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IIoT Edge Network and Spectrum Scarcity Issue
Published in Sudan Jha, Usman Tariq, Gyanendra Prasad Joshi, Vijender Kumar Solanki, Industrial Internet of Things, 2022
Gyanendra Prasad Joshi, Sudan Jha
Although there is some overlap between IIoT and IoT, the consumer IoT, or just called IoT, is the network of physical objects that are equipped with sensing or tracking technologies, and software to connect and share data with other devices and systems. Some examples of IoT devices are smartwatches, smart home speakers, light bulbs, door locks, smart white goods, and smart brown goods. The IIoT refers to interconnected sensors, machines, tools, instruments, process, and other industrial devices networked together with industrial applications, with the major objective to achieve high operational efficiency, increased productivity, and better management of industrial assets and processes through product customization, intelligent monitoring applications for production floor shops and machine health, and predictive and preventive maintenance of industrial equipment (Khan et al., 2020). The IIoT connects people, products, and processes to power digital transformation in industries. The basic objective of both IoT and IIoT is the same, i.e., to use sensors and automation to make processes more efficient. However, the consumer IoT is about making life easier and IIoT is for an intelligent and efficient industrial process. Boyes et al. discussed the definitions of IoT and IIoT and gaps in the current literature and understanding of IIoT (Boyes et al., 2018).
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).
Evaluating readiness degree for Industrial Internet of Things adoption in manufacturing enterprises under interval-valued Pythagorean fuzzy approach
Published in Production & Manufacturing Research, 2022
The primary objective of IIoT adoption is to achieve increased productivity, operational efficiency, and enhanced management of the manufacturing process and assets through product customization, intelligent inspection in the production shop floors, and predictive and preventive maintenance of production equipment. There are several technologies that are embedded under the IIoT umbrella, including cloud computing, machine-to-machine (M2M) communication, machine learning, artificial intelligence (AI), and distributed computing. IIoT results in not only a shift in technical manufacturing but also broader corporate impact and opportunities (Kiel et al., 2017). Implementing IIoT in supply chains and operations provides tangible commercial benefits such as low risk and cost, increased transparency, visibility, flexibility, operational flow, and virtualization (Khan & Salah, 2018; Trappey et al., 2017). Manufacturing enterprises have realized the impacts of IIoT in five key perspectives such as design and innovation, asset utilization and revenue planning, supply chain and logistics design, resource productivity optimization, and extension of stakeholder experience. Notwithstanding, the IIoT adoption remains costly, complex, and high risk for manufacturers. Therefore, the assessment of manufacturers’ readiness prior to IIoT adoption has become very important.
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.