SUMMARY: The optimum selection of a structure for a given application is a capital phase in typological synthesis of parallel robots. To help in this selection, this paper presents a performance evaluation of four translational parallel robots: Delta, 3-UPU, Romdhane-Affi-Fayet, and Tri-pyramid (TP). The problem is set as a multiobjective optimization using genetic algorithm methods, which uses kinematic criteria, that is, global dexterity and compactness, to ensure a prescribed workspace. The results are presented as Pareto fronts, which are used to compare the performances of the aforementioned structures. The obtained results show that the TP robot has the best kinematic performance, whereas the 3-UPU robot is the most compact for a given prescribed workspace.

The goal of the paper is the integration of safety analysis in a model-based systems engineering approach to ensure consistency between system design and safety artifacts. This integration permits the continuous improvement of the structure and behavior of the system. It also reduces system development time and prevents late detection of errors. To reach this purpose, the SafeSysE methodology is extended. In SafeSysE, a preliminary Failure Mode and Effects Analysis (FMEA) is automatically generated from a SysML model, and this FMEA is then completed by the safety expert but no further development was proposed. The contribution of this paper is to suggest recommendations based on the FMEA analysis in order to enhance the system design and make it comply with safety requirements. First, an updated system structure that may contain redundancy is proposed. Then, a redundancy profile is used to enrich the system model with redundancy information, which will allow the generation of a dynamic fault tree considering the system behavior. Finally, the generated dynamic fault tree should be analyzed in order to create a state machine diagram that describes the behavior of the system. The created state machine with an internal block diagram will help the system designers to better understand the system dysfunctions by simulating the system. The proposed methodology is applied to an Electro-Mechanical Actuator system which is used in the aeronautics domain.

The development of a mechatronic system involves different designers having various viewpoints on the overall system to handle its complexity. Consequently, multiple models are created from a variety of domains such as mechanical, electronic, and software engineering. These models use different formalisms, modeling languages, and tools to address specific concerns. The major challenge of this approach is to identify and solve any potential inconsistency between models in order to minimize costs and development time before the verification and validation phases. This paper proposes a new collaborative methodology to maintain consistency between different engineering disciplines at an early stage of the development cycle of mechatronic systems based on Model-Based Engineering (MBE). We apply a model synchronization approach to actively check for model consistency in a continuous way during the multidisciplinary design process. As a novel contribution of this paper, we demonstrate how model transformation techniques can be employed; firstly, to abstract various engineering models in a common formalism based on graph theory and, secondly, to update models with appropriate changes evaluated by a project manager. We also show how to detect the differences automatically, and we discuss where designer decisions are essential.

Systems are getting increasingly complex and challenging to design. For safety-critical systems, the integration between model-based systems engineering and model-based safety assessment to improve the choice of the system architecture since the early design stage becomes a necessity. One of the integration solutions is to generate fault trees (FTs), either static or dynamic, directly from the system description. In this paper, we are particularly interested in the generation of the dynamic fault trees (DFTs) of the systems that contain redundancies, which is widely used in safety-critical systems to enhance their reliability. The goal of this paper is, first, to propose a redundancy profile and, second, to automatically generate the DFTs from system models. Since errors are propagated via input and output ports of the components, the generation process starts with a depth-first search graph traversal through the systems modeling language internal block diagram of the system. This diagram is considered as a multidirected graph in order to detect the external inputs, the nonredundant components, the switch components, and the redundant components of the system. Then, the redundancy information incorporated in the system model is used to generate the appropriate combinations of the FT. This FT is represented in a suitable format that can be studied using FT analysis tools, for both qualitative and quantitative safety analyses.

This paper deals with the optimal design of a planar cable-driven parallel robot (CDPR), with three degrees of freedom, intended for assisting the patient’s affected upper limb along a prescribed movement. A Qualisys motion capture system was used to record the prescribed task performed by a healthy subject. For each pose taken by the center of mass of the end-effector, the cable tensions, the elastic stiffness and the dexterity were optimized while satisfying a set of constraints. First, a multiobjective formulation of the optimization problem was adopted. Since selecting a single solution among the multiple ones given by the Pareto front presents an issue, a mono-objective formulation was chosen, where the objective function was defined as a weighted sum of the chosen criteria. The appropriate values of the weighted coefficients were studied with the aim of identifying their influence on the optimization process and, thus, a judicious choice was made. A prototype of the optimal design of the CDPR was developed and validated experimentally on the prescribed workspace using the position control approach for the motors. The tests showed promising reliability of the proposed design for the task.

This paper deals with the design of an optimal cable-driven parallel robot (CDPR) for upper limb rehabilitation. The robot’s prescribed workspace is identified with the help of an occupational therapist based on three selected daily life activities, which are tracked using a Qualisys motion capture system. A preliminary architecture of the robot is proposed based on the analysis of the tracked trajectories of all the activities. A multi-objective optimization process using the genetic algorithm method is then performed, where the cable tensions and the robot size are selected as the objective functions to be minimized. The cables tensions are bounded between two limits, where the lower limit ensures a positive tension in the cables at all times and the upper limit represents the maximum torque of the motor. A sensitivity analysis is then performed using the Monte Carlo method to yield the optimal design selected out of the non-dominated solutions, forming the obtained Pareto front. The robot with the highest robustness toward the disturbances is identified, and its dexterity and elastic stiffness are calculated to investigate its performance.