Anyone who controls their home heating from their smartphone will know the Internet of Things (IoT) isn’t a new concept. But a combination of technology advances means the IoT – and especially the Industrial IoT (IIoT) — has finally come of age. The wide availability of low-cost, cloud-based data processing, sharper artificial intelligence, and faster wireless communication have turned the IIoT into a central pillar of a growing number of manufacturers’ digitalisation strategies. In 2019 alone the IT research company, IDC, expects global discrete manufacturing and process manufacturing to spend $119 billion and $78 billion respectively on IoT solutions.
Building an IIoT on Legacy Assets
Growth in IIoT usage is occurring across all industrial sectors. That doesn’t mean every manufacturer is taking the same approach to building out an IIoT – or that they need to. But there is a common thread between every successful IIoT system, and that’s the efficiency and speed with which it captures, analyses and deploys essential data. In particular, manufacturers are harnessing the IIoT to gain rapid insight into machine performance so they can prevent downtime and better pre-empt and manage maintenance. And it’s a trend that is set to grow as manufacturers turn to remote monitoring to support greater automation.
Measuring systems are high on the list of machines to track because of their impact on productivity. But sharing data from them isn’t always easy. Even today the bulk of data about the operational status of measuring machines is trapped in silos and often accessible by only one person, the machine operator. That’s why Hexagon’s Manufacturing Intelligence division is developing solutions to unlock, analyse and share data from a full range of new and legacy measurement systems across an IIoT, including those from our competitors.
Remote Monitoring and Maintenance
Once manufacturers have access to clean, real-time data about the performance of measurement systems they can put it to use in multiple ways. Not only are shop floor managers able to see at a glance where and why a machine has stopped working and determine how to fix it, machine learning software makes it simpler to predict maintenance needs. Engineers can also draw on data to perform remote diagnostics and repairs, using augmented reality glasses to visualise the part they are repairing. And because maintenance decisions are founded on data rather than intuition or observation, they are precise and reliable.
To find out more contact your local Hexagon representative.
