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Industrial Internet of Things
Published in Bhawana Rudra, Anshul Verma, Shekhar Verma, Bhanu Shrestha, Futuristic Research Trends and Applications of Internet of Things, 2022
Industrial Internet of Things (IIoT) is a network of sensors, intelligent objects, architecture, platforms, and applications that compromise various technologies and enable them to provide a communication environment. The main goal of Industrial IoT applications is to improve the availability of processors, adding intelligence to machines, affordability and enables sensors and other networking devices to communicate efficiently with real-time information. Industrial IoT applications have become very popular among industries and academia. Several sectors use the Industrial Internet of Things. Low-cost connected devices [1] play a vital role in IIoT applications. IIoT services are classified into two different categories as short-range and long-range connectives. Industrial IoT is used by various industries like automotive, agriculture, and healthcare. Predictive maintenance is one of the main advantages of using IIoT in automotive industries.
Industry 4.0
Published in A. Kanthimathinathan, Manufacturing Excellence in Spinning Mills, 2022
Manufacturers historically isolated their factories, plants, sites, and facilities from data connections. Today, significant opportunities are available to leverage the benefits of digital networks and enable extraction of data for analysis and ultimately improve “plant performance.” In a nutshell, the benefits of IIoT are as follows:Improving the manufacturing efficiencyImproving the machinery utilizationImproving the productivityEnhancing employee safety in the industriesBetter service to customersInnovative process and product development
Internet of Things
Published in Matthew N.O. Sadiku, Emerging Internet-Based Technologies, 2019
The term “industrial Internet” is strongly pushed by General Electric. Some see this as the biggest and most important part of the overall IoT picture. In fact, there are two subsets of IoT: the Consumer IoT and the Industrial IoT. The Consumer IoT naturally evolves from human-operated computers to automated things that surround humans. It consists of smart home devices, wearable computers, cameras, and networked appliances. The IIoT refers to a large number of interconnected industrial systems that are communicating, sharing data, and improving industrial performance to benefit the society. It includes networked smart power grid, manufacturing, medical and transportation infrastructures. It requires high reliability, lower power usage, and timely exchange of information [13]. It is helping to improve productivity, enhance worker safety, and reduce operating costs. A typical IIoT is shown in Figure 1.4 [14].
Integration of SCADA and Industrial IoT: Opportunities and Challenges
Published in IETE Technical Review, 2023
A. Nechibvute, H. D. Mafukidze
The application of the Internet of Things (IoT) to industry, called Industrial IoT (IIoT), is an integral part of the industry 4.0 paradigm that seeks to digitize and connect entire industrial plants and processes. Industry 4.0’s vision seeks to achieve this primarily through the systematic integration of traditional industrial capabilities with internet technology. Thus, IIoT involves the inter-networking of intelligent machines, computing devices, and humans to enable smart industrial operations. Operational technology (OT) domain is typically involved with field-based devices connected to a process control system monitoring and controlling those devices, and the SCADA system is the most popular example. Communications in such OT frameworks are device-to-device, or device-to-computer, with relatively little human interaction. On the other hand, Information Technology (IT) domain involves office information systems employed to conduct commercial/business-type transactions such as cost and tax accounting, billing and revenue collection, asset tracking and depreciation, human resource records and time-keeping, and customer records. The advent of the IIoT is radically changing this perspective and progressively these two previously distinct domains started to share common technologies and approaches [22] (see Figure 3).
Integration of Industry 4.0 technologies into Lean Six Sigma DMAIC: a systematic review
Published in Production Planning & Control, 2023
Tanawadee Pongboonchai-Empl, Jiju Antony, Jose Arturo Garza-Reyes, Tim Komkowski, Guilherme Luz Tortorella
Internet of Things (IoT) or, in the context of I4.0, Industrial Internet of Things (IIoT), refers to interconnected physical industrial assets, such as machine sensors, technical equipment, and computer hardware, but also digital models of processes, products, and plants (Ghobakhloo 2018). IoT technology enables real-time data collection for improved process control and performance measurement. In the IoT architectures presented, data is automatically recorded through an interconnected network of sensors or smart devices (Arcidiacono and Pieroni 2018; Chiarini and Kumar 2021; Fernandez et al. 2021). Intelligent systems analyze the data using machine learning algorithms and provide insights and guidance for taking appropriate measures based on predicted results. The authors also proposed how IoT technologies can support LSS DMAIC phases and supported their claims through case studies. In this context, Arcidiacono and Pieroni (2018) introduced the term ‘Lean Six Sigma 4.0’ (LSS 4.0) to represent their novel concept. Thus far, there is no officially agreed definition of LSS4.0, but academics and practitioners might argue that there is more to LSS4.0 than the integration of LSS with IoT or a few I4.0 technologies.
The role of artificial intelligence in shaping the future of Agile fashion industry
Published in Production Planning & Control, 2022
Mujahid Mohiuddin Babu, Shahriar Akter, Mahfuzur Rahman, Md Morsaline Billah, Dieu Hack-Polay
Current industry 4.0 manufacturing operations are converted into smart factories, which integrate various advanced technologies, e.g. Industrial Internet of Things (IIoT) and Big Data. This is with the view to optimize performance, quality, controllability and transparency of manufacturing processes (Nguyen et al. 2019). To become a smart manufacturing unit, a factory undergoes a long-term and complex process, which requires a deep understanding of advanced technologies. IIoT, Big data and AI are integrated to engender smart manufacturing. IIoT is used in industrial manufacturing processes where large-scale data are collected and analysed through sensors and other modern technologies such as cyber-physical systems, cloud computing, mobile technologies, and radio frequency identification (RFID). These are embedded in all the components of a manufacturing process. AI provides advanced computing technologies such as machine learning, neural networking, and cognitive technology to process massive, complex and heterogeneous Big Data and eventually revolutionize the industrial manufacturing process.