Robotics and Autonomous Systems (RAS) are a key technological component of Industry 4.0, or the fourth industrial revolution, and are becoming increasingly significant for the economy. RAS technologies have broad-reaching effects on the economy and could present important opportunities for businesses looking to cut costs or boost efficiency.
RAS are machines and physical systems capable of acting without the intervention of a human being by observing, making decisions, and adjusting to their surroundings. RAS applications can comprehend what is occurring in their operational space and adapt their behavior to specific situations with varying degrees of decision-making autonomy, in contrast to more conventional machines with a single, predetermined purpose.
RAS has the potential to have a significant economic impact: by 2025, it is predicted that advanced robotics will have an annual global economic impact of between $1.7 and $4.5 trillion (McKinsey, 2013). More recent estimates indicate that increasing robot installations by 30% above the baseline could increase global economic output by $4.9 trillion annually by 2030. (Oxford Economics, 2019). These numbers show the size of the potential RAS opportunity, even though estimates of future impacts are, by their very nature, surrounded by considerable uncertainty.
Let’s now find out some of the key economic impacts of RAS across sectors:
According to studies, the strongest adoption of RAS on current trends is anticipated in warehouse logistics. According to estimates, the number of robots in the warehouse logistics sector will increase from 3.3 per million hours worked in 2020 to 27.2 over the next five years, 147.8 over the following ten years, and 346.7 by 2035. The quantitative analysis for this study’s findings indicates that uptake of this size could result in labor productivity gains of about 23.3% above baseline and a potential 14.4% increase in GVA by 2035.
RAS in the logistics industry includes picking, picking, and sorting items from storage, for example. Large portions of warehouses can be automated in RAS-equipped warehouses under the control of robots, greatly enhancing warehouse productivity and efficiency. RAS can be used to automate the packaging process in the logistics supply chain as well as in the broader logistics industry, for instance, through autonomous vehicles or last-mile delivery using drones (though challenges such as regulations on airspace, package weights, and the low margins in the industry remain).
Food & drink manufacturing
A rise in RAS adoption may also have significant advantages for the food and beverage industry. The variability of food items has made it difficult for RAS to grip and handle them, so automation levels remain lower than in other manufacturing sectors like the automotive industry, even though the sector already experiences higher levels of automation than some other chosen sectors (except warehouse logistics). This is changing due to advancements in soft robotics, and RAS adoption in the food and beverage manufacturing industry is rising. According to estimates, the number of robots in the food and beverage manufacturing sector will rise from 1.6 robots per million hours worked in 2020 to 6.9 in 2025, 34.1 by 2030, and 82.3 by 2035. Compared to the warehouse logistics segment, associated economic impacts are considered less significant. By 2035, productivity is anticipated to rise by about 4.6% relative to the baseline, while GVA is anticipated to rise by about 3.0% relative to the baseline.
RAS can be used to produce food and beverages to automate the picking, packaging, and preparation of food items. Advanced grippers that enable swift but delicate handling of food products like soft fruit and vegetables are another RAS application. Agriculture and the sector both share overlaps with the food and beverage services. ‘Traditional’ industrial robots are anticipated to play a significant role in the manufacturing industry despite the rise of RAS use-cases. By 2030, it is predicted that a third of all robot shipments to the UK’s food and beverage industry will be industrial robots.
Energy & infrastructure
By 2025, it is anticipated that the energy and infrastructure sectors will only gradually adopt RAS, with robot density remaining below three robots per million hours worked. However, this will be predicted to increase to 12.2 by 2030 and 22.9 by 2035. As a result, it is predicted that associated productivity impacts will be relatively minor, amounting to about 1.3% in comparison to baseline by 2035. By 2035, it is predicted that this will have effects on GVA that are 1% greater than the baseline.
Repair and upkeep of infrastructure assets like pipes, cables, and roads, as well as in challenging or hazardous locations, are use cases in the energy and infrastructure sectors. These include height-related inspections (such as towers or bridges) and maintenance tasks carried out in harsh environments (such as deep-sea oil pipelines, offshore wind farms, and oil rigs), all of which increase worker safety.
Robot density is predicted to rise later in agriculture, remaining below 1.0 robots per million hours of work by 2025, rising to about 8.0 robots per million hours by 2030, and then rising to 21.6 robots per million hours of work by 2035. By 2035, associated productivity increases are projected to be in the range of 0.9% compared to baseline, resulting in an estimated 0.7% increase in GVA compared to baseline.
Along with dairy farming, which is already highly automated, RAS applications in the agricultural sector include crop harvesting and fruit picking robots, weeding and phenotyping, precision agriculture, and use cases in wider livestock management. The use of pesticides, herbicides, and fertilizers, which have well-documented detrimental effects on ecosystems and biodiversity, can be reduced by adopting RAS in agriculture while lowering greenhouse gas emissions. Synergies with improvements in other technologies are also advantageous for use cases in the sector. For instance, the advantages of combining electrification (such as switching to electric motors for large diesel tractors), artificial intelligence, satellite tracking for earth observation, and the use of autonomous robots.
Construction, food & drink services, and health & social care
Under the current adoption trends, it is predicted that the effects on the construction, food, beverage, and health and social care sectors will continue to be relatively minor. By 2035, it is predicted that there will only be 3.0 robots per million hours of work in the construction industry, 6.0 in the food and beverage services industry, and 4.9 in the health and social care industry. By 2035, it is predicted that the corresponding labor productivity gains and GVA impacts for these sectors will only increase by 0.1% to 0.2% compared to the baseline. This suggests that roles requiring complex operations or working in settings with high levels of human interaction will be largely filled by people. In these settings, RAS may be more constrained to specialized, niche roles that support human labor.
Nevertheless, important use cases for RAS in these sectors exist; including:
- Robotic nursing, disinfectant robots, and assisted surgery are use cases in health and social care. Importantly, even though the economic effects on healthcare may be less significant, the application of RAS could result in significant improvements in patient outcomes, such as increased diagnostic accuracy, surgical precision, and a decrease in adverse patient outcomes. According to a study, more people die within 30 days of surgery than from HIV, malaria, and tuberculosis combined, at least 4.2 million people worldwide per year (2.97 million deaths). Similarly, numerous use cases in nursing and social care where RAS can enhance patient experiences. For instance, by assisting with patient lifting, appointment scheduling, vital sign monitoring, and new patient care forms, RAS can lessen the burden on caregivers and nurses.
- Robots could be used in the construction industry for a variety of tasks, including the demolition of buildings, site surveying, and mapping. They could also assist workers in lifting heavy objects by using powered exoskeletons, improving accuracy, efficiency, and safety.
- Although less obvious, interesting use cases for RAS in the food and beverage industry include robot waiters and robots for food and beverage preparation. Applications of RAS in the service sector could be particularly advantageous in automating routine tasks (like baking, making sandwiches, etc.) and reducing the need for people to work in confined spaces (like kitchens and canteens). This area is perhaps especially relevant given the ongoing difficulties brought on by COVID-19 and the associated social distancing restrictions. The industry also intersects with and benefits from the larger food and beverage industry and the agricultural industry.