This higher level of AI development is riding on the wave of large scale investments in cloud computing and IoT accomplished through the wave of digitalization across all industries. With unprecedented amounts of data being gathered every day and computing power becoming virtually limitless – the need for machines that can mine this data for insights became more apparent.
By applying advanced AI technologies such as machine learning and cognitive services against the data coming in from the manufacturing process, you now have a value-added layer of insight into your data. This allows you to improve operational efficiencies, speed production, optimize equipment performance, minimize waste and reduce maintenance costs.
By running machine learning algorithms against these huge data sets, organizations were able to effectively coach their systems to look for specific data patterns and create a new layer of value that is gained from gathering and analyzing production data. Based on these insights, companies can optimize operations, production speed, equipment performance and scrap rates.
IoT acceptance fueling the rise of AI
Even though manufacturers recognize that AI is capable of driving competitive advantage, many are still reluctant to put a plan in place.
In a report published by MIT and BCG, the 3,000 manufacturing executives surveyed overwhelmingly (85%) agreed that AI will help their companies secure a competitive advantage. However, there was a significant gap between the number of executives that recognize the business value and the number of companies with an AI strategy in place (39%).
What’s also worth mentioning is that a lot of this is due to the lack of strategy companies still have in regards to their data collection and analytics. The AI we’re talking about here is, of course, not the fully autonomous AI of SciFi literature. The “pragmatic AI” that we can employ today is not inherently smart – in other words, it’s only as good as the data that it we allow it to run against.
Still, industry experts are anticipating an increase in the number of organizations to adopt AI as its prerequisites – such as IoT sensors and data analytics become more ubiquitous. According to IDC estimates, the AI market is expected to grow to more than $47 billion by 2020. By this time, an estimated 50 percent of leading companies will be employing AI and advanced analytics for production planning and demand forecasts.
Big Data Powering AI
As more companies are looking to go down the road of digitalization, Microsoft is constantly helping support this shift. With the advancement of intelligent edge and cloud computing power, we are one step closer to achieving smart manufacturing with production machines that can make autonomous decisions and talk to each other to prevent and fix issues. This approach to AI is centered on harnessing the value of big data to power advanced algorithms to enhance and complement the human ability to learn and understand.