Model-free adaptive iterative learning control of melt pool width in wire arc additive manufacturing

© 2020, Springer-Verlag London Ltd., part of Springer Nature. Wire arc additive manufacturing (WAAM) is a Direct Energy Deposition (DED) technology, which utilize electrical arc as heat source to deposit metal material bead by bead to make up the final component. However, issues like the lack of assurance in accuracy, repeatability and stability hinder the further application in industry. Therefore, a Model Free Adaptive Iterative Learning Control (MFAILC) algorithm was developed to be applied in WAAM process in this study. The dynamic process of WAAM is modelled by adaptive neuro fuzzy inference system (ANFIS). Based on this ANFIS model, simulations are performed to demonstrate the effectiveness of MFAILC algorithm. Furthermore, experiments are conducted to investigate the tracking performance and robustness of the MFAILC controller. This work will help to improve the forming accuracy and automatic level of WAAM

Process control for WAAM using computer vision

This study is mainly about the vision system and control algorithm programming for wire arc additive manufacturing (WAAM). Arc additive manufacturing technology is formed by the principle of heat source cladding produced by welders using molten inert gas shielded welding (MIG), tungsten inert gas shielded welding (TIG) and layered plasma welding power supply (PA). It has high deposition efficiency, short manufacturing cycle, low cost, and easy maintenance. Although WAAM has very good uses in various fields, the inability to control the adding process in real time has led to defects in the weld and reduced quality. Therefore, it is necessary to develop the real-time feedback through computer vision and algorithms for WAAM to ensure that the thickness and the width of each layer during the addition process are the same

The 1st International Conference on Computational Engineering and Intelligent Systems

Computational engineering, artificial intelligence and smart systems constitute a hot multidisciplinary topic contrasting computer science, engineering and applied mathematics that created a variety of fascinating intelligent systems. Computational engineering encloses fundamental engineering and science blended with the advanced knowledge of mathematics, algorithms and computer languages. It is concerned with the modeling and simulation of complex systems and data processing methods. Computing and artificial intelligence lead to smart systems that are advanced machines designed to fulfill certain specifications. This proceedings book is a collection of papers presented at the first International Conference on Computational Engineering and Intelligent Systems (ICCEIS2021), held online in the period December 10-12, 2021. The collection offers a wide scope of engineering topics, including smart grids, intelligent control, artificial intelligence, optimization, microelectronics and telecommunication systems. The contributions included in this book are of high quality, present details concerning the topics in a succinct way, and can be used as excellent reference and support for readers regarding the field of computational engineering, artificial intelligence and smart system

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Contemporary Robotics

This book book is a collection of 18 chapters written by internationally recognized experts and well-known professionals of the field. Chapters contribute to diverse facets of contemporary robotics and autonomous systems. The volume is organized in four thematic parts according to the main subjects, regarding the recent advances in the contemporary robotics. The first thematic topics of the book are devoted to the theoretical issues. This includes development of algorithms for automatic trajectory generation using redudancy resolution scheme, intelligent algorithms for robotic grasping, modelling approach for reactive mode handling of flexible manufacturing and design of an advanced controller for robot manipulators. The second part of the book deals with different aspects of robot calibration and sensing. This includes a geometric and treshold calibration of a multiple robotic line-vision system, robot-based inline 2D/3D quality monitoring using picture-giving and laser triangulation, and a study on prospective polymer composite materials for flexible tactile sensors. The third part addresses issues of mobile robots and multi-agent systems, including SLAM of mobile robots based on fusion of odometry and visual data, configuration of a localization system by a team of mobile robots, development of generic real-time motion controller for differential mobile robots, control of fuel cells of mobile robots, modelling of omni-directional wheeled-based robots, building of hunter- hybrid tracking environment, as well as design of a cooperative control in distributed population-based multi-agent approach. The fourth part presents recent approaches and results in humanoid and bioinspirative robotics. It deals with design of adaptive control of anthropomorphic biped gait, building of dynamic-based simulation for humanoid robot walking, building controller for perceptual motor control dynamics of humans and biomimetic approach to control mechatronic structure using smart materials

The doctoral research abstracts. Vol:11 2017 / Institute of Graduate Studies, UiTM

Foreword: Congratulation to IGS on the continuous effort to publish the 11th issue of the Doctoral Research Abstracts which highlights the research in various disciplines from science and technology, business and administration to social science and humanities. This research abstract issue features the abstracts from 91 PhD doctorates who will receive their scrolls in this 86th UiTM momentous convocation ceremony. This is a special year for the Institute of Graduate Studies where we are celebrating our 20th anniversary. The 20th anniversary is celebrated with pride with an increase in the number of PhD graduates. In this 86th convocation, the number of PhD graduates has increased by 30% compared to the previous convocation. Each research produces an innovation and this year, 91 research innovations have been successfully recognized to have made contributions to the body of knowledge. This is in line with this year UiTM theme that is “Inovasi Melonjak Persaingan Global (Innovation Soars Global Competition)”. Embarking on PhD research may not have been an easy decision for many of you. It often comes at a point in life when the decision to further one’s studies is challenged by the comfort of status quo. I would like it to be known that you have most certainly done UiTM proud by journeying through the scholarly world with its endless challenges and obstacles, and by persevering right till the very end. Again, congratulations to all PhD graduates. As you leave the university as alumni we hope a new relationship will be fostered between you and UiTM to ensure UiTM soars to greater heights. I wish you all the best in your future endeavor. Keep UiTM close to your heart and be our ambassadors wherever you go. / Prof Emeritus Dato’ Dr Hassan Said Vice Chancellor Universiti Teknologi MAR

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

Novel analysis and modelling methodologies applied to pultrusion and other processes

Often a manufacturing process may be a bottleneck or critical to a business. This thesis focuses on the analysis and modelling of such processest, to both better understand them, and to support the enhancement of quality or output capability of the process. The main thrusts of this thesis therefore are: To model inter-process physics, inter-relationships, and complex processes in a manner that enables re-exploitation, re-interpretation and reuse of this knowledge and generic elements e.g. using Object Oriented (00) & Qualitative Modelling (QM) techniques. This involves the development of superior process models to capture process complexity and reuse any generic elements; To demonstrate advanced modelling and simulation techniques (e.g. Artificial Neural Networks(ANN), Rule-Based-Systems (RBS), and statistical modelling) on a number of complex manufacturing case studies; To gain a better understanding of the physics and process inter-relationships exhibited in a number of complex manufacturing processes (e.g. pultrusion, bioprocess, and logistics) using analysis and modelling. To these ends, both a novel Object Oriented Qualitative (Problem) Analysis (OOQA) methodology, and a novel Artificial Neural Network Process Modelling (ANNPM) methodology were developed and applied to a number of complex manufacturing case studies- thermoset and thermoplastic pultrusion, bioprocess reactor, and a logistics supply chain. It has been shown that these methodologies and the models developed support capture of complex process inter-relationships, enable reuse of generic elements, support effective variable selection for ANN models, and perform well as a predictor of process properties. In particular the ANN pultrusion models, using laboratory data from IKV, Aachen and Pera, Melton Mowbray, predicted product properties very well