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Manufacturers of plastic parts recognize the potential of conformal cooling to reduce molding cycle times. Problem is, conformal molds require additive manufacturing (AM), and technologies in that space are still evolving. Costs also can be high, and beyond that, many manufacturing organizations lack the knowledge and expertise needed to apply and incorporate additive technologies into their operations.
Machine vision and video streaming systems are used for a variety of purposes, and each has applications for which it is best suited. This denotes that there are differences between them, and these differences can be categorized as the type of lenses used, the resolution of imaging elements, and the underlying software used to interpret the data.
In the face of growing challenges for embedded technology engineers, designers should actually be designing for a new IoT -- the Internet of Tomorrow.
As today’s product design cycles are held to tighter schedules and budget constraints, it’s becoming even more critical to consider human factors up front to catch and fix problems during the initial development stages, when it’s faster and less costly to do so. Overlooking human factors at the beginning of the design cycle could lead to poor user experience, a decrease in effective product performance, and an increase in safety risk to the user.
Plastic part manufacturers are always looking for ways to reduce cycle time and get more productivity out of their injection molding machinery. One of the longstanding constraints in injection molding production has been cooling time. Removing parts from the mold before they have cooled induces warping or shrinking. But wait time works against productivity.