Yonghua Chen

Bio: Yonghua Chen is an academic researcher from University of Hong Kong. The author has contributed to research in topics: Haptic technology & Soft robotics. The author has an hindex of 27, co-authored 158 publications receiving 2577 citations.

Robot machining: recent development and future research issues

Abstract: Early studies on robot machining were reported in the 1990s. Even though there are continuous worldwide researches on robot machining ever since, the potential of robot applications in machining has yet to be realized. In this paper, the authors will first look into recent development of robot machining. Such development can be roughly categorized into researches on robot machining system development, robot machining path planning, vibration/chatter analysis including path tracking and compensation, dynamic, or stiffness modeling. These researches will obviously improve the accuracy and efficiency of robot machining and provide useful references for developing robot machining systems for tasks once thought to only be capable by CNC machines. In order to advance the technology of robot machining to the next level so that more practical and competitive systems could be developed, the authors suggest that future researches on robot machining should also focus on robot machining efficiency analysis, stiffness map-based path planning, robotic arm link optimization, planning, and scheduling for a line of machining robots.

3D printing of shape memory polymer for functional part fabrication

Abstract: This article presents a novel method of shape memory polymer (SMP) processing for additive manufacturing, in particular, fused-deposition modeling (FDM). Critical extrusion process parameters have been experimented to determine an appropriate set of parameter values so that good-quality SMP filament could be made for FDM. In the FDM process, effects of different printing parameters such as extruder temperature and scanning speed on object printing quality are also studied. In all the process studies, we aim to achieve good-quality parts by evaluating part density, tensile strength, dimensional accuracy, and surface roughness. Based on these studies, sample SMP models have been successfully built. Due to the thermal sensitive nature of the printed SMP parts, they can potentially be used as fasteners in active assembly/disassembly, smart actuators, deployable structures for aero-space applications, etc.

Passive Particle Jamming and Its Stiffening of Soft Robotic Grippers

Abstract: The compliance of soft grippers contributes to their great superiority over rigid grippers in grasping irregularly shaped objects and forming soft contact with environments. Due to a relatively small pressure, soft grippers lack the stiffness required for wider applications. Particle jamming has been frequently reported as a means of stiffness control. Unlike previous research using vacuum for particle jamming, this paper proposes a novel passive particle jamming principle that does not need any vacuum power or other control means. The proposed method is by simply patching a silicone rubber soft actuator and a pack (made of strain-limiting membrane) of particles to form an integral gripping finger. The inflation of the soft actuator applies a pressure to the particle pack causing particles inside it to jam. A larger squeezing pressure will result in tighter particle jamming, thus increasing the stiffness of the finger. The stiffness of the finger is controllable as it is proportional to the actuator's air pressure, which has been verified by experiments in this research. The stiffness can increase more than six fold when air pressure changes from 20 to 80 kPa in the experimental studies. The reported discovery may enhance the capabilities of soft robotic grippers so that more robotic picking operations could be performed by soft grippers.

Bioinspired Robotic Fingers Based on Pneumatic Actuator and 3D Printing of Smart Material

Abstract: In this article, we have proposed a novel robotic finger design principle aimed to address two challenges in soft pneumatic grippers-the controllability of the stiffness and the controllability of the bending position. The proposed finger design is composed of a 3D printed multimaterial substrate and a soft pneumatic actuator. The substrate has four polylactic acid (PLA) segments interlocked with three shape memory polymer (SMP) joints, inspired by bones and joints in human fingers. By controlling the thermal energy of an SMP joint, the stiffness of the joints is modulated due to the dramatic change in SMP elastic modulus around its glass transition temperature (Tg). When SMP joints are heated above Tg, they exhibit very small stiffness, allowing the finger to easily bend around the SMP joints if the attached soft actuator is actuated. When there is no force from the soft actuator, shape recovery stress in SMP contributes to the finger's shape restoration. Since each joint's rotation can be individually controlled, the position control of the finger is made possible. Experimental analysis has been conducted to show the finger's variable stiffness and the result is compared with the analytical values. It is found that the stiffness ratio can be 24.9 times for a joint at room temperature (20°C) and at an elevated temperature of 60°C when air pressure p of the soft actuator is turned off. Finally, a gripper composed of two fingers is fabricated for demonstration.

Design for additive manufacturing: trends, opportunities, considerations, and constraints

Abstract: The past few decades have seen substantial growth in Additive Manufacturing (AM) technologies. However, this growth has mainly been process-driven. The evolution of engineering design to take advantage of the possibilities afforded by AM and to manage the constraints associated with the technology has lagged behind. This paper presents the major opportunities, constraints, and economic considerations for Design for Additive Manufacturing. It explores issues related to design and redesign for direct and indirect AM production. It also highlights key industrial applications, outlines future challenges, and identifies promising directions for research and the exploitation of AM's full potential in industry.

Soft Robotic Grippers.

Abstract: Advances in soft robotics, materials science, and stretchable electronics have enabled rapid progress in soft grippers. Here, a critical overview of soft robotic grippers is presented, covering different material sets, physical principles, and device architectures. Soft gripping can be categorized into three technologies, enabling grasping by: a) actuation, b) controlled stiffness, and c) controlled adhesion. A comprehensive review of each type is presented. Compared to rigid grippers, end-effectors fabricated from flexible and soft components can often grasp or manipulate a larger variety of objects. Such grippers are an example of morphological computation, where control complexity is greatly reduced by material softness and mechanical compliance. Advanced materials and soft components, in particular silicone elastomers, shape memory materials, and active polymers and gels, are increasingly investigated for the design of lighter, simpler, and more universal grippers, using the inherent functionality of the materials. Embedding stretchable distributed sensors in or on soft grippers greatly enhances the ways in which the grippers interact with objects. Challenges for soft grippers include miniaturization, robustness, speed, integration of sensing, and control. Improved materials, processing methods, and sensing play an important role in future research.

Product platform design and customization: Status and promise

Abstract: In an effort to improve customization for today's highly competitive global marketplace, many companies are utilizing product families and platform-based product development to increase variety, shorten lead times, and reduce costs The key to a successful product family is the product platform from which it is derived either by adding, removing, or substituting one or more modules to the platform or by scaling the platform in one or more dimensions to target specific market niches This nascent field of engineering design has matured rapidly in the past decade, and this paper provides a comprehensive review of the flurry of research activity that has occurred during that time to facilitate product family design and platform-based product development for mass customization Techniques for identifying platform leveraging strategies within a product family are reviewed along with metrics for assessing the effectiveness of product platforms and product families Special emphasis is placed on optimization approaches and artificial intelligence techniques to assist in the process of product family design and platform-based product development Web-based systems for product platform customization are also discussed Examples from both industry and academia are presented throughout the paper to highlight the benefits of product families and product platforms The paper concludes with a discussion of potential areas of research to help bridge the gap between planning and managing families of products and designing and manufacturing them

Design for Additive Manufacturing

Abstract: Design for manufacture and assembly (DFM) has typically meant that designers should tailor their designs to eliminate manufacturing difficulties and minimize manufacturing, assembly, and logistics costs. However, the capabilities of additive manufacturing technologies provide an opportunity to rethink DFM to take advantage of the unique capabilities of these technologies. As mentioned in Chap. 16, several companies are now using AM technologies for production manufacturing. For example, Siemens, Phonak, Widex, and the other hearing aid manufacturers use selective laser sintering and stereolithography machines to produce hearing aid shells; Align Technology uses stereolithography to fabricate molds for producing clear dental braces (“aligners”); and Boeing and its suppliers use polymer powder bed fusion (PBF) to produce ducts and similar parts for F-17 fighter jets. For hearing aids and dental aligners, AM machines enable manufacturing of tens to hundreds of thousands of parts, where each part is uniquely customized based upon person-specific geometric data. In the case of aircraft components, AM technology enables low-volume manufacturing, easy integration of design changes and, at least as importantly, piece part reductions to greatly simplify product assembly.