IIoT in Manufacturing: Overcoming Common Challenges

Data is essential in virtually every aspect of modern life. A goalkeeper can’t improve if they don’t know their save percentage. A radio station won’t know the best ads to play if they don’t know who listens to their programs most often. A baker’s treats won’t taste very good if they don’t know the precise measurements of each ingredient. While it’s certainly possible to improve without the help of facts and figures, it’s much more difficult when blindly attempting those advancements. The same is true for manufacturing. We may eventually find the reason behind common bottlenecks or figure out a way to speed up the production process without sacrificing quality, but those efforts will take much longer (or may never occur) without data. The implementation of IIoT in manufacturing does just that — creates valuable, actionable data that can be tracked, managed, reported, organized, and much more. Today, we’re covering a few common challenges that come along with the adoption of IIoT in a manufacturing environment and how they can be overcome.

What is IIoT?

Before diving into the finer points of IIoT implementation, it’s first necessary to understand what it is. To keep it brief, IIoT stands for the industrial internet of things and is also frequently referred to as industrial IoT. At its core, manufacturing IIoT connects a wide range of systems, hardware, and devices to one another. It gathers data from each of these elements, puts that data into the cloud, and allows users to track and manage what’s going on in their plant. By collecting this data and putting it into a format that can be interpreted and reported on, manufacturers are able to more easily find things like factory bottlenecks, the best areas for optimization, machine errors, spots where production quality can be improved, and beyond. Learn more about industrial IoT in our first digitalization blog post at this link.

The Primary Challenges of IIoT Implementation

The industrial internet of things offers incredible potential to the manufacturers who utilize it. But like anything that offers the possibility of outstanding results, there are a few aspects that can present a challenge to operators and stakeholders. Here’s a breakdown of a few of the most common, and we’ll go over how to overcome them in the next section.

• Data Fragmentation: When working with both new tech and legacy systems, data often ends up siloed and incompatible with other information. To fully embrace IIoT, it’s important to integrate all systems.
• Insufficient Infrastructure: Industrial IoT needs a number of important elements – network connectivity, storage for data, and full processing capability. Oftentimes, manufacturers just beginning the implementation process lack all or some of these.
• Understanding Appropriate Solutions: There is a diverse range of IIoT solutions on the market. Knowing which is ideal for a unique company can be difficult.
• Data Privacy and Security: Knowing how to train manufacturers about IIoT security is of utmost importance. The data collected is usually of a sensitive nature and operators must know how to address any vulnerabilities in order to protect that data.
• Proving ROI: Industrial IoT devices and the related infrastructure often comes with some sticker shock. Proving to investors and key stakeholders that it will provide exceptional ROI can feel like a challenge, meaning that manufacturers need to develop clear business cases that show expected ROI and long-term value.
• Long-Term Scalability: Any smart business decisions will consider future growth. This means companies should select IIoT solutions and technologies that allow them to adapt to any changes in their industry, as well as possible updates to regulations and standards.
• The Workforce: Specialized skills are a necessary aspect of industrial IoT adoption. Training team members or acquiring new talent may present a significant problem. Additionally, with changes in processes and job roles or responsibilities, it’s possible that there will be internal resistance that needs to be shifted toward cultural acceptance of new technologies.