Industrial executives and operators are faced daily with the challenge and pressure to do more with less and reduce their excessive resource consumption. There is immense potential for AI and machine learning technologies to help companies address these challenges, mitigate rising costs, and increase their profit margins. For example, within the beverage industry, there might be one process analyst responsible for maintaining assets for up to 12 different plants. With each plant, there may be five types of software systems that house the data, such as SCADA, ERP, CMMS, and others, within complex and aging on-premise environments.
As a result, industrial plant operators are making decisions based on years of on-the-job experience and clunky tools to conduct asset performance management. We help these process analysts extract data from their own systems, determine if it is viable to solve their problems, and then apply AI to analyze and provide a higher level of data intelligence. This lets them better track and deliver on their key performance indicators and goals. Due to the large volumes of readily available historical and real-time data within these systems and plants, AI also uncovers blind spots previously unknown to analysts because they've been unable to link all of this data together, building a bridge between the data and the business metrics, which is crucial. Cloud-based AI solutions let them make more informed decisions, providing benefits such as higher throughput efficiency and increased revenue retention, as well as extending the life of a plant’s assets.