AGMA 15FTM07 PDF

The Industry 4.0 is an initiative of leading German industrial corporations and scientific institutions, supported with funding from the German government, which promotes the computerization of traditional industries such as manufacturing. This paper reviews the four industrial periods from the viewpoint of gear manufacturing and points out the special character of the fourth industrial period, which has just begun. The main part of the paper reports about the techniques and elements of the so-called cyber physical production systems and how they will change the way of industrial manufacturing. In the proceeding sections, the paper relates the features of Industry 4.0 to the Gleason achievements regarding machining process design, machine networking, expert systems, machine self-diagnosis, and cycle optimization, as well as remote diagnosis. The conclusion points out that the new movement will enhance manufacturing capabilities, improve product quality, and will create very flexible manufacturing. Gleason products today already show a significant content of smart features and modern data processing, which together with a leading strategy for future developments, is represented with the name Gleason 4.0.

A concern of manufacturing personnel is the missing transparency and traceability of the action that a smart manufacturing control is executing. The concern, that chaotic situations can occur if the smart manufacturing system has to react to unexpected input information, is justified; the concern about missing traceability is, in most cases, not justified. For example, in the early days of G-AGE corrections, gear engineers liked to understand why the combination of five or more delta settings would correct a certain flank form error. However, the mathematics behind those corrections are rather complex and would require many hours—or even days—to verify a single set of correction data. After the first years of practice with G-AGE, gear engineers learned to trust the results and applied them without questioning. In the few cases when the theory failed and the corrections made the gear worse, the gear engineer used common sense and either applied simple manually calculated corrections or eliminated a critical input or output variable in order to unarm the unstable part of the originally computed results.

This example shows that it is efficient to have the thousands of decisions or actions which are constantly reoccurring done by the smart manufacturing system. Its strength is to execute reoccurring operating tasks very fast. The human skill is to concentrate on all out-of-the-ordinary situations, in which the computerized intelligence is not very strong. The artificial neurons don’t take anyone’s workplace. Quite the contrary—future manufacturing will only exist if it follows the smart movement. Workplaces in factories will be sophisticated and interesting, and humans will be in control…probably in more control than they have been in the past.