Given the multiple varieties and small batches, the production of industrial robots faces the ongoing challenges of flexibility, self-organization, self-configuration, and other “smart” requirements. Recently, cyber physical systems have provided a promising solution for the requirements mentioned above. Despite recent progress, some critical issues have not been fully addressed at the shop floor level, including dynamic reorganization and reconfiguration, ubiquitous networking, and time constrained computing. Toward the next generation production system for industrial robots, this study proposed a hybrid architecture for smart assembly shop floors with closed-loop dynamic cyber physical interactions. Aiming for dynamic reorganization and reconfiguration, the study also proposed modularized smart assembly units for the deployment of physical assembly processes. Enabling technologies, such as multiagent system (MAS), self-organized wireless sensor actuator networks, and edge computing, were discussed and then integrated into the proposed architecture. Furthermore, a multijoint robot assembly process was selected as a target scenario. Thus, an MAS was developed to simulate the coordination and negotiation mechanisms for the proposed architecture on the basis of the Java Agent Development Framework platform.
The scheduling of parallel machines and the optimization of multi-line systems are two hotspots in the field of complex manufacturing systems. When the two problems are considered simultaneously, the resulting problem is much more complex than either of them. Obtaining sufficient training data for conventional data-based optimization approaches is difficult because of the high diversity of system structures. Consequently, optimization of multi-line systems with alternative machines requires a simple mechanism and must be minimally dependent on historical data. To define a general multi-line system with alternative machines, this study introduces the capability vector and matrix and the distribution vector and matrix. A naive optimization method is proposed in accordance with classic feedback control theory, and its key approaches are introduced. When a reasonable target value is provided, the proposed method can realize closed-loop optimization to the selected objective performance. Case studies are performed on a real 5/6-inch semiconductor wafer manufacturing facility and a simulated multi-line system constructed on the basis of the MiniFAB model. Results show that the proposed method can effectively and efficiently optimize various objective performance. The method demonstrates a potential for utilization in multi-objective optimization.
Nano-precision positioning stages are characterized by rigid-flexible coupling systems. The complex dynamic characteristics of mechanical structure of a stage, which are determined by structural and dynamic parameters, exert a serious influence on the accuracy of its motion and measurement. Systematic evaluation of such influence is essential for the design and improvement of stages. A systematic approach to modeling the dynamic accuracy of a nano-precision positioning stage is developed in this work by integrating a multi-rigid-body dynamic model of the mechanical system and measurement system models. The influence of structural and dynamic parameters, including aerostatic bearing configurations, motion plane errors, foundation vibrations, and positions of the acting points of driving forces, on dynamic accuracy is investigated by adopting the H-type configured stage as an example. The approach is programmed and integrated into a software framework that supports the dynamic design of nano-precision positioning stages. The software framework is then applied to the design of a nano-precision positioning stage used in a packaging lithography machine.
The advances of manufacturing techniques, such as additive manufacturing, have provided unprecedented opportunities for producing multiscale structures with intricate latticed/cellular material microstructures to meet the increasing demands for parts with customized functionalities. However, there are still difficulties for the state-of-the-art multiscale topology optimization (TO) methods to achieve manufacturable multiscale designs with cellular materials, partially due to the disconnectivity issue when tiling material microstructures. This paper attempts to address the disconnectivity issue by extending component-based TO methodology to multiscale structural design. An effective linkage scheme to guarantee smooth transitions between neighboring material microstructures (unit cells) is devised and investigated. Associated with the advantages of components-based TO, the number of design variables is greatly reduced in multiscale TO design. Homogenization is employed to calculate the effective material properties of the porous materials and to correlate the macro/structural scale with the micro/material scale. Sensitivities of the objective function with respect to the geometrical parameters of each component in each material microstructure have been derived using the adjoint method. Numerical examples demonstrate that multiscale structures with well-connected material microstructures or graded/layered material microstructures are realized.
Biological knowledge is becoming an important source of inspiration for developing creative solutions to engineering design problems and even has a huge potential in formulating ideas that can help firms compete successfully in a dynamic market. To identify the technologies and methods that can facilitate the development of biologically inspired creative designs, this research briefly reviews the existing biological-knowledge-based theories and methods and examines the application of biological-knowledge-inspired designs in various fields. Afterward, this research thoroughly examines the four dimensions of key technologies that underlie the biologically inspired design (BID) process. This research then discusses the future development trends of the BID process before presenting the conclusions.
Damage accumulation and failure behaviors are crucial concerns during the design and service of a critical component, leading researchers and engineers to thoroughly identifying the crack evolution. Third-generation synchrotron radiation X-ray computed microtomography can be used to detect the inner damage evolution of a large-density material or component. This paper provides a brief review of studying the crack initiation and propagation inside lightweight materials with advanced synchrotron three-dimensional (3D) X-ray imaging, such as aluminum materials. Various damage modes under both static and dynamic loading are elucidated for pure aluminum, aluminum alloy matrix, aluminum alloy metal matrix composite, and aluminum alloy welded joint. For aluminum alloy matrix, metallurgical defects (porosity, void, inclusion, precipitate, etc.) or artificial defects (notch, scratch, pit, etc.) strongly affect the crack initiation and propagation. For aluminum alloy metal matrix composites, the fracture occurs either from the particle debonding or voids at the particle/matrix interface, and the void evolution is closely related with fatigued cycles. For the hybrid laser welded aluminum alloy, fatigue cracks usually initiate from gas pores located at the surface or sub-surface and gradually propagate to a quarter ellipse or a typical semi-ellipse profile.
Electromagnetic interference (EMI) causes electromechanical damage to the motors and degrades the reliability of variable-frequency drive (VFD) systems. Unlike fundamental frequency components in motor drive systems, high-frequency EMI noise, coupled with the parasitic parameters of the trough system, are difficult to analyze and reduce. In this article, EMI modeling techniques for different function units in a VFD system, including induction motors, motor bearings, and rectifier-inverters, are reviewed and evaluated in terms of applied frequency range, model parameterization, and model accuracy. The EMI models for the motors are categorized based on modeling techniques and model topologies. Motor bearing and shaft models are also reviewed, and techniques that are used to eliminate bearing current are evaluated. Modeling techniques for conventional rectifier-inverter systems are also summarized. EMI noise suppression techniques, including passive filter, Wheatstone bridge balance, active filter, and optimized modulation, are reviewed and compared based on the VFD system models.