Introduction to Industrial AI
Artificial Intelligence (AI) is no longer a buzzword for the industrial sectors as it is becoming more widely adopted in the new era of Industry 4.0. Industrial AI is the use of AI in industrial use cases in any physical operations such as movement of goods, supply chain optimization, manufacturing of products, and factory automation. Industrial AI is focused on assisting an organization in monitoring, optimizing, or controlling the behavior of various activities and systems in order to improve efficiency and performance. As new advances in AI are incorporated to augment our industrial machinery and manufacturing processes with dynamic capabilities, industrial assets will become more cognitive and autonomous.
Devices and technology connected over the Internet of Things (IoT) can monitor and measure data in real-time. The data is transmitted, stored, and can be retrieved at any time, creating efficiency in manufacturing and distribution networks. Data is continuously generated, processed, and analyzed — and the role of AI in this process makes the future look both promising and exciting in the industrial sector. According to a research report, the AI adoption rate in industrial settings has increased from 19% to 31% in slightly more than two years, and estimated that the IoT market will reach $102.2 billion by 2026.
Why is it important for industrial companies to adopt AI
While AI has been around for decades, today’s intelligent machines are a far cry from the data-based algorithms of the past. AI is making inroads everywhere, perhaps that’s why it’s becoming harder to imagine living without it. Industrial professionals can now realize tremendous competitive advantages by honing these strategies and building digital capabilities with an Industrial AI platform.
By leveraging the power of AI, industrial plants are better able to increase profitability, improve business continuity and resiliency, and position themselves for growth in the years to come. The potential and promise of digitalization are accelerating, speeding up the velocity of change at every production facility. AI-driven systems can automate and reinvent fundamental industrial processes, including product development and supply chain operations.
How AI is applied across different industries
- Oil & Gas
AI is proven to be a great facilitator for oil and gas operations, with a variety of uses. According to GlobalData’s report, AI-assisted predictive maintenance tools offer the oil and gas sector operational and financial fluidity. These include using Computer Vision to interpret seismic and subsurface data more quickly, as well as decreasing the downtime of equipment through predictive maintenance. In fact, predictive maintenance has been known to bring in tremendous time and cost savings for oil and gas businesses. In one case, a major oil and gas business was successful in cutting the time it took to revive a well by as much as 83% and the cost of alternative fuel by $20,000 per day. Imagine the amount of savings on a yearly basis.
Since the introduction of AI into the Oil and Gas industry, there has been a boom in the demand for intelligent machines that are capable of making accurate, automated decisions. Companies can gain a better understanding of their equipment’s health and avoid costly unplanned downtime by using predictive maintenance. Furthermore, a competent predictive maintenance program would result in a more effective maintenance schedule and attain higher-level operational excellence. Therefore, adopting AI solutions bring a wealth of benefits for oil and gas companies, including reducing costs, increasing uptime, and improving productivity.
Demand for manufactured products continues to increase, but plant managers and maintenance professionals still struggle to keep pace with the pressure to improve production efficiency. Traditional methods of preventing machine downtime are labour-intensive and often lead to unnecessary maintenance tasks. In fact, the world’s largest manufacturers lose almost $1 trillion a year to machine failures.
A case in point is by leveraging AI to enable smart industrial production, real-time analytics, and predictive maintenance. To minimize unexpected downtime, manufacturers are turning to predictive maintenance strategies that use real-time data to predict machine failures and prevent them from happening.
AI can also enable manufacturers to make informed decisions about the interplay of data and processes, which helps to produce components that are high quality and cost-effective. Consumers now expect products that are safe, reliable, and lower costs.
In a world where customer demands are constantly changing, it is equally important for organisations to be able to respond rapidly to changes in order to remain competitive. Downturns in demand can be devastating as they can have a negative impact on the overall performance of an organisation. However, a response to demand volatility is possible with AI by using Machine Learning algorithms to predict changes in consumer demand as accurately as possible. These algorithms can automatically recognise patterns, identify complicated relationships in large datasets, and capture signals for demand fluctuation.
Through the use of AI, manufacturers can more easily meet customer demands while creating the automation needed to achieve the highest level of efficiency of their production line.
Did you know that shipping transport provides an important trade network that enables 90% of world trade? The maritime industry is considered to be one of the most complicated and challenging sectors in the world. There are many different factors at play, such as the weather, technology, economic conditions, and more. Because of all these uncertainties, it has long relied on manual efforts and human expertise – which is why ships seldom stop running if they are in need of maintenance. For decades, the maritime industry has been slow to embrace new technologies and innovations.
However, the recent global pandemic has significantly impacted the shipping supply chain. AI is now starting to make its way into the sector, through the introduction of autonomous systems, more efficient processes, and better safety standards. As shippers struggle to mitigate disruptions and rising costs, digitalization is a key solution for modernizing shipping operations.
The benefits of digitalization and data science include increased efficiency in scheduling maintenance and repairs, and better fuel management to save on consumption and operational costs. It also allows companies to have full clarity on their vessel’s condition using predictive analytics to prevent unexpected downtime, and the ability to prioritize maintenance based on the severity of the issue. AI also enhances the overall navigational ability of a vessel. AI-powered navigational devices are becoming more powerful and reliable as they give vessels access to real-time weather, sea, and traffic conditions as well as provide advanced weather forecasting. Using the vessel’s data, machine learning systems help optimize routes to reduce fuel usage.
By digitizing vessels with advanced data science technology, operators can not only increase profitability by saving lost hours of productivity due to unplanned maintenance but also create a safer environment for their crew.
Studies have shown that large-scale projects can experience budget overruns of up to 80%, and 45% of the construction professionals claim that they spend more time than expected on non-productive tasks.
With the help of AI, companies can put that to a stop. Construction companies have benefitted from AI in a variety of ways, including tackling some of the industry’s most challenging problems, such as safety concerns, labour shortages, and cost and schedule overruns. Construction managers across the globe are increasingly finding value with AI and cognitive technologies to help automate many of the mundane but essential tasks of running their operations.
By using remote ‘Smart Monitoring’ for surveillance of worksites and ensuring the safety of site workers, companies are also able to gain 24/7 visibility to their worksites and receive real-time actionable insights on safety compliance and precautionary notifications about potential safety lapses. From optimizing work schedules to improving workplace safety to keeping a secure watch on construction facilities, AI in the construction industry is already proving its value.
Leading mining companies are currently facing a long list of challenges due to the COVID-19 pandemic, including the increase in the fatality and injury rates, decrease in productivity rates, and project delays. While the human contribution to the mining industry is undeniable, McKinsey estimates that by 2035, the age of smart mining, achieved through AI will save mineral raw materials producers between $290 billion and $390 billion annually.
AI continues to revolutionize the mining industry by positively impacting efficiency and global costs. The mining industry is one of the most dangerous sectors in the world. According to a study by the Bureau of Mines, 85% of all accidents can be attributed to at least one human error. In response to this, AI is being used to prevent injuries and fatalities by maintaining an increased level of safety at mine sites. Real-time monitoring of production sites enables stakeholders to make more informed decisions regarding their workflows. This allows for increased efficiency in site operations and workflow management, as well as minimized disruption during routine production cycles. In addition, replacing repetitive jobs with automated solutions dramatically increases productivity. AI is also used in other areas such as remote sensing data collection, which provides valuable insights into soil material and mineral presence at mining sites. These improvements potentially pave the way toward sustainable development goals for large mining companies around the world.
AI is the inevitable for the industrial sector
To sum up, AI has made its foray into our lives and is becoming the best tool at our disposal to identify patterns and discover trends. It also helps industrial companies process large volumes of data, extracting meaningful insights and delivering unprecedented levels of efficiency. As AI continues to advance, automation will become even more widespread, impacting every industry and every job role in some way. It is an inevitable, and it is best for industrial companies to quickly adopt it to remain competitive.
Here at Groundup.ai, we have extensive expertise in the field of AI and predictive analytics. These technologies are highly capable of supporting industrial companies to save time, save cost, and even save lives. Come and have a chat with us to find out more details.