Abstract
Factories have employed automation for nearly 100 years. With the launch of Industry 4.0 in 2011, operations have expanded their use of robots on an unprecedented scale. As of 2017, there were roughly 2 million industrial robots in use globally. By 2030, it's estimated that 20 million manufacturing jobs around the world could be replaced by robots. Yet, substantial hurdles remain before predicted level of automation can be realized. On the one hand, smart factories are almost exclusively multibillion-dollar enterprises. Their costs are simply too high for most manufacturers. On the other hand, intelligent machines are limited in what they can do because so many of the engineering tasks required to support them are still being done by people. Widespread use of automation requires expanding the use of artificial intelligence to manage data, create drawings, evaluate designs, and program machines.
TopIssues, Controversies, Problems
For all the time and money being spent on automation the technology isn’t without its fair share of problems. Chief among these are high costs and low flexibility. For example, the average price of a six axis robotic arm with an eight kilogram payload in 2018 was $25,000. After accounting for integration, safety, tooling, and programming, automation costs increase four to six times (Maw, 2018). This is a significant amount of money to spend on technology which is somewhat limited in scope. In 2016, the head of manufacturing at Mercedes voiced an all too common complaint about robots. “They can't deal with the degree of individualization and the many variants that we have today” (Abbosh et. al, 2019).
In light of automation’s challenges, there were only 237,000 industrial robots in operation across all of North America in 2015 (West, 2015). To put this number in perspective, that same year there were approximately 72 million people employed in North American factories. This works out to roughly 1 robot for every 300 workers. A heavy reliance on people over robots is expected to dramatically shift in the near future. By 2025, it’s predicted that one out of every four industrial tasks will performed by robots (Melanson, 2018). By 2030, 20 million manufacturing jobs around the world could be replaced by robots. (BBC, 2019). For automation to grow anywhere near its potential fundamental changes are needed.
Key Terms in this Chapter
Automation 4.0: Machines possess the ability to perform tasks as well as the engineering necessary to support those tasks without human involvement.
Coding: Use of a programming language to interface with a computer in order to guide performance of a machine.
CAE: Computer-aided engineering. Computer software capable of evaluating digital designs under simulated environments meant to match application dynamics and kinematics.
CAD: Computer-aided drafting. Computer software used to create, revise, or analysis digital designs.
Artificial Intelligence: Machines with the capability to respond to stimulation as humans with contemplation, judgment, and intention.
Industry 4.0: The fourth industrial revolution. The digital world is connected to the physical world through intelligent machines.
Smart Factory: A digitalized manufacturing environment where machines are able to self-improve processes.