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Purpose The purpose of this study is to determine the optimal shape of a one-sided elliptical composite material patch of an adhesively bonded repair of cracked metal plates under biaxial stress. Design/methodology/approach The approach consists on determining the patch topology and adhesive thickness that minimize the stress intensity factor and the bending moment caused by the asymmetry of the repair by applying a differential evolution algorithm with a selection phase using the Deb’s rules. Findings The results demonstrate that an elliptical patch of major axis length equal to the plate width, and minor axis length equal to the crack length, with a thin adhesive thickness, provides the highest stress intensity factor and bending moment reduction, maximizing the fatigue life of the repair. Research limitations/implications The results are limited to linear elastic behavior of the cracked plate and a fully rigid bond between the cracked plate and the patch. The effectiveness of the repair was verified by theoretical calculation of the fatigue life, thus experimental validation is still needed. Practical implications The results of this work can be applied to experimental validations of the effectiveness of the elliptical one-side composite bonded repairs, avoiding and extensive number of experiments, and also, encourage maintainers to explore on this technique that is more economical and easier to apply, in comparison to other repair techniques. By following the patch geometry recommendations proposed herein, it is analytically predicted that the fatigue life may increase by as much as 27 times that of the unpatched plate. Originality/value Currently, there are no detailed studies that assess one-side patch repair procedures, which require consideration of the bending moment and biaxial stress state, and therefore, the optimal patch geometry and adhesive thickness are unknown.

Finding the inverse kinematic solution of a serial manipulator has always attracted the attention of optimization enthusiasts, as the solution space is highly nonlinear and, depending on the number of degrees of freedom, has multiple solutions. In the literature, one can find several proposed solutions using heuristic techniques; however, for highly redundant manipulators, e.g., seven or more, the discussions focused on minimizing the positional error. In this paper, a metaheuristic approach is presented to solve not only the inverse kinematics of a 7 and 8 DOF manipulators but the proposed algorithm is used to find the robot's poses for trajectory planning where the robot is required to meet the desired position and orientation based on quaternion representation of each point along the path. The metaheuristic approach used in this paper is particle swarm optimization (PSO), where the unit quaternion is used in the objective function to find the orientation error. The results prove that the use of the unit quaternion representation improved the performance of the algorithm and that our approach can be used not only for individual poses but for trajectory planning.

This paper presents the development of a wrist rehabilitation system with a novel approach for structural design, based on the modeling of an optimization problem solved by a metaheuristic algorithm, Improved Harmony Search (ImHS). It is part of a project for developing low-cost rehabilitation systems expressly designed for the population of Latin American countries. A mixed optimization problem is modeled for the design, where the material type is associated with an integer variable and the dimensions of the components are continuous parameters. The novelty is that each element is calculated individually, but considering the combined effect over the structure. The optimization works simultaneously on both the material selection and the meeting of the associated constraints, to guarantee that the system will not fail because of any load, neither it will be unsafe for the patients, since the operation will always be within the limits considered in the modeling. ImHS is a variant of the Harmony Search algorithm, modified to enhance the exploration and exploitation processes. It is a simple yet powerful metaheuristic, implemented in this development with additional modifications to handle constraints and mixed variables. The proposed approach produced quality results, indicating that ImHS can be applied to solve complex engineering problems, facilitating the manufacture and control processes.