Artificial intelligence (AI) techniques have been behind disruptive innovations in every industry. Based on AI techniques, large amounts of data can be converted into actionable insights and predictions. Manufacturers have frequently faced different kinds of challenges, such as unexpected machinery failures or defective product deliveries. Still, the adoption of AI techniques is expected to improve operational efficiency, enable the launch of new products, customize product designs, and plan future financial actions. Recently, manufacturers have been using AI techniques to improve the quality of their products, achieve greater speed and visibility across supply chains, and optimize inventory management.

Given that the attention and interest in AI techniques has been growing rapidly, it is time that the current state of the art of their practical applications be presented. The main aim of this special issue is to bring together the latest AI research and practical case studies of AI techniques in production engineering. Related topics of interest include but are not limited to the following:

* Product development and design customization
* Process modeling/simulation
* Process monitoring/control
* CAD/CAM/CAE and generative design
* Predictive maintenance and logistics optimization

We hope this special Issue will contribute to the future research and development efforts of researchers and engineers in the field of production engineering.