The IIoT is one of the hottest topics in digital transformation today. With Gartner predicting that 20 billion devices will be connected to IIoT Operational Networks (OT) by 2020, it's time for companies to start planning how they are going to deploy their IIoT strategy. In this journal entry, we're going to discuss five ways you can use AWS IoT services and tools to help your company successfully deploy an IIoT strategy. Adopting the Industrial Internet of Things (IIoT) can provide unique advantages to manufacturers and industries worldwide. However, some pitfalls come with this technology as well. Specifically: if something goes wrong in the digital world, it could have real-life consequences. For instance: an improper integration can damage real-world equipment and cause production issues.

Top 5 challenges to Industrial IoT adoption

High-Investment cost

Although IIoT adoption stands to cut expenses through better asset management, access to business intelligence, and productivity gains, it's difficult for organizations to justify the initial setup cost. They are not sure about what kind of ROI to expect, and they don't have enough experience when it comes to implementing connected systems. Microsoft's 2019 IoT Signals report says that 29% of organizations reported that lack of resources was one of the most significant factors for putting off IoT adoption.

Secure data storage and management

IIoT systems need to process a massive amount of data extremely fast to identify patterns in real-time. Also, IIoT technologies demand high-level security. As a result, organizations need to find a way to streamline data monitoring, management, and storage. A robust framework allows for faster response times to incoming threats. Hence, organizations must implement secure and short-term storage solutions like edge computing at the beginning. Soon, they will need a long-term solution like cloud or data centers for long-term storage purposes.

Using legacy and outdated systems

IIoT devices can be set up as an add-on module on legacy equipment and various other devices made by different companies. If not properly implemented, it makes it an uphill task for employees to monitor and control the end-to-end operation. Also, there's no set of standards for how organizations should handle data between various devices and machines.

Connectivity outages

IIoT solutions require constant, uninterrupted connectivity for real-time monitoring and alerting. However, a properly architected solution can enable computation at the edge, which allows for an IIoT solution to react to real-time situations without any cloud connectivity. Such solutions would need to be appropriately architected and tested.

Training IT to manage an IIoT Operational Network

Most industrial companies don't have the necessary IT resources or skills to build a cost-effective and fast IoT solution internally. Internal projects of this nature eventually run over deadlines and budgets.

Tips for successful Industrial IoT adoption

To ensure smooth adoption and overcome the industrial IoT challenges we talked about before:

• Hire the right experts: A properly architected solution with the right consulting partner, new employees, or you can upskill your team. Sometimes a combination of all of these options is the best way to go. IT experts who can implement proper security measures, data scientists to extract the right insights, and operations staff who know how to work with connected systems need to all part of the same team.
• Avoid downtime: Organizations will need to find a suitable vendor for meeting connectivity requirements to avoid downtime. That can cause significant problems when sensors are being utilized to detect hazards such as gas leaks or an outage that could be a life or death situation.
• Set proper controls: Ensure that the proper fail-safes have been put into place to help your manufacturing teams prevent safety issues, property damage, and incoming security threats.
• Integrate data properly: Organizations need to find a way to integrate the incoming IIoT data with their current architecture. For example, companies need to figure out how IIoT-generated data will fit current storage and data management systems.

Apart from following these tips, a well-architected solution needs a proper process for collecting and storing data from legacy devices with new technologies. All the technologies used need to work seamlessly together.

Organization prerequisites required to be considered fully IIoT-enabled

• Machinery that can collect and organize data using sensors and software.
• Robust cloud or edge computing systems that can keep and process data as it is received.
• Decisions about internal operations, supply chain optimization, asset management, etc., need advanced analytics systems that allow teams to extract and analyze data from connected systems. This data allows you to reward each employee with adequate knowledge of their performance.

IIoT transformation is a challenging task since most manufacturing, utilities, and logistics companies haven't taken the initiative to adopt the latest technologies.

IIoT adoption should not be thought of as a massive, company-changing maneuver; it should be looked at as a series of small projects or digital testbeds that can potentially increase your productivity, revenue and boost customer retention. IIoT integration comes with its own set of difficulties; there's a lot that can go wrong. Bringing the physical and digital world together can be tedious since you need to combine sensors and advanced analytics with legacy equipment built for another time.

The challenge of gathering, storing, and eventually putting data to good use cannot be overlooked. Hiring the right partner and team can help you develop an IIoT strategy designed around your organization's target objectives without making any mistakes.