Resquest a demostration
Batch production is a process used in many industries, in which components or goods are produced in groups (lots). Each batch goes through a stage of the production process before moving on to the next stage. Some examples of batch production are the manufacture of food and beverages, pharmaceutical ingredients, purifying water, inks, paints and adhesives, and also the chemical desorption of gold from activated carbon.
Golden Batch was designed to help analyze your lots using information from PI System, relational databases and other data sources of your operation to find the so-called Golden Batch, this being the ideal batch against which it is compared to all other lots . The best way to do this is to use reports that can allow operators and supervisors to receive real-time information about the current lot and allow comparison with the golden lot or any other lot for the shift / day / month.
Golden Batch uses the PI system to collect real-time information about your batch process and associate it with automatically generated events. This information could be received from automation systems, text files, relational databases, manual data entry, other data sources or advanced processing. This solution uses a typical infrastructure of the PI system, provides PI Datalink reports that determines the performance of the process in real time compared to the Golden Batch, also historical information that helps operational users identify the best performance over a period of time, detect anomalies, improve process quality. In addition, the information can be displayed in PI Processbook, PI Coresight (PI Vision), Power BI reports. Finally, going further, the KPI calculation could be added and displayed in the form of dashboards and analytics.
With Golden Batch, customers need the necessary information about their lots in real time, as well as the quantity of each consumable used, the duration, the differences between the current and the golden lot. The idea behind this solution is to improve efficiency, reduce costs, present historical and real-time information that allows the identification and correction of operational defects, support a process of continuous improvement within the organization with reliable information. In addition, it allows to identify an ideal model for the batch process in which the formulas, the proportions and all the automation equipment work in perfect synchronization and remember the correct quantity of each component. The objective of this is that when the same batch process must be executed in a different location, each part of the model is understood and can be reproduced to match the ideal configuration.