6 Myths about IIoT Implementation Debunked
The Internet of Things (IoT) is ushering in the Fourth Industrial Revolution. While the need for digitalization is understood across-the-board, there are still many misconceptions that deter Industrial IoT (IIoT) implementation. Many organizations are postponing their IIoT initiatives or hesitate to move beyond pilots due to complexity and cost concerns.
Preparing for the worst isn’t necessarily bad, but you might be overcalculating the risks of IIoT and undermining its true value. Shying away from IIoT implementation based on false assumptions won’t help your bottom line and competitive edge. To help you build a more accurate picture, this week we debunk 6 common myths around IIoT deployments.
Myth #1: IIoT Always Means Cloud (Internet)-Connected
The cloud is that buzzword hovering around most IoT or IIoT discussions. Without doubt, the cloud has its perks and a profound position in the IIoT marketplace. It provides cost-effective, ubiquitous infrastructure for massive data storage and management. Cloud computing incorporating advanced machine learning algorithms can even identify trends in processes and equipment operations to anticipate and prevent future failures.
Having said that, the cloud is by no means a must in IIoT deployments. Despite their benefits, cloud solutions may not be a preferred option for many industrial companies. This is because a large number of legacy industrial systems have only limited security features, making them an easy target for cyber hackers when connected to the Internet. Besides cyber-security risks, data privacy, increased latency and unguaranteed service uptime are other top concerns of third-party managed clouds.
With numerous wireless vendors offering cloud-integrated solutions, it seems the cloud is an indispensable part of IIoT implementation. The truth is, the most versatile IIoT architecture renders this decision to end users, letting them employ a backend system that best suits their business requirements. Operational data can be relayed to an on-premises historian and data center or a cloud-based analytics platform – depending on users’ needs. IIoT is about increased control and visibility of industrial operations to augment operational efficiency, safety and sustainability. This should never come at the costs of security and data authority.
Myth #2: IIoT-Enabling Legacy Systems Is Highly Complex and Involves Production Downtime
Born during the Third Industrial Revolution, Programmable Logic Controllers (PLCs) are at the heart of industrial automation systems. Though excelling at real-time, localized tasks, these control hubs – designed in the early 2000s – aren’t meant to be connected to the outside world. The majority of older PLCs come with a plethora of proprietary serial protocols only intended for closed-loop control processes. Newer PLCs may come with Ethernet connection, but many hostile industrial environments are prohibitive for hardwiring.
Due to these communication challenges, manufacturers tend to think that IIoT enabling legacy PLCs and industrial systems is extremely arduous, if not impossible. It’s common to picture a daunting process with burdensome hardware changes, wiring and weeks of production shutdowns. The fact is, emerging plug-and-play connectivity is making IIoT implementation in brownfield plants much more a reality.
Such a solution can interface with legacy PLCs using automation-specific protocols to extract critical data points without any hardware modifications. Providing a robust radio link, it can then wirelessly transfer data to a central management system, eliminating any wiring requirements. As such, costly production downtime is simply not part of the process.
Myth #3: IIoT Is Only About Millisecond-Latency Automation Networks
Manufacturers often apply the conventional, automation-centric mindset to interpret IIoT and its potential value. Many envision digital factories as a new generation of automation facilities – fully equipped with next-gen manufacturing lines and robotic machinery that can communicate data in millisecond latency. While enhanced real-time automation is part of the story, it surely isn’t the single facet defining our next industrial revolution.
The central value around IIoT is unprecedented visibility into existing processes and equipment that empowers strategic decision-making. Often times, such visibility comes from granular sensor networks capturing asset, process and contextual data. Think of examples like workers’ wearables, pipeline sensors and environmental sensors. By timely notifying conditions that can disrupt operations and threaten worker’s health, remote monitoring networks are a core pillar of IIoT deployments to enhance plant safety and productivity.
Rather than high-bandwidth, time-sensitive communications, IIoT sensor networks mostly pertain to sending small bursts of telemetry data every few minutes or only when abnormalities are identified. Data sent too frequently, on the contrary, can be useless and burden the backend system. What really counts is network coverage, reliability and scalability alongside the ability to operate on independent batteries for years. Automation-oriented Ethernet infrastructure can’t keep up with these requirements.
Myth #4: IIoT Implementation Is Too Capital Intensive
The need for a new wireless communications architecture often induces the idea of significant upfront investment that deters IIoT adoption. However, as soon as you start looking at technological options available today, you’ll realize that building an IIoT infrastructure doesn’t necessarily cost a fortune. A new robotic system can cost hundreds of thousands of dollars upfront – not to mention the complex and expensive setup and maintenance process. In direct comparison, a wireless low-power IIoT sensor network can be deployed at a fraction of both capital and operational expenditures (CAPEX & OPEX).
Besides the much-reduced sensor cost today, new wireless technologies like Low Power Wide Area Networks (LPWAN) provide highly cost-effective connectivity for factory-wide sensor networks. With a scalable solution, you can also minimize expensive infrastructure (i.e. base stations) while addressing multiple applications and challenges simultaneously. This, in turn, streamlines complexity and accelerates Return-on-Investment (ROI).
Myth #5: IIoT Has Little Immediate Value
Even when an IIoT investment is comparatively affordable, manufacturers may still think it isn’t worth it. This is due to the common notion that IIoT has little immediate value and is just an optional add-on to daily operations. However, knowing that the total estimated cost of industrial downtime tops $50 billion annually, may change your mind.
By unlocking data from systems previously functioning in an encapsulated manner, IIoT helps manufacturers break down plant data silos. Enhanced asset and operational transparency greatly facilitate troubleshooting and maintenance activities while eliminating manual tasks. This will have an immediate impact on cost savings and overall equipment effectiveness by reducing machinery and production downtime.
Myth #6: IIoT Will Eventually Replace People
IIoT reflects a paradigm shift in industrial operations and the required expertise. Certain manual tasks will be automated for enhanced productivity, but this doesn’t mean the need for manpower will fade away. On the contrary, a digital factory is only as smart as the people who operate it. To secure and translate Big Data into business intelligence, new job domains like data scientists and security engineers will be critical. Existing jobs like machine operators will continue to evolve with new skill sets. Human intelligence is the brain behind IIoT implementation and no machine can be as flexible as humans themselves.
It’s also important to note that IIoT frees worker from repetitive, monotonous tasks to focus on more rewarding, higher-value ones. Likewise, one of its ultimate goals is to create a safer and healthier work environment for employees. As such, rather than being viewed as an employment threat, IIoT should be seen as a means towards future worker-centric smart plants.
As with any previous industrial revolutions, IIoT implementation does not come without challenges. However, make sure the misconceptions aren’t diverting you from the reality. Accurately assessing how IIoT can tackle your business challenges and measure it against potential costs will be key to a successful deployment.
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