialized for vehicular applications. In the AHRS, three‐axis accelerometers (TAA) and three‐axis magnetometers (TAM) may be affected by large disturbances due to non‐gravitational accelerations and local magnetic fields. Therefore, the design parameters of EFH_∞ estimator including the theoretic bound of disturbance intensity and the attenuation level are adaptively tuned using a fuzzy combination of three change‐detection indices. Once a sensor is affected by an exogenous disturbance, the fuzzy system will increase the scale factor of the corresponding measurement disturbance to place more confidence on the data of the AHRS dynamics including measurements of gyros with respect to the data coming from the TAA and TAM.

An intelligent fault detector is proposed for considering changes of disturbances to adjust the upper bounds of the estimator's disturbances and the length of data to update the fuzzy system inputs. The EFH_∞ estimator is suitable to attenuate the effects of disturbances changes on accurate estimation of the attitude and heading angles, intelligently.

The paper provides a fuzzy state estimator for adaptively adjusting the theoretic disturbance matrices according to the actual intensity of the disturbances affecting the AHRS dynamics and the measurement sensors.

The purpose of this paper is to develop an analytical approach to evaluate the influence of material uncertainties on cross‐sectional stiffness properties of thin walled composite beams.

Fuzzy arithmetic operators are used to modify the thin‐walled beam formulation, which was based on a mixed force and displacement method, and to obtain the uncertainty properties of the beam. The resulting model includes material uncertainties along with the effects of elastic couplings, shell wall thickness, torsion warping and constrained warping. The membership functions of material properties are introduced to model the uncertainties of material properties of composites and are determined based on the stochastic behaviors obtained from experimental studies.

It is observed from the numerical studies that the fuzzy membership function approach results in reliable representation of uncertainty quantification of thin walled composite beams. The propagation of uncertainties is also demonstrated in the estimation of structural responses of composite beams.

This work demonstrates the use of fuzzy approach to incorporate uncertainties in the responses analytically, in turn improving computational efficiency drastically as compared to the Monte‐Carlo method.

Several variables can affect work stress. This study aims to model the cause-and-effect relationships among different variables that can predict work stress based on one of the most important fuzzy multicriteria decision-making methods used to investigate the cause-and-effect relationships among variables.

This study was conducted in 2020, including 17 experts in safety management, occupational health and work psychology, based on the fuzzy decision-making trial and evaluation laboratory method as a robust approach to identify the cause-and-effect relationships among different variables.

Shift work, lack of job satisfaction, mental health, mental overload, fatigue, job security, sleep disorders, environmental discomfort, work pressure, job knowledge (this could mean expertise/level of qualifications/familiarity with the job), work complexity and role conflict were found to be the most significant variables affecting work stress. Moreover, the cause-and-effect model of relationships among variables showed that shift work and lack of job satisfaction are root causes, and mental health, fatigue, mental workload, sleep disorder and environmental discomfort are direct causes.

Although the results of this study demonstrate that work stress can be influenced by 12 different variables, the modeling results show that some variables, such as shift work and lack of job satisfaction, can directly or indirectly impact other variables and thus result in work stress.

This chapter presents a novel human arm gesture tracking and recognition technique based on fuzzy logic and nonlinear Kalman filtering with applications in crane guidance. A Kinect visual sensor and a Myo armband sensor are jointly utilised to perform data fusion to provide more accurate and reliable information on Euler angles, angular velocity, linear acceleration and electromyography data in real time. Dynamic equations for arm gesture movement are formulated with Newton–Euler equations based on Denavit–Hartenberg parameters. Nonlinear Kalman filtering techniques, including the extended Kalman filter and the unscented Kalman filter, are applied in order to perform reliable sensor fusion, and their tracking accuracies are compared. A Sugeno-type fuzzy inference system is proposed for arm gesture recognition. Hardware experiments have shown the efficacy of the proposed method for crane guidance applications.