CNC machine based on embedded wireless and Internet of Things for workshop development

Al-Saedi, Ibtesam R. K.; Mohammed, Farag Mahel; Obayes, Saifaldeen S.

doi:10.1109/cadiag.2017.8075699

Cited by 22 publications

(6 citation statements)

References 10 publications

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“…Periodical tests on manufacturing pieces report the local parameters to a monitoring system, which stores and analyzes data to assess the manufacturing qualities with respect to employed time. The authors of [18] focus on the integration of wireless technology and a Computer Aided Manufacturing (CAM) system for Computer Numerical Control (CNC) workshop development. The focus of the case study is to show a complete phase of manufacturing, starting from Computer Aided Design (CAD) modeling, machine processing, and data gathering.…”

Section: Iot Monitoring Systems In Industrial Manufacturingmentioning

confidence: 99%

A Condition and Fault Prevention Monitoring System for Industrial Computer Numerical Control Machinery

Ragnoli,

Pavone,

Epicoco

et al. 2024

IEEE Access

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Nowadays, the integration of smart systems within the modern industrial scenario is a continuously growing paradigm. Computer Numerical Control (CNC) machinery can heavily benefit from the introduction of Artificial Intelligence (AI) based monitoring applications. In this paper, we present an industrial condition and fault prevention monitoring system for CNC tools. The developed system is the result of an industrial project aimed at realizing a multi-purpose machine which is currently in pre-commercial stage. The results of this work represent the base platform for the further commercial development, which will be carried on from the industrial partners in accordance with clients feedbacks and specifications. This work presents the hardware architecture of the system, the web-based monitoring platform for remote management, and the AI framework used for fault monitoring. The multi-purpose machine is equipped with accelerometer units to monitor the vibration in multiple points of the structure. The control unit of the machine is connected to the sensing nodes and is used to communicate the actual machine state to a remote web platform. The accelerometric data are analyzed through an AI algorithm to perform fault detection. The fault detection algorithm was trained with the measurements performed on the machine under controlled environment faulty operation. The Internet of Things (IoT) based architecture has proven to be effective to facilitate the supervision of the machining processes, and the AI-based classification shows good classification performances for the fault detection tests.

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Section: Iot Monitoring Systems In Industrial Manufacturingmentioning

confidence: 99%

A Condition and Fault Prevention Monitoring System for Industrial Computer Numerical Control Machinery

Ragnoli,

Pavone,

Epicoco

et al. 2024

IEEE Access

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show abstract

“…Research focuses on wireless communications and CAD/CAM technologies in CNC workshop production in a particular work. An IoT concept using temperature, accelerometers, and gyroscopes is implemented to monitor machining operations [5].…”

Section: A Review Of Iot In Manufacturingmentioning

confidence: 99%

Internet of Things Based Cutting Tool Status Monitoring in a Computer Numerical Control Milling Machine

Natarajan¹,

Gokulachandran²

2021

Int. J. Adv. Sci. Eng. Inf. Technol.

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The Internet of Things (IoT) in the manufacturing industry shares machine data in real time. The majority of industrial data can be gathered and processed from machines and other remote IoT devices in a production system through data streaming. As sensors become smaller and more affordable, the Internet of things will attract more attention. It is possible to employ a wide range of sensors for monitoring, and with efficient open-source software, the status of the operation can be evaluated effectively. Our work aims at providing instructions for sending data (cutting tool status time) from Particle Photon devices connected to CNC milling machines to open-source software called ThingSpeak. This task is accomplished by integrating the Particle Photon device with the infrared sensor to the CNC milling machine. Three axis CNC vertical milling machine is used to manufacture the sample component. The status of the cutting tool, in this case the cutting time for each machining feature is monitored. Using infrared technology, the sensor detects whether the cutting tool is present. Particle photons measure machining time and communicate it to ThingSpeak. The ThingSpeak library will interpret the cloud information and displays it. With ThingSpeak software, we define the fields for various cutting tools and track every tool in real time. The time recorded using ThingSpeak software is found to be near to the time, which is monitored manually by the user. A major step in computer assisted process planning in manufacturing is monitoring the machining time for each cutting tool and it is successfully implemented in this research work.

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“…Wang et al [5] applied NX MCD to determine pose by solving the transformation matrix provided by the solver engine, enhancing this with a sampling strategy optimized beyond traditional equidistant approaches by incorporating rigid body constraints. Furthermore, Al-Saedi et al [6] leveraged MATLAB and NX software for modeling, using multiple sensors to monitor the machining process within a workshop. Lastly, Huang et al [7] implemented NX MCD for industrial robots and training related to the "1+X" programming certificate.…”

Section: Introductionmentioning

confidence: 99%

Design of a material sorting digital twin system based on NX MCD

Li,

Yang

2024

Manufacturing Rev.

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Current methods of manually checking whether materials meet the required standards are inefficient and harmful to workers' health. To address the complexity and variability of real-world systems, it is imperative to establish highly consistent digital models for subsequent operations. However, there is a challenge in unifying various modules and components into a single system and optimizing them for functionality. A mechatronic solution is proposed for material sorting within the production manufacturing process, leveraging Siemens TIA Portal and NX 2007. The solution involves constructing a physical platform and realizing a digital twin system to enable real-virtual interaction via communication protocols. Initially, a virtual material sorting simulation and debugging platform is established using NX software, while operations are conducted in the TIA Portal. Subsequently, the control program is designed within the TIA Portal, and Virtual PLCs are created using PLCSIM Advanced for virtual debugging and analysis, confirming the solution's feasibility. Following this, the physical material sorting platform is developed, utilizing Siemens S7-1500 PLC to manage inverter and servo motor operations. Ultimately, the OPC UA communication protocol facilitates information exchange between the physical PLC and the virtual platform, establishing effective linkage between the virtual system and the physical model to ensure coordination and consistency. Results demonstrate real-time synchronization and virtual sorting operations during joint real-virtual debugging. This digital twin design solution is poised to significantly enhance manufacturing efficiency, reduce initial hardware costs in factory design, and augment automation and intelligence in production.

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CNC machine based on embedded wireless and Internet of Things for workshop development

Cited by 22 publications

References 10 publications

A Condition and Fault Prevention Monitoring System for Industrial Computer Numerical Control Machinery

A Condition and Fault Prevention Monitoring System for Industrial Computer Numerical Control Machinery

Internet of Things Based Cutting Tool Status Monitoring in a Computer Numerical Control Milling Machine

Design of a material sorting digital twin system based on NX MCD

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