Besides meeting the demand for higher and higher quality, production line engineers & equipment suppliers also have to deal with rapidly increasing project complexity. As a result, the task of devising and maintaining a manual data-storage structure has become almost impossible. No matter how well thought out a system seems to be, confusion and lack of clarity can all too easily creep in. Further powerful arguments in favour of an effective data management system are heightened emphasis on IIoT technologies, the growing number of standard programming blocks and the importance of comprehensive process and delivery documentation. versiondog and AutoSave provide valuable support for production line engineers & equipment suppliers all the way from the project design phase to commissioning and customer acceptance.
Standard program block library management with usage list
Centralised data storage
End-to-end process documentation including indelible record of state at delivery and detailed comparisons for audit trail reports
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.