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SETTING THE BENCHMARK

The Unmet Need for Low-Cost Lidar in Industrial Automation

by Peter Levinshteyn / July 21, 2021

Industry 4.0 and smart manufacturing are all the rage these days and for a good reason. Robotic and autonomous technology greatly enhance reliability, quality control, and cost savings, and more data means better insights on facility health and efficiency. One of the most critical factors in creating a 4.0 facility is utilizing sensor technology, specifically, low-cost industrial Light Detection and Ranging (lidar). However, Benchmark has found that the market for lidar has been controlled by the autonomous vehicle industry, which leverages high-end lidar for autonomous technology.

The lidar used in the autonomous vehicle industry is high-cost and includes many unnecessary features for industrial users. In addition, most manufacturers developing lidar are focused on the automotive industry, so industrial options are limited or nonexistent. This scenario is creating an unmet need for the complex industrial sector that Benchmark wants to help solve.

Benchmark has developed critical expertise in the design, engineering, test, and manufacturing of lidar technology, and we’ve served the industrial industry for more than 30 years. We understand our industrial customers and can help develop cost-effective lidar solutions that meet their specific needs.

In this white paper, we examine the state of lidar options in today’s marketplace and propose solutions to meet the requirements of the industrial sector. 

CLICK HERE TO ACCESS THE  WHITE PAPER

Manufacturing Complex Industrial Engineering

about the author

Peter Levinshteyn

A leader within Benchmark North American Engineering Services, Peter leads a team of 13 Electrical Engineers and 6 PCB Designers spread out between three Benchmark facilities in Minnesota. Peter has 20 years of experience in signal and power integrity performing analysis and measurements of memory and high-speed digital interfaces as well as power rails on printed circuit boards with microprocessors and FPGAs. Peter holds a Bachelor of Science degree in Electrical Engineering and a Master of Engineering degree in Computer Engineering from the University of Minnesota.