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Automated production systems involve multiple engineering disciplines and often operate for several decades. Therefore, in order to leverage benefits of model-based system engineering, modeling approaches must handle both multiple disciplines and variability. As a first step towards variability modeling and management, a small case study is carried out to investigate the opportunities and challenges...
The concept of using a Magnetic Resonance Imaging (MRI) device for chemotherapy, by employing a micro robot, consisting of a polymer bound aggregate of ferromagnetic particles, is explored in this paper. We primarily contribute towards the design of a Fuzzy Sliding Mode Controller (FSMC) for trajectory tracking of the micro robot in the human vasculature considering a highly non-linear model available...
Position error between master and slave occurs in bilateral control system under time delay and it is undesirable for delicate works. To solve this problem, this paper proposes a compensation method of position error in bilateral control under time delay. Firstly, the cause of position error is expressed. After that, it is shown that 3-channel bilateral control system, which is the conventional method,...
This paper proposes a framework for formal verification of industrial automation software in an intuitive way. The IEC 61499 function block architecture is assumed to be the input language, and the Intelligent Mechatronic Components (IMC) architecture is assumed as an underlying design pattern for the applications, which implies autonomous control logic in each IMC and their compositions to systems...
Change request management and Model Driven Engineering (MDE) are two key concepts for industrial automation software in today's competitive and fast changing environment. However, although there exist frameworks on general change management, they do not exploit the capabilities of MDE. This paper proposes a workflow to combine these two technologies, enabling the engineer responsible for the change...
This paper presents a distributed secondary control scheme for voltage unbalance compensation in the islanded microgrid (MG) systems. Conventionally, the voltage unbalance compensation is realized in a centralized way, which has certain intrinsic disadvantages such as poor fault tolerance ability and higher computational and communication cost. In order to overcome these drawbacks, a distributed secondary...
The German working committee for “Industrie 4.0” identified the horizontal integration throughout value networks and the vertical integration of networked manufacturing systems as key issues in the context of smart factories. For this purpose we aim for a universal model-driven industrial engineering framework spanning over production chains and value networks. Thereby, we build up on the Resource...
The distance from academic research output to industrial implementation is often daunting, costly, and delays the return on research investment for industrial sponsors. Operational performance monitoring techniques, infrastructure and tools are of pivotal importance to efficient and effective process engineering plants, but new research output typically requires extensive development before deployment...
In this paper a generic degradation model based on Dynamic Bayesian Networks (DBN) which predicts the condition of technical systems is presented. Besides handling bi-directional reasoning, a major benefit of using DBNs is its capability to adequately model stochastic processes. We assume that the behavior of the degradation can be represented as a P-F-curve (also called degradation or life curve)...
Education curricula for children with developmental disabilities have attempted to include information and communication technology (ICT) teaching materials. However, such children demonstrate individual differences at the developmental stage of their cognitive faculties. Thus, it is difficult to adopt commercially available ICT teaching materials when working with them. In this study, we introduce...
Now-a-days with the enormous synthesize and increasing use in the arena of cloud computing, smart devices, and business intelligence, Big Data also has become a growing area of research. Yet in literature existing approaches regarding logical level designing of Big Data is very rare. Most are about representation of both semi-structured and structured data and from the perspective of schema-base....
We propose a reference architecture, SelSus (SELf-SUStaining Manufacturing Systems) that aims to enable the provisioning of diagnostic and prognostic capabilities in manufacturing systems that utilize the notions of “smart” automation devices.
Considering constantly increasing demand for shift from mass production to mass customization and the need to maintain high level of automation despite permanent changes in manufacturing technologies and tools new approaches and solutions have to be provided in manufacturing. Cyber-Physical Systems and Industrial Internet of Things are enabling smart manufacturing to tackle the challenge of data processing,...
This article presents a methodology for intelligent, biologically inspired fault detection system for generic complex systems of systems. The proposed methodology utilizes the concepts of associative memory and vector symbolic architectures, commonly used for modeling cognitive abilities of human brain. Compared to classical methods of artificial intelligence used in the context of fault detection...
The complex interactions between multistage manufacturing processes and different processing technologies is difficult to express with unified mathematical expression. In this paper, the reliability robust design model was studied based on directed topological graph. This model takes the quality characteristic variation loss in the manufacturing process as the objective function, with process sequence...
This paper presents a self-learning strategy for an artificial cognitive control based on a reinforcement learning strategy, in particular, an on-line version of a Q-learning algorithm. One architecture for artificial cognitive control was initially reported in [1], but without an effective self-learning strategy in order to deal with nonlinear and time variant behavior. The anticipation mode (i.e...
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