From raw data to actionable knowledge
The change will in all likelihood be less dramatic than some people think. Sure, the roles of people will change, for example when younger employees enter the workforce who rely much more on technology, data and modern system support.
The key issue is to make decision-making easy and transform the huge amounts of data generated by production systems and stored in data lakes into actionable knowledge – and communicate that knowledge to employees when they need it.
How will the mill change as a workplace?
The trend towards higher automation will continue. The peak is not yet reached. Automatic warehouses, wrapping lines, in future most likely also Artificial Intelligence -run production machinery will develop further.
Even when companies are focusing on simplification in their transformation projects, it will happen through an increasing number of technical interfaces in the background. These include the interfaces between machines, between machines and warehouses – in other words, the industrial internet.
The workforce, at least in Europe, will include fewer people. With ageing population, there will inevitably be a natural loss in employees with decades of hands-on experience. In Asian countries with their different demographics, this phenomenon might not be as pronounced. On the other hand, new Asian players are emerging who are looking to ramp up production quickly relying on automated processes.
Increased complexity will grow into production processes and products. With smaller batches, more customised products and shorter runs, agility must be built into production.
Impact on the people
The nature of mill work will evolve from executing specific tasks to monitoring. Even if machines are doing the standard work, humans are still needed to monitor the process.
There will be a transformation from many specialists to only a few generalists. This sounds like a contradiction in today’s world where we are used to thinking in terms of niche specialists. However, if there are fewer people in a mill doing ‘only’ monitoring, they are responsible for a wider area. It is impossible for them to have in-depth special know-how on all aspects of production.
Doing standard work will gravitate towards handling exceptions. Machines do the standard work automatically, but when an exception occurs, human intervention is needed.
New demands for IT systems
When the people side of manufacturing is changing, it will place a whole new set of demands on the IT systems in the background.
Monitoring requires good decision-making and alerting systems. Generalists need decision support, a knowledge base and scenario engines to to see what happens if… Huge amounts of computing power, analytics and machine learning are needed to achieve this. Similarly, integration between systems and ways to communicate knowledge to where, by whom and when it is needed requires real-time interactive capacity. Things such as Augmented Reality and vast scenario databases come into play.
Handling exceptions with high complexity requires good collaboration between colleagues and specialists who may reside in geographically dispersed locations anywhere in the world. The requirements for this include reliable communication channels with minimum latency, as well as uncompromising data security and integrity solutions.
Don’t forget to register for the Winning in the industry – IT’s about people and data event in May!
Managing Director Tieto Germany & Head of Production Excellence, Tieto