Beyond Consistency in Automation Maturity Adoption

Posted: June 09, 2021 

To be competitive in today’s data-driven marketplace, organizations are implementing a variety of tactics for digital transformation but may struggle in finding the most cost effective way forward. Orchestrating the endeavor requires careful plotting and experience to pull off successfully. Despite best efforts, many quests for digital transformation fail without appropriate planning and clearly defined expectations.

Understanding your organization’s current automation maturity level helps guide an effective digital transformation plan, and you can find out where you stand by taking a complimentary Automation Maturity Assessment:

In case you missed it, you can review some benefits of digital transformation in our automation maturity series introduction.

Data is only as Good as the Insight Generated

Does your organization share some operational data, but lacks the ability to provide visibility to corporate business and mobile users outside the control network? Have you standardized consistent automation control sequences across your facility, but not yet determined how to gain deep process insights and perform equipment root cause analysis? If the answer to either of these questions is “yes”, your company is likely at the ‘consistent’ level.

Your organization has embraced the need for centralized control and data acquisition across enterprise processes so staff can operate individual control loops based on plantwide context, rather than in a vacuum. Because automation programming and operational procedures are standardized across the plant, the user experience is consistent—even among systems created by different manufacturers—enabling simpler system training and better operational decision-making.

However, without the ability to easily extract insights from data, greater optimization throughout the value chain is difficult and complete awareness of plant equipment conditions is not possible. Deep analysis is required to identify all opportunities, avoid the need for rework, and minimize unplanned downtime. While data from the central historian can be manually analyzed, this takes a significant amount of effort by highly skilled engineers and technicians and can end up costing more in terms of time than the generated insights are worth. A more sophisticated approach is called for.

Organizations at the consistent level typically execute well-established procedures for process data sharing and operational decision-making, but natural boundaries exist at the extent of the control network. To measure production bottom line and maximize efficiency, business personnel must also be able to securely access operational and real-time process data, to ensure goal alignment across the company.

To mitigate the risk of equipment failure, many organizations at this level invoke conservative preventive maintenance programs, but this drives maintenance costs up due to servicing equipment before it is necessary. By utilizing software to reveal process and equipment health insights, companies can utilize predictive maintenance to alert staff when equipment performance degradation is first detected. This provides an early warning of equipment requiring service, typically ahead of failure in operation.

Without mechanisms for generating insights, it is difficult to properly interpret the reasons for certain process alarms or recognize impending failures. Sometimes, cryptic alarms are inaccurately classified as ‘nuisances’ and ignored until a system fails outright, whereas with an insight-generation mechanism, staff are often able to ascribe and address the cause of the alarm.

Making Sense of the Data

While these challenges are difficult to overcome left to in-house processes. AVEVA can help with:

• Standardization and change propagation.
• Process and equipment insight generation.
• Predictive maintenance.
• Intuitive alarm management.
• Process relational context.
• Improving remote visibility.
• Creating transparency across the value chain.

Are your organization’s standards and procedures positioned to move forward from ‘consistent’ to ‘reinforced’, or are you just rounding the ‘prepared’ bend of the journey?