In late 2015, the business began investigating the Internet of Things (IoT) “beyond the buzzword”, in terms of drawing up plans which had the real potential to bring about transformative change.
In light of reports that many businesses were (and still are) struggling to get real value from investment into Big Data-driven analytics and technology, a decision was made to invest initially in small-scale, short-term strategies where value could be seen quickly.
The plan, as instigated by IoT lead Justin Hester, was that these would work as proof to gain buy-in across the company for further, larger scale and more challenging projects.
“The promise of IoT is well understood in the industry,” Hester told me. “This idea that we can finally harness the data coming in from all of these different sources, whether they are machines, humans, parts – but I think the real challenge is the next step – how do I execute? That’s the challenge.”
Hester and the team at Hirotec’s answer was to start small. The thinking was that the reason behind the failure of many businesses to get to grips with implementing IoT analytics was an over-eagerness to “boil the whole ocean.”
“They say ‘we see tons of benefit from Big Data and we want to bring all of this in and analyse it’ and that’s true and sounds great – but data doesn’t collect itself and it doesn’t analyze itself.
“So, we recognized the need to create short sprint activities which were projects which would help us solve one of our internal challenges and also be scalable so we could implement them again but on a larger scale.”
Gathering real-time measurement
One of the early projects initially involved connecting and monitoring computer-controlled cutting devices at Hirotec’s North American tool building facility. Here, ultra-precise blades cut through metal and plastic and minor fluctuations in the performance or reliability of machines can have large knock-on effects.
The abundance of legacy technology in the manufacturing world was an initial problem – unlike in computing, manufacturing machines are expected to remain productive until they die of exhaustion, rather than being replaced with new models every two or three years when they start to get a little creaky.
“We had these machines on the shop floor and there was one from 1970, with no connective technology, and one from 1990 which had this really cool new tech that could send a message to your beeper.”
On – 21 Apr, 2017 By Bernard Marr