Jun 6, 2019
Automation requires new competencies
The digital transformation has fundamentally changed the working world. The automation of tasks has become one of the most important components in companies to optimize work processes. Machines transmit information, so that the company can measure efficiency and use algorithms to generate demand forecasts. Each day, the Laundry & Home Care business unit at Henkel alone racks up one terabyte of data. To make the best possible use of it, employees and machines must continuously learn about and adapt to these developments.
When forklifts drive themselves and production line units communicate with one another, does industry still need people? Absolutely, says Wolfgang Weber, who is responsible for the digital transformation of the supply chain in the Laundry & Home Care business unit. He sees automation not as a danger, rather a clear chance to develop: “Automation is definitely not a personnel downsizing program. On the contrary, there are many competencies that we now need to have in-house, which we used to get from service providers and suppliers,” he explains. These aren’t just programmers and specialists, but more generally people who have a fundamental understanding of digital processes: “Every machine is constantly online and transmitting data. Therefore, our employees need to steer these units via web-based interfaces and understand the processes, which is a relatively new skillset,” says Weber.
Like it? Share it!
Automation at Henkel: Data, drones and digital skills
Quick stock check
In two warehouses, drones are used not just to take inventory, but also to control the quality of the packaging. Within 15 seconds, they scan a stock slot, identify each pallet by its label and check whether it contains the right goods and follows the correct packing arrangement. The technology then feeds all data back into the SAP system. The drones are due to be deployed in many other non-fully automated warehouses soon.
In Germany, Serbia, Poland and Spain, self-driving forklifts are taking over particularly short, recurring trips in production. The AGVs (Automated Guided Vehicles) use sensors within a defined area for orientation, as well as scanning their surroundings with laser and ultrasound technology. When an emitter stops working, the vehicle comes to an immediate halt to ensure that it won’t collide with people or other devices.
Henkel uses algorithms to generate realistic demand forecasts. Its so-called “demand sensing” combines internal data with public information like weather reports and holiday dates to estimate sales volumes in a given region. Demand sensing is currently in use for all European and North American markets. In the next implementation phase, Henkel will add customer data to the mix and roll the application out globally.
How much energy does the Somat filling process in Düsseldorf currently require? Which outlets consume more water than average? Henkel generates digital representations of all its environmental indicators. At every site, for every factory, we measure how much water and energy are needed and how much waste is generated. The figures allow comprehensive benchmarking, highlight potential for improvement and enable energy savings in the amount of 7 million euros per year.
As members of a production site’s management team, digital SPOCs (Single Points of Contact) act as multipliers for digital topics and speed up the communication both ways. Thanks to them, important decisions reach the individual sites faster. Conversely, they pick up employees’ ideas and suggestions, consolidate them and take them back to the group. The dialog increases employees’ awareness of which topics are important for the company and motivates them to contribute individually.
Automation requires the interaction between man and machine. For instance, plant layouts need to be readily available before they can be uploaded into self-driving vehicles. Employees then define where the vehicles are allowed to drive, simulate the flow of materials and control the applications. “These people have to be able to read the layouts, upload them and operate the forklift. We prepare them for this and bring them into the loop during development. They are also present when the units are installed,” Weber explains. With every production step that Henkel digitalizes, the goal is to make better use of machines, avoid production standstills and improve supply reliability. This, however, doesn’t mean that because of automation, fewer people are involved: “In Düsseldorf, three employees currently operate two high-speed filling lines. No digital technology could replace any of them,” he insists.
Collecting and analyzing data to make it usable
To digitalize the entire supply chain, Henkel needed to start early. For the Laundry & Home Care business unit, experts like Weber are driving Industry 4.0. They have defined three essential topics that created the foundation for automation: first, the “digital backbone” collects continuously generated data from around the world, including all applications, robots and a total of 3,500 sensors in the warehouses and factories. The second area is big data analytics, used to process real-time data, and the third is “paperless operations” – the interface with employees. This includes all the information that people need, but is no longer available as a handbook or printout, such as an efficiency curve on a screen, or information inside an app. The key for Weber and his team is to provide colleagues with the contents that they actually need. “We are not developing expert systems for ourselves. Everything that is created centrally needs to help our colleagues around the world and should be integrated as quickly as possible,” Weber says.
Automation requires “Digital Upskilling”
Since automation creates new areas of responsibility, employees have to be trained accordingly. With the training program “Digital Upskilling,” Henkel assesses the digital competence of all its employees and then offers them a personalized course. Weber and his colleagues have created a lot of educational content. Because not all processes are the same across the supply chain, there is even a dedicated training channel for working with the data collector. “We are dealing with historical structures where, as long as a machine is still working, we don’t replace it. That means we have to enhance the machines and create technical workarounds that our colleagues can operate,” says Weber. According to him, this may not turn every Henkel production plant into a smart factory – but it does mean every site has the basic digital capabilities to be online and access all crucial data.