Artificial Intelligence (AI) has entered the mainstream and is starting to revolutionize industries around the globe.  Digital print production is no exception. In fact, it offers rich potential for the use of the technology to enhance quality and productivity, streamline operations and create client value.

We at Ricoh have already identified five key ways in which AI can take digital print production forward:

Ensuring consistently high print quality – AI algorithms can process data captured from a press’s integrated inspection system to analyse the quality of the printed output in real time to maintain colour consistency and to identify any potential print quality issues early, enabling the press to automatically take action to address them as they arise.

Reducing operator load through automation of repetitive tasks – A valuable use of AI is to help automate repetitive tasks such as print scaling, front-to-back registration, density adjustment, and paper profiling, allowing operators to focus on higher value added activities.

Keeping presses productive cost effectively through targeted preventative maintenance – Changing out components before they fail has become a well-established industry practice.  However, the frequency of part replacements has often been based on simple estimations of their average operating lives. AI, on the other hand, can analyse the performance of the press to predict much more accurately when individual components will fail – allowing just those that need replacing to be changed, thus reducing waste from unnecessary downtime and unwarranted component replacements.

Increasing efficiency via print production automation – AI has the potential to play a role in the management and optimisation of the entire print production workflow from prepress through to post-processing – automating processes and giving executives better visibility of performance, supporting management decision making and driving even greater efficiencies.

Creating value through greater print personalization – AI can be deployed to analyse large quantities of customer data, facilitating a higher level of print personalisation.  This can, for example, increase the return on investment for direct mail campaigns.