This manufacturing revolution is poised to enhance productivity, transform economics, foster industrial growth, and alter the global workforce—ultimately changing the competitiveness of global economies and regions. Industry 4.0 is characterized by, among others, 1) an increased level of automation at a grander scale than in the third industrial revolution, 2) the merging of the physical and digital worlds through cyber-physical systems, enabled by Industrial IoT, 3) a shift from a central industrial control system to a more distributed one where smart products define and control the processes, 4) use of digital twins and closed-loop data models and control systems, and 5) increased personalization/customization of products.
These new cyber-physical systems form the bedrock of Industry 4.0 (e.g., “smart machines”). The smart component is a result of the embedded software in these machines, which provides an internet address to connect and be addressed via IoT (the Internet of Things). Furthermore, the use of modern control systems, Artificial Intelligence (AI) and Machine Learning (ML) technologies enables new production management, value creation, and real-time optimization. Cyber-physical systems create the capabilities needed for smart factories of today. These smart capabilities permeate further than manufacturing itself to impact smart supply-chain management, smart marketing, financial control and now even environmental compliance.
Industrial Internet of Things (IIoT) and Industry 4.0
IIoT is at the heart of Industry 4.0. Industrial IoT is a subset of the Internet of Things, where various smart sensors, radio frequency identification (RFID) tags, software and electronics are infused within industrial machines and systems to collect real-time data about their condition and performance. Although IIoT is one of the 12 breakthrough technologies enabling Industry 4.0, it is by far the most prominent one.
IIoT, in turn, is fueled by advancements in edge computing technology. Edge computing can be loosely defined as the technology that enables deployment of data-handling, operations and monitoring/analytics at the source of the equipment without dependence on a central network system. This distributed computing process optimizes the cyber-physical system, IIoT devices, and applications by bringing computing capabilities closer to the edge of the network (at the site of the creation of data itself), which generally refers to the area where the device first communicates with the internet. For IIoT devices, such as a vibration monitor, the network edge will be the processor within the vibration sensor assembly, while for non-connected equipment, the network edge will be within the smart edge device attached to the equipment.
How edge computing functions for industrial IIoT
The features and function of edge computing are what deliver the diverse benefits associated with it and makes it attractive to industrial/manufacturing organizations. Industrial edge computing’s primary benefit is the ability to bring low latency computing to manufacturing facilities. These attempts have been successful and beneficial in elevating the use of edge computing in IIoT devices. Broadly, the benefits of augmenting IIoT can be described as:
- Driving automation to the last mile – IIoT can enable a paradigm shift in automating industrial processes and operations through the complete integration of edge computing in the equipment, devices, and processes that drive operations. However, inadvertently, situations arise where IIoT devices produce large and unwieldy data sets, sending this captured data to centralized systems for analysis and waiting for control actions to be generated, which slows down automation. Edge computing can be integrated to eliminate communication and processing time lags to drive real-time automation. This paves the way for an autonomous lights-out factory to be created in the future, wherein human interaction with processes is negligible.
- Automating maintenance procedures – A fundamental tenant within Industry 4.0 is the need to introduce predictive maintenance to factory floors. This has created an industry boom of sorts in the industrial sector, as every equipment manufacturer is introducing IIoT-enabled capital goods that can be remotely monitored and repaired without human intervention. This new operational modality has bred several innovative business models that are outcome/solution-based and often predicated on asset leases instead of capital purchases by customers. IIoT serves as a fundamental building block to enable this new operational paradigm, providing unprecedented access to equipment manufacturers to their equipment deployed at customer sites. As the smart equipment proliferates, the reliability of the IIoT devices and network becomes vital for sustained operations. Edge computing can ensure the maintenance procedure of IIoT devices is completely automated, given the device knows when to seek replacement, recharging, repair, etc. Edge can enable several corrective actions on the IIoT equipment, such as running diagnostic checks, reporting to a charging port, raising maintenance work orders and initiating replacement component purchases. As IIoT networks get more congested, edge monitoring software will alleviate the pain of the management and upkeep of these IIoT points, leaving equipment manufacturers and customers focused on analytics to improve overall equipment and process performance.
- Enhancing IT security – The growth of IIoT devices on the shop floor has created its own challenges. Industrial customers are now dealing with security loopholes created by the influx of several tiny IIoT network points that are vulnerable due to the lack of inbuilt security features. This has created several weak links in the IT ecosystem and multiple access points for attackers to exploit. Applying edge computing for Industrial IoT is one important way to tackle these security challenges, owing to the concept behind the edge’s computing process. Fundamentally, edge computing can reduce the points of failures (or access points) that can be exploited by intruders. Edge computing provides necessary isolation to make the network more fault-tolerant, self-healing, and resilient. Moreover, the independence edge computing enables can also be extended to legacy equipment; it creates an ecosystem of data management, analytics and local control. This means IIoT and legacy equipment will capture, analyze, and discard temporary data while sending only key/permanent data to a centralized server, thus reducing overall bandwidth costs, improve security and make networks more fault tolerant.
The influx of IIoT devices and equipment makes the introduction of edge computing within industrial facilities a much easier task than integrating it within brownfield shop floors. For most industrial users, IIoT is generally the first instance of implementing edge computing and gaining benefits from its advantages. Both IIoT and edge computing are evolving fast and addressing their gaps. Edge is dealing with its standardization, infrastructure, security and framework issues, which are likely to be solved over the next few years. As the edge ecosystem matures, IIoT adoption will benefit immensely.
