Just a few years ago, those employees that showed an interest in technologies such as Artificial Intelligence (AI) were considered exotic nerds within their organizations. That has changed: More and more organizations are recognizing the potential and are ready to make use of them. What’s more, to remain competitive in today’s markets, organizations in innovative sectors and industries are particularly dependent on the latest IT innovations.
Data forms the basis for these new technologies. Yet, while at first glance, the human brain only sees a huge mountain of information, or worse yet, contradictions, the software ideally recognizes patterns, regularities or deviations that help to identify weak points more quickly and improve results. The data analytics can be used to derive insights for practical applications. The results of our latest “Performance Drivers 2024” study show quite clearly how great this potential is: Three out of four industrial organizations expect their industry to experience a significant economic boost from the introduction of new technologies, particularly AI (see graphic).
As an experienced consultant and project manager in the fields of operational excellence and Lean Management, Dr. Michael Feldmeth holds a doctorate in engineering and is a trainer at Staufen Academy. He specializes in mechanical and plant engineering, automotive and vehicle construction, and medical technology. He has extensive expertise in plant development, factory design and in optimizing direct and indirect business processes.
Michael has experience of restructuring in the areas of production (manufacturing and assembly), logistics and order fulfillment, practical Shop Floor experience and a sound technical understanding of production processes.
New standards in technology, applications that are more user-friendly, and advances in the development of AI have made this technology no longer exclusive to a few high-tech specialists, but an affordable tool for SMEs – an ideal instrument to stand out from the competition. While gut instinct was often relied upon in the past, decisions are now increasingly based on data.
Digitalization in industrial SMEs is made possible by linking a broad range of data sources, including suppliers, production machines, purchasing figures, and even user feedback. This data pool delivers the information needed to uncover hidden relationships. As a result, problems in the production chain, for example, that used to take days to detect, can now be identified immediately by glancing at the dashboard. By the same token, potential obstacles to production can be cleared out of the way as early as the product development phase. This leads to a data-driven productivity boost in the industrial organizations’ workshops and offices.
What is required for the change to be successful is a willingness to question tradition and embrace new technologies. Nevertheless, this is a worthwhile effort. Costs of goods sold are falling, while product quality has improved. One extremely positive effect is that the burden on employees is reduced while they are provided with an optimal information base for far-reaching and continuously adaptable optimization measures – the perfect driver, therefore, to establish operational excellence within the organization.
Enormous Amounts of Potential are Released
Participants in our study have also predicted this shift in industry: 84 percent expect the industrial workplace to change rapidly in response to technological developments. The close interaction between employees and intelligent systems will soon shape day-to-day work. Fears that AI will take over thinking while humans merely execute are unfounded. Quite the opposite: All the signs indicate that, thanks to AI and automatic data analysis, humans will be able to make rational decisions with sufficient leeway for value-adding, creative activities.
With networked machines, extensive data analysis and the intelligent dovetailing of all processes, digitalization will be able to live up to its promise of greater efficiency and cost benefits in industry. Still, we still have a long way to go, as 86 percent of the more than 200 companies surveyed admit: According to our own assessment, we can significantly improve our ability to exploit the data analysis potential for improving results.
As an experienced consultant and project manager in the fields of operational excellence and Lean Management, Dr. Michael Feldmeth holds a doctorate in engineering and is a trainer at Staufen Academy. He specializes in mechanical and plant engineering, automotive and vehicle construction, and medical technology. He has extensive expertise in plant development, factory design and in optimizing direct and indirect business processes.
Michael has experience of restructuring in the areas of production (manufacturing and assembly), logistics and order fulfillment, practical Shop Floor experience and a sound technical understanding of production processes.
The often small-scale and rather knee-jerk reactions to the current polycrisis are increasingly taking up so much capacity in many organizations that long-term projects often fall by the wayside. According to the latest study “Performance Drivers 2024”, there are already three out of four organizations that have to cut back on implementing their strategic decisions. If they want to propel their business back towards high performance, though, organizations should abandon this passive attitude and instead systematically and courageously improve their performance.
The automotive supplier DRÄXLMAIER has established a production line for 800 volt batteries that power the Porsche Taycan electric sports car. A key factor in the
successful implementation of the production targets was data management.
In the interview, Dr Vineetha Menon emphasises that companies must overcome challenges such as the ethical and safe integration of AI when adapting to the digital age. Successful AI implementations involve continuous learning and fostering a learning culture. Explainable AI plays a key role in building trust and transparency, especially in sensitive industries. Future workforce needs a combination of technical, AI and soft skills. Companies should invest in education and training to create an AI-friendly culture. In addition, ethical, social and legal issues need to be clarified in order to integrate AI sustainably.
Intelligent Industry 4.0 production processes can be applied to accomplish a variety of objectives. These include achieving greater productivity and efficiency, fulfilling consumer specifications faster and more expediently, and developing brand-new industrial products and business models. Small and mid-sized companies often have a particular need for this kind of consulting and guidance.
