The Internet of Things (IoT) has tremendous potential to change the way plant managers and machine builders do their jobs while increasing efficiency and productivity, according to industry experts. By 2030, some estimate the Industrial Internet of Things (IIoT) could be worth a jaw-dropping $7.1 trillion to the U.S. economy.
Yet, despite the hype, developing this potential has been frustratingly slow. Rolling out the IoT infrastructure is a huge undertaking that only large companies with mature, established business processes seem eager to tackle. Many are wary of strange new terms like “cloud-based computing,” “gateways,” and the myriad Ethernet-based protocols. Little wonder that a recent survey by Forrester Research found 23% of global enterprise respondents use the IoT, compared to only 14% of respondents from small and medium-size company.
Many people developing IoT technology focus on enterprise-level platforms that provide top-down approaches to deploying IoT. Even for companies that have made the “switch,” an IoT application might only capture a fraction of the machine data available, not really giving the whole picture. That makes it difficult to create reliable and repeatable predictive maintenance and performance optimization algorithms. Even worse, some IoT approaches may capture too much data, making it tough to find the meaningful information. Successful IoT applications must be based on knowing what data is important to stakeholders and how they will use it.