Some analysts estimate that by the year 2020, the number of IoT devices will reach 30 billion, and that number will more than double by the year 2025. It’s not just personal devices; manufacturing is experiencing one of the highest and most rapid adoptions of IoT technology.
Manufacturers leverage powerful, real-time data from the IoT to increase uptime, perform preventative maintenance, enhance productivity, improve mobile accessibility, and a host of other benefits. It’s clear that manufacturers need to embrace the IoT if they want to succeed in highly competitive markets. Implementing the technology, however, comes with some challenges.
1. Hardware Compatibility and Data Connectivity
The longer your manufacturing facility has been in operation, the more likely it is to have legacy systems in place or older equipment that may not integrate easily with IoT technology. Unlike legacy devices, newer machines are compatible with Cloud-based systems. In order to extract useful data to improve efficiencies, uptime, and productivity, devices must be able to communicate with systems and software.
Sensors can be added to machines to aid in this type of two-way interaction, and enterprises need to identify which equipment and systems need to be integrated based on their desired business goals. When researching IoT solutions, examine how each will operate with existing systems, and consider future needs and growth goals to ensure the solution you choose can scale with your business.
2. Securing Data
One of the greatest concerns among manufacturers is the risk of a cyber attack or data breach. Ransomware can incapacitate a facility for hours or days until demands from a hacker are met or backup systems are restored. Additional concerns include the loss of intellectual property, trade secrets, and other proprietary information.
To mitigate the risks, enterprises must ensure proper governance of systems by utilizing a provider that will implement secure configurations with authorized-user-only access to sensitive information. As use of the cloud for data storage becomes more prevalent, establishing data-related security policies and user protocols during the IoT integration planning phase is critical.
3. Inaccurate Analytics
When software is unable to record data or handle deviations in runtime or incidents on the plant floor, it results in incorrect documentation. Decisions based on inaccurate data inevitably lead to less-than-optimal results and can negatively affect outcomes.
Vast amounts of data are generated through IoT-enabled devices, and parsing through it all and knowing which data is of value is one of the only ways to achieve actionable insights. Enterprises must also consider that, as the IoT becomes the norm, the amounts of data generated will compound exponentially. Not all platforms are currently capable of handling large data sets, let alone the extensive data that will one day be generated. When developing your IoT architecture, identify the data-processing power you need today with the capability of adding real-time or predictive analytics in the future.
4. Finding the Right Provider
The best and most expensive system in the world can be rendered useless if you don’t have the right team on board to successfully install, implement, and service it. Too many stories have been told about manufacturers that have made major capital purchases of IoT technology only to have it fail to bring ROI.
It’s critical to work with a provider that is not only familiar with IoT technology and integration considerations, but that is also familiar with the manufacturing industry and its various sectors. When you choose to go all-in with IoT adoption, it’s best to work with an outside expert from the start to ensure all the implementation phases — from planning to execution to service — provide the results and ROI you’re looking for.
Reach out to the IoT experts at Wipfli to discuss your organization’s challenges and how technology can help overcome them, and know that your IoT adoption will go as smoothly as possible.