A Vision-Based Framework for Enhanced Quality Control in a Smart Manufacturing System

2019 ◽  
Author(s):  
Zixuan Yang ◽  
Huaiyuan Teng ◽  
Jeremy Goldhawk ◽  
Ilya Kovalenko ◽  
Efe C. Balta ◽  
...  
Keyword(s):  
Computer Vision ◽  
Quality Control ◽  
Computer Aided Design ◽  
Manufacturing Systems ◽  
Smart Manufacturing ◽  
Dimensional Metrology ◽  
Design Changes ◽  
Central Controller ◽  
Aided Design ◽  
Smart Manufacturing Systems

Abstract Dimensional metrology is an integral part of quality control in manufacturing systems. Most existing manufacturing systems utilize contact-based metrology, which is time consuming and not flexible to design changes. There have been recent applications of computer vision for performing dimensional metrology in manufacturing systems. Existing computer vision metrology techniques need repeated calibration of the system and are not utilized with data analysis methods to improve decision making. In this work, we propose a robust non-contact computer vision metrology pipeline integrated with Computer Aided Design (CAD) that has the capacity to enable control of smart manufacturing systems. The pipeline uses CAD data to extract nominal dimensions and tolerances. The dimensions are compared to the measured ones, computed using camera images and computer vision algorithms. A quality check module evaluates if the measurements are within admissible bounds and informs a central controller. If a part does not meet a tolerance, the central controller changes a program running on a specific machine to ensure that parts meet the necessary specifications. Results from an implementation of the proposed pipeline on a manufacturing research testbed are given at the end.

scholarly journals Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1467 ◽  
Author(s):  
Zeinab Shahbazi ◽  
Yung-Cheol Byun
Keyword(s):  
Machine Learning ◽  
Quality Control ◽  
Manufacturing Systems ◽  
True Positive Rate ◽  
Machine Learning Techniques ◽  
Smart Manufacturing ◽  
Control Approach ◽  
Learning Techniques ◽  
Positive Rate ◽  
Smart Manufacturing Systems

Smart manufacturing systems are growing based on the various requests for predicting the reliability and quality of equipment. Many machine learning techniques are being examined to that end. Another issue which considers an important part of industry is data security and management. To overcome the problems mentioned above, we applied the integrated methods of blockchain and machine learning to secure system transactions and handle a dataset to overcome the fake dataset. To manage and analyze the collected dataset, big data techniques were used. The blockchain system was implemented in the private Hyperledger Fabric platform. Similarly, the fault diagnosis prediction aspect was evaluated based on the hybrid prediction technique. The system’s quality control was evaluated based on non-linear machine learning techniques, which modeled that complex environment and found the true positive rate of the system’s quality control approach.

The Use of IGES in Rapid and Automated Design Prototyping

1988 ◽  
Author(s):  
J. A. Kirk ◽  
D. K. Anand ◽  
M. Anjanappa ◽  
W. K. Rickert
Keyword(s):  
Flexible Manufacturing ◽  
Computer Aided Design ◽  
Manufacturing Systems ◽  
Data File ◽  
Cnc Machining ◽  
Design Data ◽  
University Of Maryland ◽  
Design Representation ◽  
Design Changes ◽  
Aided Design

Abstract The Initial Graphic Exchange Specification (IGES) for design data and the EIA standard M and G Codes for Numerically Controlled machines (N/C) is used to develop an automated interface between existing computer aided design systems and N/C manufacturing systems. The Flexible Manufacturing Protocol, developed at the University of Maryland, outlines such an interface to control automated manufacturing cells used for prototyping quick design changes. This paper demonstrates one application of the protocol, developing an automated IGES to CNC interface to control a 3 axis CNC machining center given the geometric representation of the part in IGES format. Wireframe representations of 2-1/2 dimensional parts, composed of linear elements, are the primary tools used for design representation. The automated production of the sample part, presented in this paper, demonstrates that rapid prototyping is possible using an IGES design data file as input to the protocol.

scholarly journals A Model for Working Environment Monitoring in Smart Manufacturing

2021 ◽  
Vol 11 (6) ◽  
pp. 2850
Author(s):  
Dalibor Dobrilovic ◽  
Vladimir Brtka ◽  
Zeljko Stojanov ◽  
Gordana Jotanovic ◽  
Dragan Perakovic ◽  
...  
Keyword(s):  
Open Source ◽  
Student Teaching ◽  
Manufacturing Systems ◽  
Working Environment ◽  
Smart Manufacturing ◽  
Environment Monitoring ◽  
Application Development ◽  
Testing Platform ◽  
Proposed Model ◽  
Smart Manufacturing Systems

The growing application of smart manufacturing systems and the expansion of the Industry 4.0 model have created a need for new teaching platforms for education, rapid application development, and testing. This research addresses this need with a proposal for a model of working environment monitoring in smart manufacturing, based on emerging wireless sensor technologies and the message queuing telemetry transport (MQTT) protocol. In accordance with the proposed model, a testing platform was developed. The testing platform was built on open-source hardware and software components. The testing platform was used for the validation of the model within the presented experimental environment. The results showed that the proposed model could be developed by mainly using open-source components, which can then be used to simulate different scenarios, applications, and target systems. Furthermore, the presented stable and functional platform proved to be applicable in the process of rapid prototyping, and software development for the targeted systems, as well as for student teaching as part of the engineering education process.

INTEGRATION AND EVALUATION OF A PROPOSAL FOR STRATEGIC KNOWLEDGE TEACHING IN CAD

10.6036/9505 ◽  
2021 ◽  
Vol 96 (1) ◽  
pp. 145-149
Author(s):  
XABIER GARIKANO OSINAGA ◽  
MIKEL GARMENDIA MUJIKA ◽  
ANGEL PEREZ MANSO ◽  
ENEKO SOLABERRIETA MENDEZ
Keyword(s):  
Computer Aided Design ◽  
Empirical Test ◽  
Control Group ◽  
Strategic Knowledge ◽  
Learning Framework ◽  
Design Changes ◽  
Professional Requirements ◽  
Teaching Learning ◽  
Didactic Strategies ◽  
Aided Design

Computer-aided design competency is critical for an engineering graduate starting in the world of work. Therefore, the development of this competency must be in line with professional requirements and consider the design constraints. For example, in the case of modeling, a geometrically correct model may not be sufficient if it is unable to withstand the modifications required by design changes. Therefore, we consider that training must be based on the development of this knowledge, known as strategic knowledge, and encourage its acquisition. This article describes a CAD training proposal focused on the development of strategic knowledge. Starting from the contributions of researchers, the modeling process is broken down so that it can be reproduced in the different scenarios that may be presented at the time of modeling. In order to facilitate the acquisition of this knowledge, an active learning framework has been established and specific didactic strategies have been developed for this purpose. Finally, the results of an empirical test are presented after the implementation of this proposal in which the results show a notable improvement in the experimental group in relation to the control group. Keywords: CAD modeling, teaching-learning, strategic knowledge

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