Predictive data and the use of analytics are changing the UK’s manufacturing landscape, writes Dr David Bott, principal fellow at WMG, part of the High Value Manufacturing Catapult.
It is very common these days to talk about the digital revolution – being applied to most human activities – but although it is having profound impacts, it is currently more an evolution of things people have already done. However, the availability of more powerful computers, bigger data storage and faster communications mean that going forward this evolution is going to start going a lot faster than we are used to.
In manufacturing, data can support the selection of materials and processes, optimise the process-material combination, and accelerate products to market. It can bring flexibility by making sure that the right components and sub-assemblies are there when needed. It can understand how customers use products, providing, for example, valuable feedback on service support.
The desire to control individual machines (or reactors in the process side of manufacturing) has been around for a long time. Initially measurements were simple and infrequent, but as the measurement and computing capability grew, so did the type and amount of data we can collect and use to control machines. This led, in turn, to the ability to virtually model existing, or even new, machines and optimise them “offline”.
Very few factories comprise one machine, and it is important to manage the flow of materials from one machine to another. The enhanced computing and communication capability enables the monitoring, control and modelling of assembly lines for optimal productivity.
The next step in this evolution was to apply this newfound insight back up the supply chain. Factories often buy in components and sub-assemblies made in other factories. Given that it was possible to use data to optimise a factory, it was simply just a bigger task to optimise a supply chain. There are challenges in that the suppliers are separate companies with their own drivers and restrictions, and care needs to be taken sharing commercially sensitive data.
More recent (although the driver was always there) is the need to find out what your customers do with your products, and how you can turn that insight into the information necessary to produce better products in the future. This is behind the rise of the “smart” product. Used properly, this approach enables managed service and maintenance in use – with the consequent minimum disruption of use – which makes the customer happy, and an understanding of what your customers actually want.
All this data gives insight into what everyone along the supply chain wants and can ask questions of the way products and services are delivered. It has enabled the restructuring of many types of transactions, where it is simply the need, or ability to supply, that is traded and the physical side of the business is carried out at a lower level. This ability has caused the disintermediation of the music and book industries, is changing the way we find taxis and hotel rooms, and even enabling people to make money from the parking space in front of their house.
However, there are risks. Understanding the security requirements of personal, manufacturing and usage data will be critical to the design of future digital systems. Those risks can be caused by the failure of humans to be aware of the importance of security, or by those who recognise that disrupting these data flows can be a source of income. This in itself appears to be a burgeoning industry.
Ultimately, there are profound changes happening in the manufacturing industry. The only question is how long it will take individual companies and what route through the forest of opportunities and acronyms they will take.