Design and Configuration of Machine Vision Robotic Cells in a Manufacturing System

2004 ◽  
Author(s):  
Roberto F. Lu
Keyword(s):  
Signal Processing ◽  
Machine Vision ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Robot Manipulator ◽  
Utilization Rate ◽  
Safety Control ◽  
Cell Functions ◽  
Wide Range ◽  
Robot Cell

Most fixed automations in traditional manufacturing systems are not equipped to manage product variations efficiently. This paper presents a design and configuration for a machine-vision-equipped robotic packing cell that is capable of managing a wide range of product sizes. Product size information is gathered at an earlier stage in the manufacturing process and then transferred electronically to the robot cell. Different controllers are needed to manage robot cell functions related to incoming product, machine vision, robot control, robot manipulator, and multiple layers of safety control information. Each controller, due to the nature of its function, has different advantages in processing different data types. In order to achieve the highest possible robot manipulator utilization rate, the assignment of information processing among controllers needs to be thoughtfully planned, especially for the critical mathematical routines. Coordination and calibration between charged-coupled device (CCD) cameras and robots in existing manufacturing facilities are configured with considerations for building vibrations, lighting conditions, and signal processing assignments among the available devices. System efficiency is improved when the vision signal, robot logical signal, and robot manipulator signal processing units are running cohesively in parallel. The capability of the machine-vision-assisted robot end effector automatic path adjustment, to pick up and pack different sizes of products dynamically, allows a higher level of flexibility and efficiency. This paper describes a feasible design and configuration for an integrated machine vision robotic cell in a manufacturing system.

Information Model for A-UGV Performance Measurement Standard

2020 ◽  
Author(s):  
Soocheol Yoon ◽  
Roger Bostelman
Keyword(s):  
Performance Measurement ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Information Model ◽  
International Committee ◽  
Ground Vehicles ◽  
Performance Information ◽  
Information Models ◽  
Wide Range ◽  
Model Instance

Abstract Automatic through autonomous - Unmanned Ground Vehicles (A-UGVs) have the potential to be applied over a wide range of manufacturing systems under industry 4.0 paradigm. In order to use A-UGVs efficiently in a manufacturing system, it is necessary to select the A-UGV suitable for each factory or workplace. A framework for evaluating the A-UGV performance under a specific manufacturing environment is needed. ASTM International Committee F45 has been developing standards2 providing a basis for A-UGV manufacturers and users to compare tasks to the A-UGV capabilities. This paper proposes information models for A-UGV performance measurement along the standards development. The standard needs are analyzed to show how the standard and information model can be used for the introduction of A-UGVs into factories. The information model in this paper provides a structured way to describe the factory elements affecting the A-UGV performance, and the measured A-UGV performances against the factory elements. To validate the proposed information model, an A-UGV performance testbed was built and the information model instance is developed to describe the testbed elements. An A-UGV is tested against the testbed elements and the measured performance is described by the other instance. This paper contributes to mutual understanding, between A-UGV makers and users, to deliver A-UGV performance information efficiently and to provide basis for A-UGVs to be tested under the same conditions.

Inhibition kinetics for propionate degradation using propionate-enriched mixed cultures

1998 ◽  
Vol 38 (8-9) ◽  
pp. 443-451 ◽  
Author(s):  
S. H. Hyun ◽  
J. C. Young ◽  
I. S. Kim
Keyword(s):  
Phase I ◽  
Competitive Inhibition ◽  
Gas Production ◽  
Phase Iii ◽  
Utilization Rate ◽  
Inhibition Kinetics ◽  
Wide Range ◽  
Propionate Degradation ◽  
Acetate Utilization ◽  
Velocity Coefficient

To study propionate inhibition kinetics, seed cultures for the experiment were obtained from a propionate-enriched steady-state anaerobic Master Culture Reactor (MCR) operated under a semi-continuous mode for over six months. The MCR received a loading of 1.0 g propionate COD/l-day and was maintained at a temperature of 35±1°C. Tests using serum bottle reactors consisted of four phases. Phase I tests were conducted for measurement of anaerobic gas production as a screening step for a wide range of propionate concentrations. Phase II was a repeat of phase I but with more frequent sampling and detailed analysis of components in the liquid sample using gas chromatography. In phase III, different concentrations of acetate were added along with 1.0 g propionate COD/l to observe acetate inhibition of propionate degradation. Finally in phase IV, different concentrations of propionate were added along with 100 and 200 mg acetate/l to confirm the effect of mutual inhibition. Biokinetic and inhibition coefficients were obtained using models of Monod, Haldane, and Han and Levenspiel through the use of non-linear curve fitting technique. Results showed that the values of kp, maximum propionate utilization rate, and Ksp, half-velocity coefficient for propionate conversion, were 0.257 mg HPr/mg VSS-hr and 200 mg HPr/l, respectively. The values of kA, maximum acetate utilization rate, and KsA, half-velocity coefficient for acetate conversion, were 0.216 mg HAc/mg VSS-hr and 58 mg HAc/l, respectively. The results of phase III and IV tests indicated there was non-competitive inhibition when the acetate concentration in the reactor exceeded 200 mg/l.

scholarly journals Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

2021 ◽  
Vol 13 (10) ◽  
pp. 5495
Author(s):  
Mihai Andronie ◽  
George Lăzăroiu ◽  
Roxana Ștefănescu ◽  
Cristian Uță ◽  
Irina Dijmărescu
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Literature Review ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Data Driven ◽  
Smart Manufacturing ◽  
Production Networks ◽  
Production Logistics ◽  
Time Production

With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.

Introduction of Flexible Manufacturing Systems as a Necessary Measure for the Russian Industrial Development

2019 ◽  
Vol 957 ◽  
pp. 195-202 ◽  
Author(s):  
Elizaveta Gromova
Keyword(s):  
Flexible Manufacturing ◽  
Flexible Manufacturing Systems ◽  
Industrial Development ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Agile Manufacturing ◽  
Industrial Sector ◽  
Business Environment ◽  
Maximum Speed ◽  
Industrial Enterprises

With the onset of the Fourth Industrial Revolution, the business environment becomes inherent in changes that occur with maximum speed, as well as characterized by the systemic nature of the consequences. One of them is the transformation of operational management models in industrial enterprises. The modern manufacturing system should focus not only on speed of response and flexibility, but also on the cost and quality of products. Integration of effective models: agile manufacturing, quick response manufacturing and lean production, in order to extract the best from them is proposed. The purpose of this study is to analyze this flexible manufacturing system and to relate it to the current state of the Russian industrial development. Theoretical and practical aspects of this model are presented. The examples of the flexible models introduction in the Russian industrial sector is allocated. The conclusion about the necessity of the flexible manufacturing systems implementation for the Russian industrial development is drawn.

scholarly journals Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nongeometric Errors

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yuxiang Wang ◽  
Zhangwei Chen ◽  
Hongfei Zu ◽  
Xiang Zhang ◽  
Chentao Mao ◽  
...  
Keyword(s):  
Neural Network ◽  
Manufacturing Systems ◽  
Robot Manipulator ◽  
Joint Stiffness ◽  
Calibration Method ◽  
Geometric Parameters ◽  
Heavy Load ◽  
Positioning Accuracy ◽  
Robot Positioning ◽  
Residual Errors

The positioning accuracy of a robot is of great significance in advanced robotic manufacturing systems. This paper proposes a novel calibration method for improving robot positioning accuracy. First of all, geometric parameters are identified on the basis of the product of exponentials (POE) formula. The errors of the reduction ratio and the coupling ratio are identified at the same time. Then, joint stiffness identification is carried out by adding a load to the end-effector. Finally, residual errors caused by nongeometric parameters are compensated by a multilayer perceptron neural network (MLPNN) based on beetle swarm optimization algorithm. The calibration is implemented on a SIASUN SR210D robot manipulator. Results show that the proposed method possesses better performance in terms of faster convergence and higher precision.

Modelling and control of manipulators with flexible links working on land and underwater environments

Robotica ◽  
2010 ◽  
Vol 29 (3) ◽  
pp. 461-470 ◽  
Author(s):  
Levent Gümüşel ◽  
Nurhan Gürsel Özmen
Keyword(s):  
Fuzzy Control ◽  
Control Method ◽  
Robot Manipulator ◽  
Control Methods ◽  
Control Laws ◽  
Linear Ordinary Differential Equations ◽  
Intelligent Technique ◽  
Wide Range ◽  
Classical Control ◽  
And Control

SUMMARYIn this study, modelling and control of a two-link robot manipulator whose first link is rigid and the second one is flexible is considered for both land and underwater conditions. Governing equations of the systems are derived from Hamilton's Principle and differential eigenvalue problem. A computer program is developed to solve non-linear ordinary differential equations defining the system dynamics by using Runge–Kutta algorithm. The response of the system is evaluated and compared by applying classical control methods; proportional control and proportional + derivative (PD) control and an intelligent technique; integral augmented fuzzy control method. Modelling of drag torques applied to the manipulators moving horizontally under the water is presented. The study confirmed the success of the proposed integral augmented fuzzy control laws as well as classical control methods to drive flexible robots in a wide range of working envelope without overshoot compared to the classical controls.

DECISION SUPPORT FOR A SUSTAINABLE PRODUCTION IN JOB SHOP MANUFACTURING SYSTEMS

10.6036/9917 ◽  
2021 ◽  
Vol 96 (5) ◽  
pp. 455-459
Author(s):  
MAHDI NADERI ◽  
ANTONIO FERNÁNDEZ ULLOA ◽  
JOSÉ ENRIQUE ARES GÓMEZ ◽  
GUSTAVO PELÁEZ LOURIDO
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Job Shop ◽  
Sustainable Production ◽  
Ease Of Use ◽  
Manufacturing Companies ◽  
Strategic Decisions ◽  
Production Environments

Despite the growing importance that is being given to the concepts of sustainability in many areas, not only in industry but also in the economy and public opinion in general, until now, most research has focused, practically, on the analysis of the concepts, but has not addressed, in a comprehensive way, its impact in decision making probably due to the complex relations of interdependence between its different aspects. In this context, MAPSAM (Methodology for the Assessment of Sustainability in Manufacturing Processes and Systems) was created to help the decision-making process, allowing a conscious and transparent assessment by administrators and managers at the different levels of the structure of companies and organisations. This article explains its development and application in a "job shop" type manufacturing system with an approach that allows the integration of economic, environmental and social criteria. MAPSAM is based on the use of various techniques and tools to quantify the importance of each aspect of sustainability and it has been applied in other production environments, being implemented in different systems, analysing their ease of use and evaluating their behaviour. The objective is to show how it helps to make operational, tactical and strategic decisions in the management on these type of manufacturing companies and, specifically, in this contribution we want to highlight its versatility and applicability, by validating it in a certain type of layout. With this new application, MAPSAM increases its possibilities as an innovative instrument that allows companies to make conscious and sustainable decisions in order to be more efficient, fair, supportive and respectful of the environment. Keywords: Manufacturing System, Simulation, Decision Support, Sustainable Production, Decision-Making

Interoperability in Cloud Manufacturing and Practice on Private Cloud Structure for SMEs

2017 ◽  
Author(s):  
Xi Vincent Wang ◽  
Lihui Wang
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
Research Work ◽  
Cloud Manufacturing ◽  
Cloud Services ◽  
Security Requirements ◽  
Research Trend ◽  
Safety Regulations ◽  
Multiple Challenges ◽  
New Research

In recent years, Cloud manufacturing has become a new research trend in manufacturing systems leading to the next generation of production paradigm. However, the interoperability issue still requires more research due to the heterogeneous environment caused by multiple Cloud services and applications developed in different platforms and languages. Therefore, this research aims to combat the interoperability issue in Cloud Manufacturing System. During implementation, the industrial users, especially Small- and Medium-sized Enterprises (SMEs), are normally short of budget for hardware and software investment due to financial stresses, but they are facing multiple challenges required by customers at the same time including security requirements, safety regulations. Therefore in this research work, the proposed Cloud manufacturing system is specifically tailored for SMEs.

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