The difference between progress and potential is subtle, yet significant. ‘Progress’ is about moving forwards or developing towards a more advanced state. Across manufacturing industries, progress is plain to see. In the automotive industry, the horseless carriages of the late 1800s have developed into the mass-produced yet highly-customised vehicles of today. Born less than 100 years ago, the electronics industry has progressed beyond belief, in turn generating progress in other industries where both manufacturing and product operations rely on digital technology.
‘Potential’ is more about future prospects, based on the development of current qualities. This makes potential harder to define at an industry level. What could a car look like in 20, 30, 40 years? Will we still need planes, or will the sci-fi staples of flying cars unite the two industries? Maybe the automotive and aerospace industries as we know them will become obsolete thanks to our teleportation devices!
With limitless potential, anything is possible; however, when we think about potential as ‘the state you are progressing towards’, the possibilities are more tangible. If a manufacturer produces a certain number of parts per day with certain productivity-limiting factors in play, then removing these factors might be enough to increase output to what might be considered the factory’s ‘full potential’. Undoubtedly progresses can be made that remove at least some of the barriers to productivity and move manufacturers closer to realising their potential.
What if information gathered at any phase of the product or component’s development could be used to inform every other phase of the product lifecycle?
Hexagon sees information as a key driver of progress and develops information technologies that provide insight and analytics through data to enable companies to fulfil their potential. In recent years, the company has developed several new touchpoints within the manufacturing process (each with development potential of its own of course!). Where previously Hexagon Manufacturing Intelligence’s information technologies addressed metrology hardware for data capture in the post-production, quality assurance phase of manufacturing, our skillset now ranges from design, costing, simulation and engineering, through to production phase CAD/CAM and statistical process control solutions, as well as metrology software.
Although these technologies are related, few companies have tried to assemble such a broad range of manufacturing information technologies under one roof. But we see potential in leveraging such technologies to bring the traditionally separate phases of manufacturing closer together. This is the potential power of data.
Every manufacturer captures data daily, but how many businesses have time to truly interrogate this data and implement learnings from it? Everyone knows they should – but there are so many obstacles that it almost seems unachievable. Data is typically captured in disparate systems and stored in different, often incompatible file formats. As a result, data that costs money to record is sometimes accessed only in isolation when looking back at a fault –even then, it may not present a complete picture.
But what if every piece of information recorded in the manufacturing process, from concept through to reality, could be integrated into a single system and interrogated as a complete set? What if information gathered at any phase of the product or component’s development could be used to inform every other phase of the product lifecycle? The potential of connecting data could have a huge impact on the way manufacturers design products and processes in future. If data could be constructively used to inform decision making, both upstream and downstream, then the resulting series of feedback loops enable continuous learning and improvement to become embedded in the process.
This learning could even transcend the factory and take service life data back into the iterative development of parts. Take the example of a compressor blade – a critical part of an aircraft engine. Its designer has carefully considered how the profile can be optimised to generate the pressure and temperature required of the inlet air. Materials have been selected. Its production has been simulated, a manufacturing process designed and implemented. The blade has been made and its quality checked, then it goes into service. What potential might there be in taking data from its service life – maintenance records, behaviour in different environmental conditions, failure analysis – back to the design team? What if the simulation could be compared directly to the real-world behaviours? Maybe next time the factory could give the maintenance team a more accurate estimate of the service life of that blade, enabling predictive rather than reactive maintenance. But it all relies on data flowing seamlessly between departments on demand – a joined up digital thread that breaks down traditional operating silos.
Such connectivity could challenge the shape of factories as we know them. Instead of production lines, factories of the future could be more modular in nature. If parts could begin to carry their own data intelligently, we might see factories with production islands, allowing individually optimised processes for each one. Perhaps the factory of the future is an interconnected ‘ecosystem’ of independent, but inherently connected production phases that rely on each other’s data to optimise and make efficiency improvements. And then, manufacturers’ estimation of their own potential might be revised for the better.
It’s all about making your vision of your potential a reality – which is what we are all about. How do we do it? By shaping smart change.
