In spring 2019, the VDMA conducted its first survey on machine learning in mechanical and plant engineering. More than 70 companies took part in the survey. The main focus of the study was on the significance and use of the artificial intelligent (AI) products in business processes as well as in products and services.
The interviewees indicate a medium to high relevance of machine learning based solutions to support business processes, especially in the application areas of customer service (64 percent), design and development (54 percent) and production (50 percent).
In terms of significance of AI products, it is mainly machines (69 percent) and predictive maintenance (69 percent) and condition monitoring (65 percent) that are of medium to high importance from the company’s point of view.
COMPANIES TO SIGNIFICANTLY INCREASE THE USE OF AI PRODUCTS IN THE NEXT 3 YEARS
Around 46 percent of the participants already have a smart solution in use for the company processes or in the products or services. Today’s application focus is essentially on design and development (14 percent), customer service (13 percent), production (13 percent), accounting and controlling (10 percent), condition monitoring (13 percent) and remote service (13 percent).
However, the companies surveyed are planning to significantly increase the use of these products and processes over the next three years. By 2022, for example, more than half of the companies want to use machine learning-based solutions in customer service.
MACHINE LEARNING USUALLY SHOWS IMMEDIATE IMPACT ON INTERNAL BUSINESS PROCESSES
The first experiences of the survey participants with the use of ML-based solutions show very different effects in the internal business processes and with the customer. Particularly in the non-manufacturing processes, the use of this technology has already led to a reduction in personnel expenses (time, costs …) for about half (41 percent) of the companies. In addition, the four most frequent effects included an increase in the degree of automation in the processes (37 percent), improvement in service support (33 percent) and communication with internal or external process participants (33 percent). The manufacturing processes in the company also show predominantly similar effects among the most frequently mentioned. Through the use of ML-based solutions in products or services for mechanical engineering customers, in addition to a reduction in personnel expenses (44 percent) and an increase in the degree of automation (41 percent), the possibility of offering new products or services (48 percent) was created in the first place.
PERSONNEL BOTTLENECKS AND A LACK OF QUALIFIED DATA MATERIAL IMPAIRED WIDER USE
Among the five most common reasons why machine builders are currently not using ML-based solutions in business processes or in products or services, lack of human resources (64 percent) and lack of qualified data material for training (64 percent) occupy the top places. Also, an unclear benefit or return on investment and open legal questions are decisive for 43 percent of the participants that no use is currently taking place.
AI AND MACHINE LEARNING EXPERTS ARE NEEDED
It is undisputed that projects in the future will not function without experts for machine learning or artificial intelligence in the company, since in many cases data first has to be analysed and modelled for the later task have to be trained. 42 percent of the participants therefore plan to make appropriate settings by 2022. Small and large companies alike are looking for this expansion of competence.
VDMA is the largest industry association in Europe with around 3,200 members. Its headquarters is in Frankfurt, Germany.