Automotive is one of the most highly-automated industries in the world, and it has been a leading force in expanding the use of industrial automation for decades. In fact, the first industrial robot in production was a Unimation UNIMATE that GM installed on a die-casting line in New Jersey in 1962.
Developments such as the Stanford Arm and MIT’s Silver Arm that were initially deployed in automotive led to widespread proliferation of industrial automation in the US auto industry throughout the 1970s and 1980s.
Industrial automation continues to grow within the automotive industry. According to the International Federation of Robotics, the automotive industry accounted for 56% of all North American industrial robotics orders in 2016, and 35% of all new robotic sales globally that year.
The integration of automation, computers, and electronics in manufacturing is only going to grow as automakers and suppliers build the “smart” cyber-physical systems that are commonly known as Industry 4.0. These systems create a virtual network between automation, advanced processes, and humans where Big Data analytics and real-time data exchange can lead to even lower costs, more significant improvements in productivity and quality, and more agile and resilient manufacturing systems. The result is production systems with near-zero downtime, advanced lean production, and integrated global production networks.
In addition to factory automation that performs physically demanding or dangerous work once done by humans, some robotics can be used to augment a human’s ability to execute a production task more efficiently or with greater precision. Collaborative robots, also known as “cobots,” are robotic arms explicitly designed to interact with humans in a production environment. Cobots have shorter armatures and automatic shut-off when touched, so they are safer to work in small spaces near workers.
More widespread use of factory automation can have employment consequences. It is not possible to stop the march of progress. However, thoughtful technology deployment planning considers the human implications at the onset as the nature of manufacturing jobs is reshaped and changed. New technology also creates demand for new positions—notably in data analytics that manufacturers can use to improve processes further.
Automation that is already pervasive at the automaker and top-tier supplier levels is spreading to smaller firms in the automotive supply chain. Broader adoption of digital manufacturing technologies enable integrated Industry 4.0 systems and will allow US manufacturers to remain globally competitive.