Application and research of robot sorting system based on LabVIEW

2021 ◽  
pp. 1-8
Author(s):  
Xiaoping Huang ◽  
Fangyi Weng ◽  
Zhongxin Wei ◽  
M.M. Kamruzzaman
Keyword(s):  
Artificial Intelligence ◽  
Visual Processing ◽  
Production Efficiency ◽  
Servo Motor ◽  
Labor Input ◽  
Driving Function ◽  
Communication Function ◽  
Inverse Solutions ◽  
Solid Works ◽  
Sorting System

Sorting robot is a kind of artificial intelligence robot which has certain sense ability and can classify items. In the sorting industry, its appearance not only reduces the labor input, but also improves the production efficiency of the sorting industry. In this paper, a production line composed of linear Delta robot and 3-DOF robot is studied. The forward and inverse solutions are calculated by MATLAB and simulated by Solid Works. Through the visual processing function, communication function and axle card driving function of Lab VIEW software, the servo motor rotation is controlled to achieve the purpose of the end moving along the predetermined trajectory, and finally the visual sorting function is realized.

Design of Surface Quality Inspection and Sorting System of Honeycomb Ceramics

2014 ◽  
Vol 556-562 ◽  
pp. 2890-2894
Author(s):  
Wei Jun Dai
Keyword(s):  
Control System ◽  
Surface Quality ◽  
Production Efficiency ◽  
Surface Inspection ◽  
Quality Inspection ◽  
Servo Motor ◽  
Ccd Cameras ◽  
Electrical Control ◽  
Image Inspection ◽  
Sorting System

According to the surface quality inspection requirements of honeycomb ceramics, an intelligent image inspection and sorting system based on machine vision was designed. The working flow of the designed system includes four steps: top inspection, bottom inspection, side inspection and sorting. Top images and bottom images are captured with area scan CCD cameras. The workpiece rotation (360°) was driven by the turntable unit driven by a servo motor and an encoder while workpiece side images were captured with line scan CCD cameras. The captured images were sent to IPC inspection software for processing and judgment. Then the judgment results were sent to the PLC electrical control system. Unqualified products were picked out by the PLC-controlled sorting unit. The designed system realized the rapid surface inspection and accurate sorting of honeycomb ceramics and improved the production efficiency.

Design of Surface Quality Inspection and Sorting System of Honeycomb Ceramics

2014 ◽  
Vol 543-547 ◽  
pp. 975-980 ◽  
Author(s):  
Wei Jun Dai
Keyword(s):  
Control System ◽  
Surface Quality ◽  
Production Efficiency ◽  
Surface Inspection ◽  
Quality Inspection ◽  
Servo Motor ◽  
Ccd Cameras ◽  
Electrical Control ◽  
Image Inspection ◽  
Sorting System

According to the surface quality inspection requirements of honeycomb ceramics, an intelligent image inspection and sorting system based on machine vision was designed. The working flow of the designed system includes four steps: top inspection, bottom inspection, side inspection and sorting. Top images and bottom images are captured with area scan CCD cameras. The workpiece rotation (360°) was driven by the turntable unit driven by a servo motor and an encoder while workpiece side images were captured with line scan CCD cameras. The captured images were sent to IPC inspection software for processing and judgment. Then the judgment results were sent to the PLC electrical control system. Unqualified products were picked out by the PLC-controlled sorting unit. The designed system realized the rapid surface inspection and accurate sorting of honeycomb ceramics and improved the production efficiency.

Symmetric Beauty: Double-Position Numerical Control Press Based on Lever-Toggle Force Amplifying Mechanism Driven by Linear Servo Motor

2011 ◽  
Vol 201-203 ◽  
pp. 2250-2253
Author(s):  
Fan Wu ◽  
Ming Di Wang ◽  
Kang Min Zhong
Keyword(s):  
Production Efficiency ◽  
Lower Cost ◽  
Pressure Head ◽  
Numerical Control ◽  
Servo Motor ◽  
Ac Motor ◽  
Mechanical Press ◽  
Working Principle ◽  
Characteristic Features ◽  
Stretching Process

According to the conception of symmetric beauty in the aesthetics, a new kind of numerical control press with double operating positions based on lever-toggle force amplifying mechanism driven by linear servo motor is introduced here. Its working principle, characteristic features and mechanical calculating formulas are given also. Compared with traditional mechanical press based on the crank-linkage-slider mechanism driven by common AC motor, the system has following advantages: two operating positions, higher energy transmission and production efficiency, no environmental pollution; lower cost of machine tool. Through rationally designing the acceleration curve of the pressure head, the impacting noise of the system can be reduced greatly. This press is especially suitable for blanking and low-stretching process.

scholarly journals Challenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry

2021 ◽  
Vol 11 (22) ◽  
pp. 10919
Author(s):  
Seokjae Heo ◽  
Sehee Han ◽  
Yoonsoo Shin ◽  
Seunguk Na
Keyword(s):  
Artificial Intelligence ◽  
Human Resources ◽  
Human Resource Development ◽  
Human Resource ◽  
Production Efficiency ◽  
Industrial Revolution ◽  
Current Method ◽  
Mechanical Equipment ◽  
Light Industry ◽  
Labor Division

The paper examines that many human resources are needed on the research and development (R&D) process of artificial intelligence (AI) and discusses factors to consider on the current method of development. Labor division of a few managers and numerous ordinary workers as a form of light industry appears to be a plausible method of enhancing the efficiency of AI R&D projects. Thus, the research team regards the development process of AI, which maximizes production efficiency by handling digital resources named ‘data’ with mechanical equipment called ‘computers’, as the digital light industry of the fourth industrial era. As experienced during the previous Industrial Revolution, if human resources are efficiently distributed and utilized, no less progress than that observed in the second Industrial Revolution can be expected in the digital light industry, and human resource development for this is considered urgent. Based on current AI R&D projects, this study conducted a detailed analysis of necessary tasks for each AI learning step and investigated the urgency of R&D human resource training. If human resources are educated and trained, this could lead to specialized development, and new value creation in the AI era can be expected.

scholarly journals Concept of convergence of augmented reality technologies and artificial intelligence for spe-cial purpose vehicles

2021 ◽  
pp. 235
Author(s):  
Oleh Nikonov
Keyword(s):  
Artificial Intelligence ◽  
Augmented Reality ◽  
Production Efficiency ◽  
Economic Effects ◽  
Increase Production Efficiency ◽  
Goods And Services ◽  
Important Trend ◽  
Augmented Reality Technology ◽  
Intelligent Information ◽  
And Control

The use of artificial intelligence is a modern important trend in the creation of promising information and control systems of vehicles, including special purpose. The high demands on augmented reality software simply cannot rely solely on human programming to display virtual objects against the real world. Neural networks and machine learning can perform these tasks with much greater efficiency and can greatly improve the augmented reality experience. Goal. The purpose of the article is to develop the concept of convergence of augmented reality and artificial intelligence technologies for special purpose vehicles. Methodology. Artificial intelligence technologies contribute to the transformation of the economy, labor market, government institutions and society as a whole. The use of artificial intelligence technologies helps to reduce costs, increase production efficiency, quality of goods and services. Augmented reality technology offers more innovative methods of visualization by expanding the boundaries of reality, controlling the perspective of the object and visualization in a real context. Results. The concept of convergence of augmented reality and artificial intelligence technologies for special purpose vehicles based on a synergetic approach has been developed. An integrated intelligent information and control system for special purpose vehicles with augmented reality technology has been developed. Originality. Using the convergence of augmented reality and artificial intelligence technologies for special purpose vehicles. Practical value. Convergence is the foundation for achieving numerous positive social and economic effects. The use of augmented reality technology and artificial intelligence can significantly increase the efficiency of special purpose vehicles.

scholarly journals Smart Controller for Efficient Domestic Cashew nut Cutting Machine

2020 ◽  
Vol 8 (5) ◽  
pp. 703-709
Keyword(s):  
Continuous Flow ◽  
Production Efficiency ◽  
Gravitational Force ◽  
Research Work ◽  
Pi Controller ◽  
Servo Motor ◽  
Cashew Nut ◽  
Cutting Machine ◽  
Punching Process ◽  
Kernel Form

India is one of the world’s largest country in terms of exportingers of cashews nuts in kernel form. Currently, more number of labours are engaged in the cashew processing industry. This research work, an automotive cashew shelling method is introduced to improve the production efficiency. It is an electronic based system which enables a continuous flow of shelless. After de-shelling the cashew nut, it falls beneath the cutter due to gravitational force and shelless cashew nuts cumulated in a vessel. Thus the proposed system has the advantage of reducing man power, time consuming and also increases the selling cost. It comprises two process. They are heating and punching process. Both processes are used to remove the cashew kernel from the shell without damage. Here a servo motor is used to extract the shell from the raw cashew. In addition, here PI controller is used to control the entire operation. Then, two blades are used to cleft the nut by operating as handle of cutter. Thus the operation forces the shell to fracture open without detaching the kernel.

scholarly journals Exploring Minds: Modes of Modeling and Simulation in Artificial Intelligence

2021 ◽  
Vol 29 (4) ◽  
pp. 409-435
Author(s):  
Hajo Greif
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Processes ◽  
Visual Processing ◽  
Theory Development ◽  
General Level ◽  
Theory Of Computation ◽  
Theory Of Intelligence ◽  
Cognitive Simulation ◽  
Modes Of Representation ◽  
Turing’S Imitation Game

Abstract The aim of this paper is to grasp the relevant distinctions between various ways in which models and simulations in Artificial Intelligence (AI) relate to cognitive phenomena. In order to get a systematic picture, a taxonomy is developed that is based on the coordinates of formal versus material analogies and theory-guided versus pre-theoretic models in science. These distinctions have parallels in the computational versus mimetic aspects and in analytic versus exploratory types of computer simulation. The proposed taxonomy cuts across the traditional dichotomies between symbolic and embodied AI, general intelligence and symbol and intelligence and cognitive simulation and human/non-human-like AI. According to the taxonomy proposed here, one can distinguish between four distinct general approaches that figured prominently in early and classical AI, and that have partly developed into distinct research programs: first, phenomenal simulations (e.g., Turing’s “imitation game”); second, simulations that explore general-level formal isomorphisms in pursuit of a general theory of intelligence (e.g., logic-based AI); third, simulations as exploratory material models that serve to develop theoretical accounts of cognitive processes (e.g., Marr’s stages of visual processing and classical connectionism); and fourth, simulations as strictly formal models of a theory of computation that postulates cognitive processes to be isomorphic with computational processes (strong symbolic AI). In continuation of pragmatic views of the modes of modeling and simulating world affairs, this taxonomy of approaches to modeling in AI helps to elucidate how available computational concepts and simulational resources contribute to the modes of representation and theory development in AI research—and what made that research program uniquely dependent on them.

Pointing the way

1997 ◽  
Vol 20 (4) ◽  
pp. 758-763
Author(s):  
Dana H. Ballard ◽  
Mary M. Hayhoe ◽  
Polly K. Pook ◽  
Rajesh P. N. Rao
Keyword(s):  
Artificial Intelligence ◽  
Eye Movements ◽  
Embodied Cognition ◽  
Visual Processing ◽  
Human Intelligence ◽  
The Core ◽  
Satisfactory Account ◽  
The Way

The majority of commentators agree that the time to focus on embodiment has arrived and that the disembodied approach that was taken from the birth of artificial intelligence is unlikely to provide a satisfactory account of the special features of human intelligence. In our Response, we begin by addressing the general comments and criticisms directed at the emerging enterprise of deictic and embodied cognition. In subsequent sections we examine the topics that constitute the core of the commentaries: embodiment mechanisms, dorsal and ventral visual processing, eye movements, and learning.

A Study on Deep Learning Methods in the Concept of Digital Industry 4.0

2021 ◽  
pp. 318-339
Author(s):  
Mehmet Ali Şimşek ◽  
Zeynep Orman
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Deep Learning ◽  
Industry 4.0 ◽  
Production Efficiency ◽  
Learning Technologies ◽  
High Potential ◽  
Data Sets ◽  
Learning Methods ◽  
Intelligence Studies

Nowadays, the main features of Industry 4.0 are interpreted to the ability of machines to communicate with each other and with a system, increasing the production efficiency and development of the decision-making mechanisms of robots. In these cases, new analytical algorithms of Industry 4.0 are needed. By using deep learning technologies, various industrial challenging problems in Industry 4.0 can be solved. Deep learning provides algorithms that can give better results on datasets owing to hidden layers. In this chapter, deep learning methods used in Industry 4.0 are examined and explained. In addition, data sets, metrics, methods, and tools used in the previous studies are explained. This study can lead to artificial intelligence studies with high potential to accelerate the implementation of Industry 4.0. Therefore, the authors believe that it will be very useful for researchers and practitioners who want to do research on this topic.

Sign in / Sign up

Export Citation Format

Share Document