any assembly operations begin with the scanning of a 1D or 2D bar code. The code might tell an assembler what parts to install and how to install them.

In its latest report, BCC Research projects the global drug delivery market to grow to nearly $227.3 billion by 2020, with a compound annual growth rate of 4.9 percent. This is great news for the French company Nemera, which designs and manufactures world-class drug delivery devices for the pharmaceutical industry.

Every manufacturer has one want and many needs. The want is universal, to be the leader in its industry or area of specialty. The needs are individual, and may concern issues as diverse as increasing capital, upgrading technology, expanding plant size or hiring more assemblers.

Many machine vision projects start with one goal: significantly improve upon the accuracy and repeatability of human inspectors.

The automotive industry experienced a record number of vehicle recalls in 2018, and this year's tally isn't far behind. Many of those issues have been caused by electronics or software glitches.

For many years, pet food manufacturers have used machine vision software to verify the presence of unique characters, codes, colors and graphic shapes on packaging for dog and cat food. Today, however, these companies can complement this process by also verifying the presence of a dog or cat image on the packaging using deep learning vision software.

Once upon a time, color vision technology was limited to large manufacturers with big budgets and lots of in-house technical expertise. But, recent advancements in cameras, lighting and software have made color vision more affordable, less complex and easier to use on assembly lines.

In many automotive parts, a small defect can cause big problems. This explains why Tier 1 suppliers increasingly use machine vision to inspect parts used for steering, air bags, seat belts, brakes, electronic controls and exhaust.

Ordinarily, parts are presented to a robot for pick up at fixed locations, the escapement of a feeder bowl, for example, or the pockets of a thermoformed tray. To save space and eliminate the cost of trays and feeders, manufacturers would like a robot to pick randomly oriented parts out of a bin, box or tote.

Semiconductor device fabrication is a complex, multistep process involving both photolithographic and chemical techniques.