Disruptions to supply chains have made major headlines in the past year with high freight rates, container capacity shortages, and port closures throwing the movement of goods into turmoil. Organizations that once sought efficiency through the stocking of just-in-time (JIT) inventory are now seeking to increase resiliency instead. As a result, digital supply chain software that can assist companies in demand forecasting, parallel planning, and overall optimization have seen growing adoption.
Following in the wake of this shift, several trends have emerged: Artificial intelligence (AI) and machine learning have become more common as supply chain planners seek to leverage more predictive value from large quantities of data, often without being able to enlist highly trained data scientists; cloud-based software offerings have expanded in order to lower costs, increase scalability, and integrate data from disparate sources, offering end-users a single source of truth; and integration between supply chain software and manufacturing execution systems (MES) has seen an uptick as granular, plant-level data is sought to give planners more accurate insight into a facility’s actual capabilities.
Many of these developments converge in a recent announcement from enterprise integration and industrial internet of things (IIoT) platform provider Software AG. The company’s TrendMiner software, which enables operators in process and other industries to analyze, predict, and optimize performance using sensor-generated time-series data, will now be available via SAP’s S/4HANA cloud-based enterprise resource planning (ERP) system and its SAP Digital Manufacturing Cloud cloud-based MES system, allowing for standard integrations with either. In addition, TrendMiner is compatible with various IIoT software stacks—including Software AG’s Cumulocity IoT—and an assortment of historians, including OSIsoft PI, Yokogawa Exaquantum, AspenTech IP.21, Honeywell PHD, GE Proficy Historian, and Wonderware InSQL.
According to Software AG, data from TrendMiner can be used to predict product quality across locations in advance of actual production, yielding better supply chain decision making. Moreover, by making product quality metrics available to their supply chain partners, end-users may be able to attain a competitive advantage by making themselves a more appealing procurement option.
Like many cloud-based software products, TrendMiner also allows end-users to leverage the data stored in SAP’s cloud to develop predictive machine learning algorithms that otherwise would be beyond their scope.