Revolutionizing business processes with AI and Machine Learning
At AVEVA, we’ve been banging the drum for some time regarding the impact artificial intelligence (AI) and machine learning (ML) technologies can have on our clients’ businesses. In fact, it’s something we recently wrote a whitepaper on - you can find the Digital Transformation whitepaper here.
An article in Bloomberg commented on the hype around AI, arguing that ‘it’s a cliché that you shouldn’t judge a book by its cover, but it’s doubly true in the age of AI’. The excitement around AI and other emerging technologies has led to AI becoming increasingly hyped up – something that is full of ideas and promise, but tricky to execute in practice. It’s a challenge we’re seeing a lot. For example, we’ve seen several companies adopt these capabilities, often announcing they intend to revolutionize operations and output with such technologies but then failing to deliver.
Why? Because with so many potential applications for AI and ML it can be daunting to identify opportunities for technology adoption that can demonstrate real and quantifiable return on investment. That’s where AVEVA comes in.
Pulling clients from pilot purgatory
Many industries, including Oil & Gas and Food Processing, have reached a sticking point in their adoption of AI and ML technologies, from disjointed data to limited business insights. This is usually from unproven start-up companies delivering some type of ‘house of cards’ technology, placing a flashy exterior around it and then relying on a customer to act as a development partner to create foundational value for it. This is the primary problem because customers are not looking for prototype and unproven software to run their industrial operations.
These poorly planned projects are putting customers in the position of pilot purgatory, with continuous feature creep and a regular rollout of new and untested beta versions of software. This practice of the never-ending pilot project is driving a reluctance for customers to then engage further with innovative companies who are truly driving digital transformation in their sector with proven AI and ML technology.
Innovation with direction
Being able to demonstrate proof points is key to overcoming this scenario - working with a supplier that can show how AI and ML technologies are real and are exactly like we’d imagine them to be. Here’s an example of how we leveraged Artificial Intelligence to help seamlessly drive scheduling decisions for production schedulers, but there are many other examples.
For instance, many clients use AI to track customer interests and needs because it can provide detailed, real-time insights on machinery operations, exposing new insights that humans cannot necessarily spot. These are insights that can drive huge impact on the bottom line of a business.
The value of AI and ML is best demonstrated in the manufacturing sector in process and batch automation. For example, customers in the sector are using AI to figure out how to optimize processes to achieve higher production yields and improve production quality. In the food and beverage sector too, AI is being used to monitor production line oven temperatures, flagging anomalies - including moisture, stack height and color - in a continually optimized process to reach the coveted golden batch.
These technologies are also helping with predictive maintenance in terms of monitoring the behavior of equipment and improving operational safety and asset reliability. A combination of both AI and ML is fused together to create predictive and prescriptive maintenance, which can reduce maintenance costs by 30% and reduce unplanned downtime by 25%. For example, using AVEVA Predictive Analytics resulted in Tata Power having increased equipment reliability and performance and better maintenance planning and cost control.
Where AI is used to spot anomalies in the behavior of assets, recommended solutions are prescribed to remediate potential equipment failure helping to reduce pressure on O&M costs, improving safety, and reducing unplanned shutdowns.
Let AVEVA transform your AI and ML journey
AI, ML and predictive maintenance technologies are enabling new connections to be made within the production line, offering new insights and suggestions for future operations. But this is just the tip of the iceberg.
We know that every need of every business is different. That’s why we go to extraordinary lengths to guide our customers through every step of their AI and ML journey, which can lead to a 25% improvement in the efficiency of their workforce. To learn more about how companies are using artificial intelligence to improve their business operations view the webinars below or download the Predictive Asset Analytics infographic.
Andrew McCloskey is Chief Technology Officer and Head of Research and Development at AVEVA. Andrew holds a bachelor’s degree in Aerospace Engineering from California Polytechnic University Pomona. He attended USC for graduate studies, and has taught university level courses in software development.