Discussion

By Robert Godwin on Jan 23, 2017

Developers often remind us that software is never done. Neither is the evolution of artificial intelligence and algorithmic processes. Our imposition workflow achieves efficiencies in time and costs using machine learning, the practical application of artificial intelligence. How? By taking into consideration costs of labor, pack-out errors and shipping.

We save about 60% in costs over conventional ganged imposition workflows using machine learning – which comes into play when post-process analysis concludes that there may be better ways to achieve those savings. And on the next sheet, those ‘learned’ ways are deployed.

Machine learning is more accurate and decides without bias. Human craftsmen? Not so much. In many cases a ganged imposition may not reduce paper waste completely, but can be cut faster in the bindery, packaged more quickly and accurately, or shipped at a lower cost. These efficiencies are achieved from the cut-block data set and running algorithms we have developed.

These are just some of the change-agent dynamics needed in most commercial print shops, and offer challenges to the most forward-thinking managers. As stated in the video, artificial intelligence and machine learning are essential to keep printing competitively priced and profitable.