In this short video, Frank Piller, an award-winning professor and future manufacturing expert, will share with you four small case studies that illustrate how digitalisation and algorithms are changing the way we design new products and services. Frank expands on this subject during his Masterclass ‘Leading Intelligent Engineering’, where he differentiates four different pillars for different fields of application.
1st Pillar: Predictive Innovation
Case Study: Fashion Start-up Choosy
The first pillar is predictive innovation, which is the ability to predict the next big innovation using an algorithm. A great example of this is a company called Choosy, which an IT graduate started in Boston. She starts with an algorithm that in real-time scans Instagram for trending fashion, which is promptly followed by a second algorithm that automatically generates new fashion items based on the trends identified by the first algorithm on Instagram. At this point, a manufacturing plant in China creates small samples of these fashion items in just two weeks, and finally, a third algorithm recommends this item to Instagram users, based on their past preferences. If the items sell and the collection becomes successful, they are then sold to prominent manufacturers and retailers as vetted collections. This entire process takes less than three weeks from design to market launch. If algorithms can design fashion, it might be worth to explore whether they could design your next product.
2nd Pillar: Collaborative front end
Case Study: Automotive Company meets Agriculture
The second pillar, collaborative front end, is something that has been spoken about for a while in open innovation, but it’s just become a reality these days. An easy example of this is a famous automotive company I worked with in Germany. In high-end cars, you have a motor that closes the trunk and side doors automatically, because of this, as opposed to cheaper cars with manual doors, if your finger gets trapped and injured while closing the door by mistake you can sue the manufacturer. This company was looking for a sensor to detect whether there were fingers in the door’s trajectory but could not find any. Hence, they went to an open innovation platform and put out the request to find said sensors. Surprisingly, the ones to respond were sensor manufacturers from the agricultural industry, a small, specialised company from Denmark, which makes sensors for robots employed in milking cows. This collaboration was only possible because of the open innovation platform, no one in the German automotive industry would have ever specifically looked in the agricultural business to find sensors for high-end cars, nor such a small and specialised Danish company would have ever thought they could do business with a large German OEM. Making these unobvious connections is one of the core abilities of this new kind of open innovation platforms.
3rd Pillar: Digital design
Case Study: Designing boats
This third example is about having an algorithm coming up with new designs, something that has been in science fiction for quite a while, but it is now happening in the real world. Tim Simpson, the colleague who is teaching the Masterclass with me, would be the perfect expert to share more about this. He would show you a real-life example of this concept, an algorithm he created that has been trained to understand the concept of what a boat is. By showing a group of algorithms thousands of pictures of boats from Google, some of the algorithms start to understand what boats are. After that, an Artificial Intelligence generates a new boat, which is then simulated in Unity, a software usually made for building videogames, but which also works to engineer real commercial products, in which the boat is tested in digital water. The algorithm understands, creates and then tests the boat, and for the first thousand times, the boat sinks right away, after a while, the algorithm comes up with a design that partially works. It then continuously iterates the process, just over night-time it can generate more than 200,000 different designs, test them, and finally come up with a speedboat that works by the next morning (although the boat will look a bit unusual). This incredible technology gives us a new level of freedom when it comes to design.
4th Pillar: Smart Product Ecosystem
Case Study: Adidas
The 4th pillar is the business model dimension of Leading Intelligent Engineering, and that’s the upcoming smart product ecosystem. Most products nowadays come in a smart version, smart light, smart cars, smartwatches are just a few examples of this. Physical products are now enhanced by digital services, an app that can provide additional value when connected to a smart product. This is one of the biggest engineering challenges, particularly because we often do not design the hardware while we develop the ecosystem. In the Masterclass, I will share the example of a new sports shoe we made with Adidas, a German shoe manufacturing company, with which we designed a new sensor-enabled shoe for running. The main challenge in the realisation of the project was not putting sensors in the shoe (although that surely wasn’t easy), it was to create a meaningful ecosystem, not just an app but a data collection and data sharing platform. We intended to create a user community so that we could create a very scalable and affordable running experience for many, many people. A platform that could give advice not just on running, but also on nutrition and health, in the form of a scalable app. The engineering task in this type of projects becomes much more significant than to create a product with embedded sensors and software to go with it, and it must focus on designing the right ecosystem.
These were rather simple examples from the consumer goods industry. If you’d like to explore more sophisticated examples that apply to your company, and get specific tools that will allow you to make your R&D and Engineering departments more effective at producing successful products, feel free to join my Masterclass, looking forward to seeing you there.