This piece was originally published on 08.07.17 and updated on 01.16.19.
According to ARK’s research, industrial robot1 costs will drop by 50-60%, to levels much lower than most analysts now anticipate, by 2025. Combined with advances in machine learning and computer vision, this drop in costs should cause an inflection point in the demand for robots as they infiltrate new industries with more provocative use cases. These factors are behind ARK’s forecast for 3.4 million robot unit sales in 2025, up from roughly 380,000 in 2017.
ARK anticipates that industrial robots will cost less than $11,000 per unit, much less than the Boston Consulting Group’s (BCG’s) expectation of roughly $24,000, by 2025, as shown above.2 Fundamental to our analysis is Wright’s Law: that is, for every cumulative doubling in number of units produced, costs will decline by a consistent percentage.3 In the robotics space, that cost decline – known as the learning rate – has been roughly 50%. Based on historical production and pricing data, ARK’s application of Wright’s Law suggests that BCG’s expectations are far too conservative.
While BCG 4 anticipates that the historical price trajectory of robots will diminish and stall in response to underlying material costs, it fails to anticipate and incorporate innovations evolving in manufacturing. 3D printing, for example, should reduce the use and weight of materials dramatically, up to 75%, without diminishing performance.5
The history of publicly traded robotics companies suggests that the industry has benefited significantly from manufacturing efficiency gains. As shown below, while robot prices have dropped by roughly 50% during the past decade, the industry’s gross margins have been relatively stable. During the next few years, this margin structure is unlikely to change significantly.
As robots have become cheaper and easier not only to train but also to integrate into traditional production processes, growth in the demand for industrial robots has accelerated in two stages since 2000. The third stage of accelerated growth could be under way now, as shown below. Prior to 2000, lower prices caused the total industrial robot market to shrink. Today, top line growth is accelerating in response to declining costs.
While ARK’s forecast for industrial robot sales is based on the price elasticity of demand during this decade, continued increases in the capability of robots, perhaps driven by artificial intelligence, could boost sales even further. Since 2015, robots have improved eightfold in their ability to pick and place items, approaching human performance, as shown below. As robots continue to decrease in cost and the use cases broaden into new industries, ARK forecasts that robot unit sales will scale from roughly 380,000 in 2017 to 3.4 million in 2025, as shown in the chart at the bottom.
As computer vision, machine learning, and new sensing capabilities impact robots, not only will their performance improve but other costs associated with installation and integration should fall as well. For example, they will require little or no human programming and will be able to roam freely instead of being trapped in safety cages and by other barriers. As a result, the industrial robot market will hit many more tipping points, surprising on the high side of expectations, perhaps dramatically, during the next few decades.6
- ARK is referring to industrial robots as defined by ISO 8373:2012: An automatically controlled, reprogrammable, multipurpose manipulator programmable in three or more axes, which can be either fixed in place or mobile for use in industrial automation applications. https://ifr.org/img/office/Industrial_Robots_2016_Chapter_1_2.pdf ↩
- Constant 2017 dollar ↩
- http://spectrum.ieee.org/tech-talk/at-work/test-and-measurement/wrights-law-edges-out-moores-law-in-predicting-technology-development ↩
- https://www.bcgperspectives.com/content/articles/lean-manufacturing-innovation-robots-redefine-competitiveness/ ↩
- https://research.ark-invest.com/3d-printing-white-paper ↩
- https://ark-invest.com/research/collaborative-robots ↩
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