Application of Artificial Intelligence in Manufacturing Systems

Ondrej, Staš; Tolnay, Marian; Magdolen, Luboš

doi:10.1142/9789814289795_0005

Cited by 4 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The system was realized in a computer prototype program. The major aim of Sta et al [122] was the real time analysis of the position of a product on a moving conveyor, the position data was sent to a Selective Compliance Assembly Robot Arm (SCARA) robot controller, which moved the product from the conveyor to a palletizing system. Real time data was acquired by three high resolution cameras.…”

Section: Intelligent Manufacturingmentioning

confidence: 99%

A Review of Artificial Intelligence Algorithms Used for Smart Machine Tools

2018

View full text Add to dashboard Cite

This paper offers a review of the artificial intelligence (AI) algorithms and applications presently being used for smart machine tools. These AI methods can be classified as learning algorithms (deep, meta-, unsupervised, supervised, and reinforcement learning) for diagnosis and detection of faults in mechanical components and AI technique applications in smart machine tools including intelligent manufacturing, cyber-physical systems, mechanical components prognosis, and smart sensors. A diagram of the architecture of AI schemes used for smart machine tools has been included. The respective strengths and weaknesses of the methods, as well as the challenges and future trends in AI schemes, are discussed. In the future, we will propose several AI approaches to tackle mechanical components as well as addressing different AI algorithms to deal with smart machine tools and the acquisition of accurate results.Keywords: artificial intelligence; smart machine tools; learning algorithms; intelligent manufacturing; fault diagnosis and prognosis Brief IntroductionWe believe that a new epoch of the "Industrial Internet of Things (IIoT) plus artificial intelligence (AI)", characterized by big machinery data, data-driven techniques, ubiquitous networks, mass innovation, automatic intelligence, cross-border integration, and shared services, has arrived [1-3]. The fast development and combination of new AI and energy technologies, for materials, bioscience, the Internet, and new-generation information exchange, is a fundamental part of this new epoch. This will, in turn, permit game-changing transformation of models, ecosystems, and means in the light of their application to national security, well-being, and the economy. The main objective is a review and summary of recent achievement in data-based techniques, especially for complicated industrial applications, offering reference for further study from both an academic and practical point of view. Yin et al.[1] describes a brief evolutionary overview of data-based techniques over the last two decades. Recent development of modern industrial applications is presented mainly from the perspectives of monitoring and control. Their methodology, based on process measurements and model-data integrated techniques, will be introduced in the next study. Jeschke et al. [2] developed the core system science needed to enable the development of complex IIoT/manufacturing cyber-physical systems (CPS). Moreover, readers can learn the current state of IIoT and the concept of cybermanufacturing from this book. In 2014, Lund et al. [3] described the central issues contributing to, and characterizing, the worldwide and regional growth of the IoT. Besides, researchers can utilize the trend analysis of IoT their region markets in the future.There are many AI algorithms for machine health monitoring and other machine tool applications: The second-order recurrent neural networks (RNN) method for the learning and extraction of finite

show abstract

Section: Intelligent Manufacturingmentioning

confidence: 99%

A Review of Artificial Intelligence Algorithms Used for Smart Machine Tools

2018

View full text Add to dashboard Cite

show abstract

“…Measurements of the induced residual stresses can identify their magnitude and location. Photoelasticity is a simple method for testing transparent materials; other techniques destroy the measured part [3,6,10]. A more sophisticated method is the hole-drilling technique, which quantifies the deformation of the sample while drilling a hole, and the corresponding stress is calculated from the deformation.…”

Section: Introductionmentioning

confidence: 99%

An Approach for Residual Stress Determination by Mechanical Indentation Technique

Bílek¹,

Lukovics²,

Samek³

et al. 2012

Scientific Proceedings Faculty of Mechanical Engineering STU in Bratislava

View full text Add to dashboard Cite

Residual stresses lower the utility value of plastic parts. Determination of the induced stresses can help deal with them. Measurements are time-consuming and expensive. A new approach to measuring residual stresses, such as indentation measurement, can lead to the simple determination of residual stresses. The paper shows the relationship between the condition of injection moulding, the subsequent residual stress, and hardness through thickness. The computer model displays the field and magnitude of residual stress in the samples. The model results are then compared to measured parameters after indentation and the magnitude of residual stress determined by the standard hole drilling method.

show abstract

Implementation of Two Cameras to Robotic Cell for Recognition of Components

Sukop

2013

AMM

View full text Add to dashboard Cite

This paper describes the proposal and implementation of two camera sensor system used in combination with SCARA robot for sorting process control. Theoretical basics of 3D camera sensor evaluation and options for mutual camera placement are included. The paper is focused on sensor system components selection and implementation specifics for particular robotic system as well. Sensor system uses OMRON Vision Mate Controller for basic image recognition and PC for resulting data processing of specific points three dimensional position calculation.

show abstract

Application of Artificial Intelligence in Manufacturing Systems

Cited by 4 publications

References 0 publications

A Review of Artificial Intelligence Algorithms Used for Smart Machine Tools

A Review of Artificial Intelligence Algorithms Used for Smart Machine Tools

An Approach for Residual Stress Determination by Mechanical Indentation Technique

Implementation of Two Cameras to Robotic Cell for Recognition of Components

Contact Info

Product

Resources

About