What are the Challenges Companies Are Likely to Face During IIoT Adoption?

The Industrial Internet of Things is transforming industrial industries worldwide. Automation boosts productivity and encourages the development of more adaptable production procedures. Meanwhile, real-time predictive analysis and notifications help businesses save money on maintenance and failures.

Fremont, CA: The corporate benefits of IoT, such as higher intelligence, productivity, and asset management, are well understood. Industrial IoT is expected to deliver similar benefits to manufacturing, oil and gas, mining, and transportation industries.

Despite its benefits, IIoT presents distinct hurdles, so some businesses are hesitant to adopt it. They are concerned that legacy systems, pricing, data management, and connectivity will make it difficult to invest in IIoT.

Here's a closer look at the main IIoT challenges and how to address them.

Cost of Implementation

An IIoT system can be costly. Companies are concerned that ROI will be low since they believe IIoT is not a viable alternative for their sector. They need a method to see the entire journey, from beginning to end, to determine whether IIoT is worth deploying correctly.

In this instance, simply presenting the costs of an IIoT effort will not suffice. Instead, learn how to convert those expenditures into benefits the firm may reap, such as increased efficiency and productivity. Consider changing from proof of concept to evidence of value. This approach makes it easy to understand the business value and benefits of IIoT.

IIoT Data Management

According to IDC, IoT devices generate vast volumes of data, with 79.4 zettabytes expected by 2025. While that projection covers all IoT devices, IIoT equipment will generate substantial data. Many industrial firms are unprepared to handle it, either from a management or security standpoint. Another aspect to consider is data storage. Organizations must plan for reliable, temporary storage, such as edge computing if their setup cannot manage everything. As devices collect data, businesses must consider long-term internal or external storage.

Furthermore, many industrial organizations employ various databases and relational data storage systems. This method may clash with IIoT devices, which often create heterogeneous data stored in nonrelational databases. Businesses must connect relational and nonrelational databases into a single consolidated view to get the most out of ERP or material management systems, customer information, and IIoT data.

Most IIoT systems include or integrate automated data-gathering software, which speeds the process. Companies do not need to devote time or effort to data collection because the platforms handle it. The products also produce actionable insights from the data they collect and analyze. Complex computations predict future scenarios and simulate various options and repercussions, providing firms with simple and unambiguous recommendations on what to do.

IIoT Connectivity

Connectivity is critical because IIoT devices link to the enterprise network, whether directly or via the Internet. Furthermore, determining the optimum connection choice is problematic when dealing with industrial equipment in areas where IIoT devices are challenging to deploy. While 100% uptime is preferable, equipment maintenance schedules and internet interruptions make this aim unlikely. To that end, businesses must weigh several connectivity alternatives -- cellular, Wi-Fi, and direct -- to determine which works best. A cellular connection, for example, could support a device located far away yet requires a significant amount of infrequent bandwidth.