Use cases around predictive maintenance
Another component of the roundtable was the exchange on use cases and usage scenarios. We at doubleSlash were able to provide insights into the Practical example of ZF wind power give. In particular, I discussed the importance of a Integration in the partner landscape in the context of wind turbines and why ZF Windkraft's approach is so remarkable in this respect. Two things have been particularly successful here: The Seamless integration of multiple suppliers in one portal and the Recycling of technical systems across these different suppliers. Because: The Added value is for the End user higher and higher, the Fewer portals, tools and applications are needed. This also appears to be the case for the Mechanical engineering sector to be highly relevant, as the open format of the event led to an intensive discussion.
Software architecture and design as a key factor for predictive maintenance projects
The second aspect that technically enables cooperation between different parties - such as the joint service providers in the wind turbine case - is the Integration of existing systemsideally with Stock interfaces. The advice from us as an IT service provider to the industry to look for a Appropriate architecture and software design was received with interest. Because we observe this time and again in projects: a Professional software development is the link for a holistic solution and will also play an increasingly important role in the future due to increasing digitalization in engineering-based companies in the mechanical engineering sector.
Predictive maintenance and virtual reality
Smart maintenance and its usage scenarios also deal with Augmented reality (AR) and virtual reality (VR) with this. In particular Deutz impressively demonstrated how to work with existing data and expertise within a company to introduce a networking solution in an extremely varied and heterogeneous environment can be used. The Deutz Connect App displays information such as maintenance processes in 3D in real time depending on the individual engine and, in my opinion, has rightly won the Red Dot Award 2018 received.
Challenges in predictive maintenance projects: Data quality and networking
The event was rounded off by a perspective from KPMG Lighthouse, which presented the role of a Data Scientists Challenges for networking and in particular to data quality. The advice to Thinking about data quality at an early stage We can only emphasize this from doubleSlash's point of view. This ensures that Machine learning or data science projects have a higher chance of success and these projects with a less effort can be implemented.
3 questions about predictive maintenance
The subsequent discussions seamlessly followed on from the very open interaction during the entire event. We took the opportunity to ask Ekkehart Gerlach, Managing Director of the Media Academy, a few questions:
- doubleSlash: Mr. Gerlach, how important are event series such as the Smart Maintenance Expert Roundtable for the topic of predictive maintenance and what experiences have you had with the event series so far?
Ekkehart Gerlach: As we all know, many topics relating to the Internet are quite complex, even nebulous in some cases, and the terms used, such as Industry 4.0, are not self-explanatory. With this in mind, it is worth taking a closer look at those areas of Industry 4.0 that offer clearly recognizable added value and, at the end of the day, result in very satisfactory black figures. - doubleSlash: How mature do you think the topic of "predictive maintenance" is in practice?
Ekkehart Gerlach: Following the first "best practices" that have already been published in trade magazines and newsletters, e.g. in the elevator sector, there has been increasing awareness in other maintenance-intensive sectors - and in many of these sectors, corresponding projects are now underway, at least as pilots. - doubleSlash: What role do software houses such as doubleSlash play in the successful implementation of predictive maintenance and how do you think it can add value for German machine builders?
Ekkehart Gerlach: Companies that offer "digital" products and services, such as software and engineering companies, generally play a very important role in the various forms of smart maintenance, as extensive ICT knowledge, an understanding of complex technology right through to algorithms and implementation expertise are required from concept to implementation.
Would you like to know whether it is worth using a predictive maintenance solution in your company? Our business case template will help you answer the relevant questions.
Download template nowMore blog posts on the topic of predictive maintenance:
Best practices in the implementation of predictive maintenance - a field report
Predictive maintenance: the maintenance of tomorrow in Industry 4.0
Predictive maintenance: the biggest challenges for companies
How does predictive maintenance differ from other maintenance methods?
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