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 that flexibility is needed throughout the value chain, but it can- not be at a high cost,” says Rodriguez.
On the other hand, there’s the rapid evolution in technology: digitalization, the Internet of Things, sensor technology, com- munication between machines and the cloud, self-regulating and self-calibrating systems, machine learning, and artificial intelligence—in a word, Industrialization 4.0. The ABB Abili- ty platform and multiple partnerships help ABB’s customers meet the current challenge.
The new architecture: simpler and flatter
To do this requires building flexibility into every layer of the manufacturing process: the machine, the line, and the enter- prise. The shape and design of the factory floor itself is chang- ing. Where there was once a conveyor belt—a line moving at a set speed—there is now a series of discrete production is- lands operated by robots and served by AGVs.
The flow of information within the factory has also changed. With machines themselves becoming ever smarter, decisions do not need to be made at a higher level but stay at the machine or on the shop floor. “The basic architecture is becoming simpler and flatter because the factory can do more on its own,” says Rodriguez.
The automobile industry has been one of the first to exper- iment with this new approach as it addresses increasing un- predictability in demand, shorter model cycles, and the shift to e-mobility. For example, as the technology improves, electric vehicles are becoming more popular. However, it is difficult to predict by how much demand will grow. Auto manufacturers therefore need a flexible approach—they need to keep open the option of building internal combustion engines and hybrids alongside new electric vehicles. Some of them need one plant that can build all three. The flexible factory gives them this, with production islands for each type of engine. If demand for one category changes, islands can be added or taken away. “It’s a modular system, so you can manage changes in demand and increase utilization of your assets,” says Rodriguez.
Algorithms find the best solutions
One sector with a high need for flexibility is consumer pack- aged goods. From shampoos and cosmetics to food and beverages, end customer demand changes rapidly, so man- ufacturers have to produce smaller lots, with more variety in product and package design, in ever shorter cycles.
Flexible factories are clearly the solution, but they bring with them some new challenges. One of the biggest of these is optimizing the flow. “I call it internal logistics,” says Rodri- guez. “How do you work out the best path for the AGVs? We didn’t have this problem in the past; we just needed to ensure that the line was running at the right speed.”
To answer this question, the manufacturing sector has been looking to warehouse logistics, where advanced auto- mation has been developed to manage the mass of products. Related to this is the new challenge of knowing where every- thing is in the plant when there is no longer a linear path, but multiple paths.
Then there is the question of what to do with the enormous amount of data produced by digitally connected machines.
“The challenge is having reliable software and platforms to process the data in an almost real-time situation in high-vol- ume operations,” says Rodriguez. This requires more work by people skilled in data science and algorithm development.
With algorithms optimizing processes, the automation paradigms change. “The platform allows information to per- colate through the enterprise,” says Rodriguez. “It moves us from rule-based to goal-based automation. Instead of saying the temperature of the furnace must be ‘x,’ we now say the temperature of the furnace must be the right one to reduce quality issues and the algorithms must find out what it is.”
The fully automated, flexible factory is already a reality, but the final challenge is enabling deployment in brownfields and retrofitting existing lines. To do this requires attaching smart sensors to machines that have no processor and no data, cre- ating a bridge to bring them into the new digital ecosystem. “This is a major undertaking that requires a modular approach,” says Rodriguez. “We have to find ways to complement existing systems without compromising the way they currently work.” Rodriguez’s guess is that in ten to twenty years from now, 10 to 15 percent of factories will be greenfield—fully automated and flexible—40 to 60 percent will be hybrid, and 10 to 20 percent will still be conventional factories. “The technology is evolving to meet our new needs,” he says. “I don’t think it’s all there yet, but there are certainly a lot of smart people thinking about how to solve these challenges.”
The robotic colleague
The collaborative
robot YuMi (above) uses camera recognition to determine which parts are in front of it, and can move them with its flexible gripping hands. It can thus assemble small parts in the electronics industry
or handle medical samples—without any risk of infection for
its human colleagues. YuMi’s software has also been designed to be connected to older computer technology
in laboratories and factories.
  CNAUS: WHERE ROBOTS BUILD ROBOTS
In a greenfield site near Shanghai, China, ABB has invested US$150 million to build a state-of-the-art robotics factory. Fully automated and flexible, this will be a production site where robots will build robots at island assembly points, served by AGVs in a decentralized production process. The system itself will decide whether to speed up or slow down production and whether to shut down islands or add new cells as demand grows. Porsche Consulting helped ABB to realize its vision, designing the IT architecture, defining digital use cases, and identifying savings. The production site is proof that manufacturing can be both flexible and efficient.
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