Molders, Shapers, and Casters, Except Metal and Plastic

In molding and casting (outside metal/plastic), some steps are already helped by machines. For example, researchers have built robotic arms that load and unload ceramics in hot kilns, making the work safer and faster ^[1]. Other teams developed robot “hands” with sensors to gently hold pottery for glazing or polishing ^[2].

In big factories (like tile or sanitaryware plants), conveyors and robots often move molds and trays to ovens, and specialize machines can spin or sponge off excess clay. Even 3D printers are entering this field: for high-tech parts (like turbine blades), ceramic molds are now 3D-printed, cutting many manual steps ^[3]. However, many tasks still depend on people.

Reading plans or work orders is usually handled on a computer screen, not by a robot, and shaping complex molds by hand or finishing details often needs human touch. Industry studies note that the ceramics sector is exploring AI and automation – for example using digital twins and sensors to track ovens and supply chains – but this is mostly in larger companies so far ^[2]. Overall, much of the heavy lifting (like oven loading or rough trimming) can be done by machines, while finer, craft-oriented steps remain hands-on. (The field still has around 42,000 workers and is expected to grow slowly over the next decade ^[4].)

Whether a pottery or casting shop adds AI/robots often comes down to cost, scale, and customer preferences. Big factories can afford special machines. For instance, one study notes that repetitive heavy work can strain workers, so factories replace those tasks with robots – improving safety and efficiency while letting people move to supervising or quality checks ^[2].

That makes sense where labor is expensive or in short supply. But small craft studios usually keep many steps manual. Special-purpose robots are costly and usually pay off only with high-volume production ^{[1] [2]}.

Social factors also matter: handmade pottery can be sold as artisanal, fetching higher prices. In those cases, owners may choose skilled workers over machines. In short, AI and automation tend to be adopted more quickly in larger, industrial settings (to boost output and meet strict environmental rules ^[2]), while in smaller shops change is slower.