Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus

This is an open access book. It gathers the first volume of the proceedings of the 31st edition of the International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, held on June 19 – 23, 2022, in Detroit, Michigan, USA. Covering four thematic areas including Manufacturing Processes, Machine Tools, Manufacturing Systems, and Enabling Technologies, it reports on advanced manufacturing processes, and innovative materials for 3D printing, applications of machine learning, artificial intelligence and mixed reality in various production sectors, as well as important issues in human-robot collaboration, including methods for improving safety. Contributions also cover strategies to improve quality control, supply chain management and training in the manufacturing industry, and methods supporting circular supply chain and sustainable manufacturing. All in all, this book provides academicians, engineers and professionals with extensive information on both scientific and industrial advances in the converging fields of manufacturing, production, and automation

Engineering Education and Research Using MATLAB

MATLAB is a software package used primarily in the field of engineering for signal processing, numerical data analysis, modeling, programming, simulation, and computer graphic visualization. In the last few years, it has become widely accepted as an efficient tool, and, therefore, its use has significantly increased in scientific communities and academic institutions. This book consists of 20 chapters presenting research works using MATLAB tools. Chapters include techniques for programming and developing Graphical User Interfaces (GUIs), dynamic systems, electric machines, signal and image processing, power electronics, mixed signal circuits, genetic programming, digital watermarking, control systems, time-series regression modeling, and artificial neural networks

Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus

This is an open access book. It gathers the first volume of the proceedings of the 31st edition of the International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, held on June 19 – 23, 2022, in Detroit, Michigan, USA. Covering four thematic areas including Manufacturing Processes, Machine Tools, Manufacturing Systems, and Enabling Technologies, it reports on advanced manufacturing processes, and innovative materials for 3D printing, applications of machine learning, artificial intelligence and mixed reality in various production sectors, as well as important issues in human-robot collaboration, including methods for improving safety. Contributions also cover strategies to improve quality control, supply chain management and training in the manufacturing industry, and methods supporting circular supply chain and sustainable manufacturing. All in all, this book provides academicians, engineers and professionals with extensive information on both scientific and industrial advances in the converging fields of manufacturing, production, and automation

Characterising, understanding and predicting the performance of structural power composites

Dramatic improvements in power generation, energy storage, system integration and light-weighting are needed to meet increasingly stringent carbon emissions targets for future aircraft and road vehicles. The electrification of transport could significantly reduce direct CO2 emissions; however, battery energy and power density limitations pose a major technological barrier. The introduction of multifunctional structural power composites (SPCs), which simultaneously provide mechanical load-bearing and electrochemical energy storage, offers new possibilities. By replacing conventional materials with SPCs, electrical performance requirements could be relaxed, and vehicle mass could be reduced; however, for SPCs to outperform monofunctional systems, significant performance and reliability improvements are still required. The use of computational models to support experimental efforts has so far been overlooked, despite wide recognition of the benefits of such a combined approach. The aim of this work was to develop predictive finite element models for structural supercapacitor composites (SSCs), and use them to investigate their mechanical, electrical, and electrochemical behaviour. A unit cell modelling technique was used to generate realistic mesoscale models of the complex microstructure of SSCs. The effects of composite manufacturing processes on the final performance of SSCs were investigated through characterisation and modelling of compaction and manufacturing defects. Numerical predictions of the elastic properties of SSCs were evaluated against data from the literature; and the presence of defects was shown to significantly degrade performance. Motivated by the large series resistance of SSCs, direct conduction models were developed to better understand electrical charge transport. Based on investigations of various current collector geometries, design strategies for the mitigation of resistive losses were proposed. To enable analysis of the combined mechanical-electrochemical behaviour of SSCs, an ion transport user element subroutine was developed but could not be validated. Overall, this work demonstrates that substantial improvements in the mechanical and electrical properties of SSCs are possible through control of the composite microstructure. The models developed in this work provide guidance for the optimisation of manufacturing processes and the design of new SSC architectures, and underpin the future certification and deployment of these emerging materials.Open Acces

The 1st Advanced Manufacturing Student Conference (AMSC21) Chemnitz, Germany 15–16 July 2021

The Advanced Manufacturing Student Conference (AMSC) represents an educational format designed to foster the acquisition and application of skills related to Research Methods in Engineering Sciences. Participating students are required to write and submit a conference paper and are given the opportunity to present their findings at the conference. The AMSC provides a tremendous opportunity for participants to practice critical skills associated with scientific publication. Conference Proceedings of the conference will benefit readers by providing updates on critical topics and recent progress in the advanced manufacturing engineering and technologies and, at the same time, will aid the transfer of valuable knowledge to the next generation of academics and practitioners. *** The first AMSC Conference Proceeding (AMSC21) addressed the following topics: Advances in “classical” Manufacturing Technologies, Technology and Application of Additive Manufacturing, Digitalization of Industrial Production (Industry 4.0), Advances in the field of Cyber-Physical Systems, Virtual and Augmented Reality Technologies throughout the entire product Life Cycle, Human-machine-environment interaction and Management and life cycle assessment.:- Advances in “classical” Manufacturing Technologies - Technology and Application of Additive Manufacturing - Digitalization of Industrial Production (Industry 4.0) - Advances in the field of Cyber-Physical Systems - Virtual and Augmented Reality Technologies throughout the entire product Life Cycle - Human-machine-environment interaction - Management and life cycle assessmen

Innovation in Energy Systems

It has been a little over a century since the inception of interconnected networks and little has changed in the way that they are operated. Demand-supply balance methods, protection schemes, business models for electric power companies, and future development considerations have remained the same until very recently. Distributed generators, storage devices, and electric vehicles have become widespread and disrupted century-old bulk generation - bulk transmission operation. Distribution networks are no longer passive networks and now contribute to power generation. Old billing and energy trading schemes cannot accommodate this change and need revision. Furthermore, bidirectional power flow is an unprecedented phenomenon in distribution networks and traditional protection schemes require a thorough fix for proper operation. This book aims to cover new technologies, methods, and approaches developed to meet the needs of this changing field

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Using machine learning to predict the ballistic response of structures to projectile impact

Ballistic loading is a primary risk in both civil and military defence applications, where successfully predicting the dynamic response of a material to impact is a fundamental component of the design of safe and fit-for-purpose protective structures. Approaches to understand the response to ballistic impact conventionally revolve around experimental tests, whereby the material or structure of interest is subject to impact by a projectile across a range of impact velocities. However, experimental testing is expensive and incurs large costs due to the destructive nature of the testing and the specialist equipment required. Numerical tools, such as the Finite Element (FE) method, play an important role by filling the gaps left sparse by experimental results and contribute towards the complete dynamic material characterisation campaign. This thesis considers an alternative to FE models by using Machine Learning (ML) techniques that learn directly from the available ballistic data. Specifically, the thesis considers the use of Multi-Layer Perceptron (MLP) models to predict the ballistic response of multi-layered targets to impact but its primary intention is to explore the value that generative networks can bring to the ballistic domain. This thesis shows how Generative Adversarial Networks (GANs) can be used to supplement sparse ballistic datasets by generating new samples representative of the dataset that it was trained on, but also how they can be used to predict key ballistic parameters for engineering design such as the ballistic limit velocity, vbl. And finally, how conditional-GANs (cGANS) can be utilised to allow the network to be conditioned on additional auxiliary information such as class labels that refer to a specific property relevant to the ballistic data thus allowing the cGAN to generate new samples specific to the class label given. This allows the trained cGAN to generate data for classes that are not present in the training set and conduct its own material characteristic campaign. The justification for using ML practices for in the ballistic domain lies in the idea that numerical models are adjusted such that the output is consistent with the results from experimental testing. There is therefore an opportunity for research to explore whether ML techniques can capture that same distribution by training on the ballistic data directly

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022, held in Hamburg, Germany, in May 2022. The 36 regular papers included in this book were carefully reviewed and selected from 129 submissions. They were organized in topical sections as follows: haptic science; haptic technology; and haptic applications

Remanufacturing and Advanced Machining Processes for New Materials and Components

"Remanufacturing and Advanced Machining Processes for Materials and Components presents current and emerging techniques for machining of new materials and restoration of components, as well as surface engineering methods aimed at prolonging the life of industrial systems. It examines contemporary machining processes for new materials, methods of protection and restoration of components, and smart machining processes. • Details a variety of advanced machining processes, new materials joining techniques, and methods to increase machining accuracy • Presents innovative methods for protection and restoration of components primarily from the perspective of remanufacturing and protective surface engineering • Discusses smart machining processes, including computer-integrated manufacturing and rapid prototyping, and smart materials • Provides a comprehensive summary of state-of-the-art in every section and a description of manufacturing methods • Describes the applications in recovery and enhancing purposes and identifies contemporary trends in industrial practice, emphasizing resource savings and performance prolongation for components and engineering systems The book is aimed at a range of readers, including graduate-level students, researchers, and engineers in mechanical, materials, and manufacturing engineering, especially those focused on resource savings, renovation, and failure prevention of components in engineering systems.