Ever since IBM rolled out the world’s first mainframe computer in the 1950s, engineers and manufacturers in information technology (IT) have been pushing the boundaries of possibility through microelectronics and software. However, modern computer capabilities did not surface in the industrial operations technology (OT) space until recently, as machine builders began to realize the benefits IT can provide for efficiency and productivity.
A decade ago, digitalization and advanced analytics in OT environments gave adopters a leg up on their competitors. But today, manufacturers cannot keep up unless they lean on IT advances. These advances address challenges for plants, such as difficulty employing knowledgeable personnel, unexpected equipment failures and lack of operational insights for increasing efficiency.
Though many advances in IT have already found their way into OT deployments, artificial intelligence (AI) carries unrealized potential to aid machine builders in achieving profitability, maintaining efficiency and minimizing downtime. Although many know AI can assist in the production life cycle, it can be difficult determining where to start. This article describes benefits of AI-enabled edge devices by covering three areas where many machine builders can use them to improve their processes — predictive maintenance, quality assurance and robotics.
Data processing problems
In manufacturing, AI algorithms examine many iterations of a process, capturing its quantitative properties. Matched with example outcomes of pass and fail, the algorithms begin to correlate properties with their respective outcomes. Over time, AI can define and predict outcomes based on the quantitative properties captured during production more accurately (see Figure 1).