Intelligent Process Planning for Smart Factory and Smart Manufacturing

2020 ◽  
pp. 205-214
Author(s):  
Mijodrag Milošević ◽  
Mića Đurđev ◽  
Dejan Lukić ◽  
Aco Antić ◽  
Nicolae Ungureanu
Keyword(s):  
Process Planning ◽  
Smart Factory ◽  
Smart Manufacturing ◽  
Intelligent Process

Implementation of MQTT protocol based network architecture for smart factory

2021 ◽  
pp. 095440542110144
Author(s):  
Chia-Shin Yeh ◽  
Shang-Liang Chen ◽  
I-Ching Li
Keyword(s):  
Machine Tool ◽  
Gesture Recognition ◽  
Manufacturing Process ◽  
Network Architecture ◽  
Information Management System ◽  
Edge Computing ◽  
Smart Factory ◽  
Smart Manufacturing ◽  
Industrial Iot ◽  
Computing Module

The core concept of smart manufacturing is based on digitization to construct intelligent production and management in the manufacturing process. By digitizing the production process and connecting all levels from product design to service, the purpose of improving manufacturing efficiency, reducing production cost, enhancing product quality, and optimizing user experience can be achieved. To digitize the manufacturing process, IoT technology will have to be introduced into the manufacturing process to collect and analyze process information. However, one of the most important problems in building the industrial IoT (IIoT) environment is that different industrial network protocols are used for different equipment in factories. Therefore, the information in the manufacturing process may not be easily exchanged and obtained. To solve the above problem, a smart factory network architecture based on MQTT (MQ Telemetry Transport), IoT communication protocol, is proposed in this study, to construct a heterogeneous interface communication bridge between the machine tool, embedded device Raspberry Pi, and website. Finally, the system architecture is implemented and imported into the factory, and a smart manufacturing information management system is developed. The edge computing module is set up beside a three-axis machine tool, and a human-machine interface is built for the user controlling and monitoring. Users can also monitor the system through the dynamically updating website at any time and any place. The function of real-time gesture recognition based on image technology is developed and built on the edge computing module. The gesture recognition results can be transmitted to the machine controller through MQTT, and the machine will execute the corresponding action according to different gestures to achieve human-robot collaboration. The MQTT transmission architecture developed here is validated by the given edge computing application. It can serve as the basis for the construction of the IIoT environment, assist the traditional manufacturing industry to prepare for digitization, and accelerate the practice of smart manufacturing.

Intelligent process planning methods for the manufacturing of moulds

2011 ◽  
Vol 40 (1/2) ◽  
pp. 64 ◽  
Author(s):  
Dirk Biermann ◽  
Andreas Zabel ◽  
Thomas Michelitsch ◽  
Petra Kersting
Keyword(s):  
Process Planning ◽  
Planning Methods ◽  
Intelligent Process

scholarly journals Toward Knowledge Management for Smart Manufacturing

2017 ◽  
Vol 17 (3) ◽  
Author(s):  
Shaw C. Feng ◽  
William Z. Bernstein ◽  
Thomas Hedberg ◽  
Allison Barnard Feeney
Keyword(s):  
Knowledge Management ◽  
Design Process ◽  
Process Planning ◽  
Smart Manufacturing ◽  
Specific Knowledge ◽  
Domain Specific ◽  
Domain Specific Knowledge ◽  
Knowledge Objects ◽  
Planning Production

The need for capturing knowledge in the digital form in design, process planning, production, and inspection has increasingly become an issue in manufacturing industries as the variety and complexity of product lifecycle applications increase. Both knowledge and data need to be well managed for quality assurance, lifecycle impact assessment, and design improvement. Some technical barriers exist today that inhibit industry from fully utilizing design, planning, processing, and inspection knowledge. The primary barrier is a lack of a well-accepted mechanism that enables users to integrate data and knowledge. This paper prescribes knowledge management to address a lack of mechanisms for integrating, sharing, and updating domain-specific knowledge in smart manufacturing (SM). Aspects of the knowledge constructs include conceptual design, detailed design, process planning, material property, production, and inspection. The main contribution of this paper is to provide a methodology on what knowledge manufacturing organizations access, update, and archive in the context of SM. The case study in this paper provides some example knowledge objects to enable SM.

Intelligent Process Planning

2010 ◽  
pp. 273-300
Author(s):  
Zude Zhou ◽  
Huaiqing Wang ◽  
Ping Lou
Keyword(s):  
Process Planning ◽  
Manufacturing Sector ◽  
Effective Means ◽  
Case Based Reasoning ◽  
Computer Aided Process Planning ◽  
Computer Aided ◽  
Multi Agent ◽  
Manual Methods ◽  
Technical Capacity ◽  
Intelligent Process

Computer Aided Process Planning is very hot topic in the manufacturing. It uses the geometric information (such as shape, size, etc.) and information technology (such as materials, heat treatment, bulk, etc.) which are input into the computer to output parts of the route of the process and the procedures automatically. Process planning is very important in the manufacturing process. With the continuous development of the manufacturing sector, the traditional manual methods of Process Planning flaws more and more serious. Computer-aided technology can increase their technical capacity effectively. CAPP is an effective means to improve the design. The research of CAPP has got a very huge development, from the search logic structure, Variant, Generative, and Hybrid to Expert System. In the future, the development of the CAPP will focus on the extending of the application scope, depth and level. In this chapter, a general introduction is presented firstly. Then the application of genetic algorithm (GA) to CAPP is introduced. Thirdly implement of ANN in CAPP System is presented. In the fourth part, use of Case-Based Reasoning in CAPP is discussed. Fourthly, CAPP based on Multi-Agent (MAS) system is illustrated.

scholarly journals Intelligent Process Planning System for End-milling Process (2nd Report)

2010 ◽  
Vol 76 (6) ◽  
pp. 658-662
Author(s):  
Masanori MUROZUMI ◽  
Keiji OGAWA ◽  
Heisaburo NAKAGAWA ◽  
Yoshiaki KAKINO
Keyword(s):  
Process Planning ◽  
End Milling ◽  
Milling Process ◽  
Planning System ◽  
Process Planning System ◽  
Intelligent Process ◽  
End Milling Process
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