Increasing Reliability of Intelligent Manufacturing Systems by Adaptive Optimization and Safety Supervision

Ding, Hu; Kain, Sebastian; Schiller, Frank; Stursberg, Olaf

doi:10.3182/20090630-4-es-2003.00250

Cited by 7 publications

(4 citation statements)

References 6 publications

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“…Further researches and evaluations are yet to be carried out but obviously they will be a key part of future manufacturing systems [15]. Industrial Revolution will happen nowadays [17,18]. This means comprehensive transformation and developing of the manufacturing systems, due to the application of new advanced technologies.…”

Section: E Micro-and Nano-electronicsmentioning

confidence: 99%

Future role of application of new technologies in small-and medium scale manufacturing systems: Regarding Intelligent and advanced manufacturing systems in northern peripheral area

Somlo¹,

Sziebig

2017

2017 IEEE 26th International Symposium on Industrial Electronics (ISIE)

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Abstract-Nowadays the concept of Industry 4.0. and the relating intelligent manufacturing system are getting more and more current and well-known. In the past years the outstanding development of different areas such as information technology computer science, machining, robotics and so on, made possible a comprehensive transformation of the manufacturing systems. Present paper aims to give a general overview of the technologies and features of an advanced manufacturing system. Furthermore our study intends to justify why essential to apply these innovative technologies and realize the consequence of these changes in term of the customers and the different industries. The research mainly focuses on small and medium scale enterprises and their challenges to achieve competitive advantages with intelligent manufacturing systems in NPA regions especially in Norway.

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Section: E Micro-and Nano-electronicsmentioning

confidence: 99%

Future role of application of new technologies in small-and medium scale manufacturing systems: Regarding Intelligent and advanced manufacturing systems in northern peripheral area

Somlo¹,

Sziebig

2017

2017 IEEE 26th International Symposium on Industrial Electronics (ISIE)

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“…For example, on the basis of Human Cyber Physical fusion intelligence, Liu et al [3] discussed the mechanism of an intelligent manufacturing system with HCP fusion and collaboration, and explored the HCP data fusion mechanism, collaboration mechanism, and interaction mechanism. For concurrent simultaneous consideration of the reliability and safety of manufacturing systems, as well as flexibility and performance, a specialized control architecture was proposed by Ding et al [4]; they extended the architecture by a specific technique for the strategic controller. For the case of an intelligent manufacturing system which reacts adaptively to a human operator, control trajectories for a robot arm are computed online such that collision with the operator is excluded.…”

Section: Introductionmentioning

confidence: 99%

Investigation on Safety Dynamic Evolution Mechanism of a Distributed Low Carbon Manufacturing System with Large Time Delay

et al. 2022

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In order to reveal the inducing factors and safety dynamic evolution mechanism of frequent personal injury accidents under a low carbon manufacturing process, a nonlinear safety dynamic evolution model of a distributed low carbon manufacturing system with large time delay is established. The established model is then verified by simulation results from mathematical analysis and dynamic evolution. Moreover, qualitative analysis on nonlinear safety dynamic evolution and the trend of human–machine safety under a low carbon manufacturing process is investigated. Finally, an application case of the established model is studied. The key results are as follows: (1) There are four dynamic regions, namely the safety area I, the deterioration area II, the asymptotically stable safety area III, and the enhancement area IV of the safety ability in the interaction evolution model of carelessness and safety levels; (2) There are two singularities in the dynamic evolution model of the man–machine safety system with large time delay under a low carbon manufacturing process; (3) The equilibrium points of the human–machine safety system are El = (0, 0) and E2 = (0.5333, 0.2489), while changes in the carelessness level have a serious block effect on safety development with time; (4) For the radial tire casing process, the low carbon development trend of the technological process of radial tire casing is good, but low carbon structure and management have slightly lower low carbon levels. This work provides a theoretical basis for the safety evaluation and control of the distributed low carbon manufacturing human–machine safety system with large time delay.

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“…This motion planning problem can be solved by a variety of methods, e.g. [8], [9], [10], [15], provided that the safety critical regions F (t) are available.…”

Section: Introductionmentioning

confidence: 99%

Human arm motion modeling and long-term prediction for safe and efficient Human-Robot-Interaction

Ding

Reißig

Kurniawan

et al. 2011

2011 IEEE International Conference on Robotics and Automation

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Modeling and predicting human behavior is indispensable when industrial robots interacting with human operators are to be manipulated safely and efficiently. One challenge is that human operators tend to follow different motion patterns, depending on their intention and the structure of the environment. This precludes the use of classical estimation techniques based on kinematic or dynamic models, especially for the purpose of long-term prediction. In this paper, we propose a method based on Hidden Markov Models to predict the region of the workspace that is possibly occupied by the human within a prediction horizon. In contrast to predictions in the form of single points such as most likely human positions as obtained from previous approaches, the regions obtained here may serve as safety constraints when the robot motion is planned or optimized. This way one avoids collisions with a probability not less than a predefined threshold. The practicability of our method is demonstrated by successfully and accurately predicting the motion of a human arm in two scenarios involving multiple motion patterns.

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Increasing Reliability of Intelligent Manufacturing Systems by Adaptive Optimization and Safety Supervision

Cited by 7 publications

References 6 publications

Future role of application of new technologies in small-and medium scale manufacturing systems: Regarding Intelligent and advanced manufacturing systems in northern peripheral area

Future role of application of new technologies in small-and medium scale manufacturing systems: Regarding Intelligent and advanced manufacturing systems in northern peripheral area

Investigation on Safety Dynamic Evolution Mechanism of a Distributed Low Carbon Manufacturing System with Large Time Delay

Human arm motion modeling and long-term prediction for safe and efficient Human-Robot-Interaction

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