Advances in solid-state fiber batteries for wearable bioelectronics

Powering wearable bioelectronics with decent skin conformability and wearing comfort is highly desired. Fiber batteries could provide an attractive alternative to traditional rigid ones and present a compelling solution to this problem. In this review, we will discuss the various classes of fiber batteries, including lithium batteries, zinc batteries, and other types of fiber batteries. We will then report the latest research progress on each battery category through its working mechanism, materials usage, structure design, and wearable applications. Finally, we provide insights into current challenges and future applications of fiber batteries, aiming to promote the development of low-cost and high-performance fiber battery technologies for wearable bioelectronics.     

Smart work packaging-enabled constraint-free path re-planning for tower crane in prefabricated products assembly process

Lack of constraint-free crane path planning is one of the critical concerns in the dynamic on-site assembly process of prefabrication housing production (PHP). For decades, researchers and practitioners have endeavored to improve both the efficiency and safety of crane path planning from either static environment or re-planning the path when colliding with constraints or periodically updating the path in the dynamic environment. However, there is a lack of approach related to the in-depth exploration of the nature of dynamic constraints so as to assist the crane operators in making adaptive path re-planning decisions by categorizing and prioritizing constraints. To address this issue, this study develops the smart work packaging (SWP)-enabled constraints optimization service. This service embraces the core characteristics of SWP, including adaptivity, sociability, and autonomy to achieve autonomous initial path planning, networked constraints classification, and adaptive decisions on path re-planning. This service is simulated and verified in the BIM environment, and it is found that SWP-enabled constraints optimization service can generate the constraint-free path when it is necessary.     

A wavelet-based multi-dimensional temporal recurrent neural network for stencil printing performance prediction

The solder paste printing (SPP) is a critical procedure in a surface mount technology (SMT) based assembly line, which is one of the major attributes to the defect of the printed circuit boards (PCBs). The quality of SPP is influenced by multiple factors, such as the squeegee speed, pressure, the stencil separation speed, cleaning frequency, and cleaning profile. During printing, the printer environment is dynamically varying due to the physical change of solder paste, which can result in a dynamic variation of the relationships between the printing results and the influential factors. To reduce the printing defects, it is critical to understand such dynamic relationships. This research focuses on determining the printing performance during printing by implementing a wavelet filtering-based temporal recurrent neural network. To reduce the noise factor in the solder paste inspection (SPI) data, this research applies a three-dimensional dual-tree complex wavelet transformation for low-pass noise filtering and signal reconstruction. A recurrent neural network is utilized to model the performance prediction with low noise interference. Both printing sequence and process setting information are considered in the proposed recurrent network model. The proposed approach is validated using practical dataset and compared with other commonly used data mining approaches. The results show that the proposed wavelet-based multi-dimensional temporal recurrent neural network can effectively predict the printing process performance and can be a high potential approach in reducing the defects and controlling cleaning frequency. The proposed model is expected to advance the current research in the application of smart manufacturing in surface mount technology.     

Development and operation of Digital Twins for technical systems and services

Digital Twins are new solution elements to enable ongoing digital monitoring and active functional improvement of interconnected products, devices and machines. In addition, benefits of horizontal and vertical integration in manufacturing are targeted by the introduction of Digital Twins. Using the test environment of smart factory cells, this paper investigates methodological, technological, operative, and business aspects of developing and operating Digital Twins. The following Digital Twin dimensions are considered in scientific and application oriented analysis: (1) integration breadth, (2) connectivity modes, (3) update frequency, (4) CPS intelligence, (5) simulation capabilities, (6) digital model richness, (7) human interaction, and (8) product lifecycle. From this, design elements for the development of Digital Twins are derived and presented.     

Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0

Abstract

Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.     

Design of regional flexibility markets for electricity: A product classification framework for and application to German pilot projects

With the growing role of distributed energy resources, the electricity network is challenged by numerous technical problems, such as capacity congestion and over- or under-voltage. An often-discussed response, especially in the European zonal electricity system, is to implement regional flexibility markets. We contribute to this discussion by providing a comprehensive classification framework for the design of flexibility products by combining technical requirements with classical auction theory. The framework structures 23 product parameters in four stages of abstraction. By applying the framework to five market approaches used in current German research projects, we demonstrate its usefulness for consistent comparison of flexibility products at a high level of detail. This framework can empower national and international policymakers and practitioners in assessing flexibility markets holistically, thereby facilitating the implementation of sound solutions.     

Team O2AS at the world robot summit 2018: an approach to robotic kitting and assembly tasks using general purpose grippers and tools

ABSTRACT

In this article, we propose a versatile robotic system for kitting and assembly tasks which uses no jigs or commercial tool changers. Instead of specialized end effectors, it uses its two-finger grippers to grasp and hold tools to perform subtasks such as screwing and suctioning. A third gripper is used as a precision picking and centering tool, and uses in-built passive compliance to compensate for small position errors and uncertainty. A novel grasp point detection for bin picking is described for the kitting task, using a single depth map. Using the proposed system we competed in the Assembly Challenge of the Industrial Robotics Category of the World Robot Challenge at the World Robot Summit 2018, obtaining 4th place and the SICE award for lean design and versatile tool use. We show the effectiveness of our approach through experiments performed during the competition.     

Exploratory factor analysis and validity of the virtual reality symptom questionnaire and computer use survey

Abstract

The widespread use of virtual reality head-mounted-displays (HMDs) calls for a re-examination of the impact of prolonged exposure to fixed visual displays at close ocular proximity. The purpose of this study is to validate the Virtual Reality Symptoms Questionnaire (VRSQ), created to understand symptoms of prolonged HMDs use, and Computer Use Survey (CUS), created to assess general physical and visual discomfort symptoms. Participants (N?=?100) recorded their general discomfort symptoms using the CUS, performed an interactive task using a HMD for thirty minutes, and then answered the CUS again along with the VRSQ. VRSQ, analysed using an exploratory factor analysis, indicated a clear two-factor solution, and demonstrated very good internal consistency (α?=?0.873). The CUS, also analysed using an exploratory factor analysis, indicated a four-factor solution, and demonstrated good internal consistency (α?=?0.838).

Practitioner Summary: A quantitative-experimental study was conducted to explore the factor structure and validate both the Virtual Reality Symptoms Questionnaire (VRSQ), and the Computer Use Survey (CUS). Findings indicate the VRSQ and CUS are precise and accurate survey instruments for evaluating discomfort after VR-HMD use and the latter for computer use.

Abbreviations: VRSQ: virtual reality symptom questionnaire; CUS: computer use survey; OLED: organic light-emitting diode; MSQ: pensacola motion symptom questionnaire; SSQ: simulator sickness questionnaire; 3?D: three-dimensional computer generated space; VR: virtual reality; VR-HMD: virtual reality head-mounted-display; HMDs: head-mounted-displays; EFA: exploratory factor analysis     

Potential pitfalls of smart city development: A study on parking mobile applications (apps) in Hong Kong

Smart cities are built upon information and communication technologies (ICTs) to enable a broad range of advanced services. Through a comprehensive literature review, this study identified four pitfalls brought by the pervasive application of ICT, including information insecurity, privacy leakage, information islands, and digital divide. Therefore, a questionnaire survey together with 27 interviews was conducted in Hong Kong to investigate how the public perceived these pitfalls within the context of mobile apps providing real-time parking information which form a major part of smart mobility. System insecurity and privacy leakage were found to arouse worries among the app-users while their awareness of protecting personal data was found to have room for improvement. Islands of real-time parking information occur as a result of the lack of collaboration among private carpark operators. Digital divide existed widely among the disadvantaged groups and the problem cannot be solved by mere provision of ICT facilities. Overall, technologies alone cannot make a city smart or smarter. It is the suitable way in which ICTs are used to serve all citizens that matters.