Industrial Internet of Things Solution for Real-Time Monitoring of the Additive Manufacturing Process

Author(s):  
Mahmoud Salama ◽  
Ahmed Elkaseer ◽  
Mohamed Saied ◽  
Hazem Ali ◽  
Steffen Scholz
Author(s):  
Rinki Sharma

Over the years, the industrial and manufacturing applications have become highly connected and automated. The incorporation of interconnected smart sensors, actuators, instruments, and other devices helps in establishing higher reliability and efficiency in the industrial and manufacturing process. This has given rise to the industrial internet of things (IIoT). Since IIoT components are scattered all over the network, real-time authenticity of the IIoT activities becomes essential. Blockchain technology is being considered by the researchers as the decentralized architecture to securely process the IIoT transactions. However, there are challenges involved in effective implementation of blockchain in IIoT. This chapter presents the importance of blockchain in IIoT paradigm, its role in different IIoT applications, challenges involved, possible solutions to overcome the challenges and open research issues.


2021 ◽  
pp. 331-344
Author(s):  
Luis Chuquimarca ◽  
Alba Asencio ◽  
Washington Torres ◽  
Samuel Bustos ◽  
José Sánchez ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3715
Author(s):  
Ioan Ungurean ◽  
Nicoleta Cristina Gaitan

In the design and development process of fog computing solutions for the Industrial Internet of Things (IIoT), we need to take into consideration the characteristics of the industrial environment that must be met. These include low latency, predictability, response time, and operating with hard real-time compiling. A starting point may be the reference fog architecture released by the OpenFog Consortium (now part of the Industrial Internet Consortium), but it has a high abstraction level and does not define how to integrate the fieldbuses and devices into the fog system. Therefore, the biggest challenges in the design and implementation of fog solutions for IIoT is the diversity of fieldbuses and devices used in the industrial field and ensuring compliance with all constraints in terms of real-time compiling, low latency, and predictability. Thus, this paper proposes a solution for a fog node that addresses these issues and integrates industrial fieldbuses. For practical implementation, there are specialized systems on chips (SoCs) that provides support for real-time communication with the fieldbuses through specialized coprocessors and peripherals. In this paper, we describe the implementation of the fog node on a system based on Xilinx Zynq UltraScale+ MPSoC ZU3EG A484 SoC.


Author(s):  
А.И. Сухотерин

В статье рассматривается проблемы управления ИБ на территориально-распределённых объектах защиты. Во избежание простоев и для сохранения безопасности на предприятии необходимо внедрение технологий, позволяющих обнаруживать и прогнозировать риски. Предлагается с помощью промышленного интернета-вещей обеспечить непрерывный интеллектуальный мониторинг ключевых показателей, что дает возможность определить проблему и принять необходимые меры для ее решения. Оперативный в режиме реального времени анализ поможет специалисту ИБ быстрее находить уязвимые места и предотвратить несанкционированные действия на предприятии. This article discusses the problems of is management on geographically distributed security objects. In order to avoid downtime and to maintain security at the enterprise, it is necessary to introduce technologies that allow detecting and predicting risks. It is proposed to use the industrial Internet of things to provide continuous intellectual monitoring of key indicators, which makes it possible to identify the problem and take the necessary measures to solve it. Real-time real-time analysis will help the IB specialist find vulnerabilities faster and prevent unauthorized actions in the enterprise .


2018 ◽  
Vol 188 ◽  
pp. 05006
Author(s):  
Christos Anagnostopoulos ◽  
Christos Alexakos ◽  
Apostolos Fournaris ◽  
Christos Koulamas ◽  
Athanasios Kalogeras

The manufacturing environment is characterized by increased complexity with different devices, systems and applications that need to interoperate, while residing at different layers of the classical industrial environment hierarchy. The introduction of the Industrial Internet of Things with increasingly smarter devices drives towards flatter hierarchies. This paper deals with an architecture for integration of IIoT devices in the manufacturing environment utilizing a Multi Agent System to this end. This extended architecture is utilised so as to perform failure detection of both IIoT devices and manufacturing resources, and react by altering the manufacturing process either automatically or semi-automatically.


Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8363
Author(s):  
Muhammad Zubair Islam ◽  
Shahzad ◽  
Rashid Ali ◽  
Amir Haider ◽  
Hyungseok Kim

With the inclusion of tactile Internet (TI) in the industrial sector, we are at the doorstep of the tactile Industrial Internet of Things (IIoT). This provides the ability for the human operator to control and manipulate remote industrial environments in real-time. The TI use cases in IIoT demand a communication network, including ultra-low latency, ultra-high reliability, availability, and security. Additionally, the lack of the tactile IIoT testbed has made it more severe to investigate and improve the quality of services (QoS) for tactile IIoT applications. In this work, we propose a virtual testbed called IoTactileSim, that offers implementation, investigation, and management for QoS provisioning in tactile IIoT services. IoTactileSim utilizes a network emulator Mininet and robotic simulator CoppeliaSim to perform real-time haptic teleoperations in virtual and physical environments. It provides the real-time monitoring of the implemented technology parametric values, network impairments (delay, packet loss), and data flow between operator (master domain) and teleoperator (slave domain). Finally, we investigate the results of two tactile IIoT environments to prove the potential of the proposed IoTactileSim testbed.


Author(s):  
С.Л. Добрынин ◽  
В.Л. Бурковский

Произведена классификация технологий аддитивного производства по базовому состоянию материала: жидкая основа, твердая основа, порошковая основа. Даны определения распространенных технологий в зависимости от базового состояния материала. Описаны технологические процессы изготовления прототипов и конечных изделий методами аддитивного производства, включающие в себя проектирование 3D-модели, преобразование форматов, нарезку 3D-модели на слои, формирование G-code и непосредственно печать. Рассмотрены технологии четвертой промышленной революции как инструмент повышения эффективности управления технологическими процессами аддитивного производства. Представлена модель модернизации технологического процесса аддитивного производства на основе технологий промышленного интернета вещей, аппаратной реализацией которого является одноплатный компьютер Raspberry Pi, программной реализацией является MTConnect - промышленный стандарт обмена данными станков с числовым программным управлением. Использование Raspberry Pi, подключенных к нему датчиков и программного обеспечения OctoPrint реализует контроль и удаленное управлениe технологическим оборудованием аддитивного производства (3D-принтером) в режиме реального времени. Представлено техническое устройство основных подсистем облачной платформы аддитивного производства. Архитектура предлагаемой системы состоит из четырех уровней: уровень адаптера доступа, уровень виртуализации ресурсов, уровень управления службами, уровень пользовательского инструментария We classified additive manufacturing technologies according to the basic state of the material: liquid base, solid base, powder base. We give definitions of common technologies depending on the basic state of the material. We describe the technological processes of manufacturing prototypes and final products by methods of additive manufacturing, including designing a 3D model, converting formats, slicing a 3D model into layers, forming a G-code and directly printing. We considered the technologies of the fourth industrial revolution as a tool for increasing the efficiency of control of technological processes of additive manufacturing. We present a model of modernization of the technological process of additive manufacturing based on technologies of the industrial internet of things, the hardware implementation of which is a single-board computer Raspberry Pi, the software implementation is MTConnect - an industrial standart for the exchange of data of machine tools with numerical control. Using Raspberry Pi, sensors connected to it and software OctoPrint implements control and remote management of additive manufacturing equipment (3D printer) in real time. We present the technical structure of the main subsystems of the cloud platform for additive manufacturing. The architecture of the proposed system consists of four levels: the access adapter level, the resource virtualization level, the service control level, and the user instrumentation level


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