The digitalisation of the value chain as completely as possible has long been at the top of the agenda for the manufacturing industry.
By Fadi Kanafani, senior director: Middle East, Africa and Pakistan at NetApp
A self-organised and independently learning production hall is the declared goal for industry 4.0 – and new technological innovations are always within reach.
A study by the Berlin Institute for Innovation and Technology (IIT) commissioned by the Federal Ministry of Economics and Energy (BMWi) shows that artificial intelligence (AI) has enormous potential for future value creation in the manufacturing industry.
The use of AI is expected to generate an additional gross value added of around 31.8 billion euros for the industry in Germany within the next five years. This would mean that AI would be responsible for a good third of the expected overall growth. According to the study, the AI applications predictive analytics, robotics and intelligent assistance systems, automation and sensor technology are particularly promising.
AI: step by step
Predictive maintenance was the entry into smart production for many industrial companies, but the need for automation and efficiency now predominates.
This is the result of a survey conducted by data management specialist NetApp among 120 German IT experts. It shows that AI is currently used in the manufacturing industry primarily for the automation of repetitive manufacturing processes (Robotic Process Automation, RPA) and for supply chain and warehouse management.
This was stated by 66,7% and 60%, respectively, of respondents from the industry. However, many companies are just at the beginning of their AI strategy: 46,7% of decision-makers were in their first year of active use of AI at the time of the survey. Other industries such as the financial sector are (still) one step ahead. However, the manufacturing industry has a particularly high success rate in AI projects – so it has recognised the importance of AI for the future.
Some reservations remain
However, there are still some persistent reservations between business and the next step in digital transformation: On the one hand, companies fear high costs for an integrated digitalization of all production processes – especially because this would also involve the modernization of outdated IT infrastructures.
Costs would therefore be incurred on the software and hardware side. The duration of such an implementation also contributes to the hesitant behavior. And, as with all data-driven processes, the question of data protection is of course also at issue here, which will become even more important than before after the GDPR comes into force.
However, many of these concerns can be eliminated or at least mitigated with the appropriate know-how. In order to bring the appropriate specialist knowledge into their own company, the manufacturers pursue several strategies. For example, they expressly set themselves the goal of setting up an internal AI department, hiring individual AI experts and cooperating with external consultants and companies.
Especially at the beginning of a company’s AI strategy, it is important to exchange ideas with parties outside its own ecosystem in order to avoid fundamental mistakes and omissions that would affect any follow-up projects. In the medium to long term, however, it is advisable to set up your own AI team in order to stimulate the internal exchange of knowledge and facilitate the integration of new employees.
No industry 4.0 without innovation
Although the next stage of digitisation will require a high level of investment from the manufacturing industry, this is a necessary step to continue the development towards an intelligent manufacturing hall. The former flagship project predictive maintenance has now become the standard, and the task now is to integrate new technological innovations into the processes.
A methodical approach has enabled the manufacturing industry to establish itself as a test champion and successfully integrate machine learning into production, customer care and quality assurance. So there is no reason why it should now stop at artificial intelligence.