Conditioning Data for Automated Business Processes Using Sigmafine – Houston

To improve their facility operations, companies must optimize their business processes and automation facilitates this change and increases the depth and frequency of their business analysis. Commonly, industrial business processes require automatic processing of large amounts of information and contextualizing these to the specific analysis. Specifically, unit operations can be monitored using conservation principles to better understand the performance of assets and to anticipate any operational issues before they become critical. To implement a fully automated analysis, Sigmafine can be configured to run unattended to track asset performance, track properties and material compositions at higher frequencies (e.g., every hour or less). These presentation discusses the main issues faced during the automation of a Sigmafine system, such as unavailability of data, manual data, interfacing with external systems and implementation of business rules. All of these sources of information have their own levels of data uncertainty and availability, which makes the automation of data reconciliation challenging, but not impossible if the right approach is used. The use of best practices produce a more resilient model to face the automation challenge, even when conditions of poor quality of inputs are found. Some case studies of Sigmafine automation will discussed to demonstrate the concepts as they are applied to production accounting, energy efficiency, material property tracking, and batch tracking.