MechChem Africa July-August 2022

⎪ Automation, process control, instrumentation and CAE ⎪

individual components and the assembly of the stacks through to the manufacture of the entire system. Fuel cell components such as bipolar plates, gas diffusion layers and catalyst-coated membranes are manu factured with different materials in dif ferent production processes. Widespread deployment of electrolysis and fuel cell technology requires product and process innovation to reduce production costs to drive the deployment of this technology. Scaling production volumes while main taining uniform quality requirements is needed. Flexible and scalable production lines that can quickly and easily be adapted to individual requirements are advisable. Approaches are needed to reduce the pro duction costs of fuel cells, as this is the only way the technology will be accepted in the longer term. Unlike battery cell production, where pro cesses have already been automated for many years and are constantly being further developed, fuel cell production is still almost at the beginning. This is mainly because hydrogen technologies do not yet have the application and acceptance that increased production requires. Many workflows are therefore carried out semi-automatically or even manually. To make hydrogen applications more at tractive, increased automation in manufac turing is urgently needed. Since battery and fuel cell manufacturing are similar in many respects, it is advisable to rely on a partner that is familiar with automated battery cell manufacturing. In addition to the technology and know how, system integrators and machine builders are also needed to jointly drive this technology forward. A particularly critical process in battery and fuel cell production is stacking, which is where errors such as Battery expertise supports fuel cell production

In the coming years, hydrogen propulsion systems will be found in many different application scenarios such as transport, heating and power generation. Source: European Commission Statement 2020.

chains. Used correctly, AI can help business leaders in the automotive sector to better understand their processes. The informa tion collected by AI and sensor-based tech nologies leads to new insights to optimise processes inside and outside the company. An example is predictive maintenance, which can be used to detect wear patterns, peculiarities and anomalies, thus coun teracting machine failures, downtime and errors. AI can also help to capture market share in new innovative markets. Particular attention should be paid to seamless and flexible intralogistics processes, the key being transparent supply chains. Collective measures needed In the coming years, a mix of different drive technologies will establish itself on the market. This includes the fuel cell as an im portant building block. For alternative tech nologies of the future to gain momentum, it is now up to politicians, manufacturers and service providers to pull together, optimise frameworks and production conditions and promote digitalisation and automation. OMRON can offer support here, with its many years of expertise in this field as well as having the technologies and strate gies of the i-Automation! model. In fuel cell production, the company places a special focus on high speed and precision. Newly developed edge-based algorithms such as Shape Search III object detection are being used. Less data is used for position adjust ment to increase transparency. At the same time, several processes work in parallel to minimise production time. Permanent position adjustment is dynami cally corrected between OMRON NX ma chine automation controllers and FH-series high speed digital cameras, considerably ac celeratinghigh-precisionpositionadjustment. These are all examples of technologi cal innovations that can optimise fuel cell manufacturing so the hurdles for increased engagement in this field (hopefully) tumble. www.industrial.omron.co.za

leaks can occur. Finding the cause takes a lot of time. Stacking expertise is therefore also recommended. In addition, the mem brane must be handled carefully so it is not damaged. The Factory of the Future The cornerstones of future-oriented fuel cell production to promote sustainable mo bility are the procedures and technologies of the Smart Factory. They make it possible to comprehensively modernise production and rationalise supply chains from the ground up, in parallel with the expansion and conversion to new drive technologies. Innovative industrial robotics, mobile robots and cobots, edge computing, sensor technology and the coupling of mechatron ics, IT and augmented reality (AR) are some examples of this factory of the future. The highest possible degree of digi talisation is key to success, so that the manufacturing process can optimise itself independently. Traceability is also essential, ideally so that every single layer of a fuel cell can be traced to establish exactly where production is not running optimally. Another pillar is artificial intelligence (AI) , which can unleash new efficiency potential from highly complex production

Innovative industrial robotics, mobile robots, cobots, edge computing, sensor technology and augmented reality (AR) are some examples of this factory of the future.

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