Trends in manufacturing 2018

January 2018 — The quality and flexibility required in industrial production cannot be provided without the corresponding software systems. Industrial production is also seeing the rapid advance of digitization. German DIIT AG sketches the most important trends in 2018.

Artificial Intelligence (AI): The use of AI will increase considerably. The use of neural networks and machine learning in industrial automation and quality assurance can lead to considerable cost savings. For example, plants can "learn” autonomously from different operating states, thereby simplifying predictive maintenance, and through intelligent solutions for image processing and pattern detection, non-destructive test processes can be used to detect anomalies very quickly. 

Agile Manufacturing: Agile Manufacturing is replacing lean manufacturing to an ever greater extent. Manufacturers can use it, for instance, to respond quickly to new requirements and make changes to product designs or specifications. This also enables small and very small batch sizes to be created without production costs exploding. The trend towards customized production leads directly to agile manufacturing. 

Quality 4.0: Quality assurance will become a key production issue and quality must be integrated into product design from the outset. Using advanced software for successful quality management from the earliest planning phases helps avoid potential product and process faults. This is the only way to develop secure, robust products and efficient processes and to minimize testing costs during and after production. As is the case today with remote PC diagnosis, specialists can access production machines directly in order to identify and remove faults. Products save production data, measurement values and specifications in the individual production steps. This means they are able, almost autonomously, to control the production stations, instigate processing and record and evaluate usage and wear parameters over the entire lifecycle.

Traceability: Against the backdrop of increasing quality requirements, end-to-end traceability for more and more components is becoming essential. Traceability enables accurate fault detection because it can identify exactly which batch on which machine is responsible for potential faults. Counter-measures can then be implemented quickly. This means faults can be tightly ring-fenced so manufacturers only have to recall specific batches and not entire series in the event of more extensive malfunctions. 

Big Data: Efficient processing and analysis of very large data volumes will become increasingly important for industrial production. The highly-interconnected production now prevalent in nearly all companies generates huge data volumes which have to be recorded and processed in real time. A full analysis of all machine data can identify any performance deviations and wear that occur during a process. The machines themselves can then request preventive maintenance measures. 

"The common thread uniting all these current trends is the requirement for the use of very powerful software systems,” says Bernd Jost, Managing Director of DIIT. "Automotive production has already traveled a long way down this road and other sectors are now gradually catching up. However, industrial production will be only able to maintain the current quality level if it is software-controlled and highly-automated. We are seeing manufacturing and IT merging closer and closer together.” Jost's company is the world’s leading provider of integrated software solutions for engineering, manufacturing execution, customized wire harness production and logistics. DIIT is a wholly-owned, independently managed company of the Schleuniger Group. Schleuniger is a globally active technology company and a leading solution supplier in the wire processing industry.

Justus-von-Liebig-Ring 11a
82152 Krailling/Germany
Contact person is Mr. Bernd Jost
Tel.: +49 89 8932500

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