Plastic injection moulding is a difficult application for machine vision. The highly reflective surface of plastics is hard to illuminate, and the fact that the same production line can create items of different colours and shapes is problematic for traditional solutions.
When designing any part for injection molding, it is important to consider the shrinkage and contraction rate of the material and the associated geometry of the component. Plastic shrinkage is the dimensional change that occurs in a molded part as it cools after injection.
While most analysis of the IoT is in respect of its positive influence on manufacturing processes, the growth in the IoT also opens up huge possibilities for micro molding as there is burgeoning demand for a variety of new and innovative micro devices.
Not being limited to metal (or a few standard plastics) opens up a much wider range of design options for engineering and design teams. They can think in more creative ways about complex geometry, performance in harsh environments, shielding considerations etc.
This approach is superior to standard molding procedures because of the high level of scientific control utilized through upfront Design of Experiments (DoE), flow analysis, process monitoring, and quality control that can quickly detect and correct any process variations.
Humans and robots can now share tasks - and this new partnership is on the verge of revolutionizing the production line. Today's drivers like data-driven services, decreasing product lifetimes and the need for product differentiation are putting flexibility paramount, and no technology is better suited to meet these needs than the Omron TM Series Collaborative Robot. With force feedback, collision detection technology and an intuitive, hand-guided teaching mechanism, the TM Series cobot is designed to work in immediate proximity to a human worker and is easier than ever to train on new tasks.