The multitude of regulations that need to be adhered to in the production of food and beverages represent a considerable challenge. In an environment where one small recipe change can result in costly product waste, the highest level of product and production process quality must be achieved in accordance with the standards set by bodies such as the FDA. versiondog and AutoSave provide a single, central data management system - for the entire production facility, and at the click of a button - a safeguard for your data, proof of quality, project documentation and change management.
End-to-end documentation of all manufacturing process
FDA 21 CRF 11 support and Documentation for audits
Increased security and less downtime
Thanks to versiondog, we are able to rapidly localise errors and get the plant back up and running again. The wonderful thing about versiondog is that fact that you know when exactly a particular change was made, who made it, and why it was made.
A firefighting mentality is one where organizations are frantically rushing to solve unexpected problems, making impulsive decisions, and applying short term “band-aid” solutions to restore production as quickly as possible. Production plants are particularly susceptible to this mentality. Why? Plants are up against a wide variety of risks to productivity and product quality. Human error, equipment failure, cyber attack, and natural disaster all have the potential to cause significant downtime. When every minute of downtime can cost thousands, it is critical to resume production as quickly as possible.
Nevertheless, very few production plants are adequately prepared for worst-case scenarios or even everyday issues. A proactive approach to data management for automation could save time, money, and effort.
This white paper will discuss how better data management can transform your industrial automation for increased productivity with fewer problems. First, it will explore the causes and concerns of a reactive “firefighting” approach to maintenance in automation. Then, it will propose data management tools and best practices to help break these habits.
