Why do manufacturers automate production? Why do they spend millions each year on new equipment and software? Those questions are pretty straight forward, and the answers seem obvious. Clearly automation allows manufacturers to improve the control of complex and business-critical processes. Surely automation reduces the cost of operation by enhancing production output while reducing production-related waste. But if that’s the case, then why do staff at automated facilities choose to operate production in any mode other than “auto”?
Two metrics that shed light on this topic are Mode Changes – especially Manual Mode – and Percent Time in Normal. Mode Changes monitors the number of interventions to a given loop that 1) involve a change to the controller’s mode and 2) directly affect the Controller Output. In a related fashion Percent Time in Normal calculates the amount of time that the loop operates in its intended or “design” mode. Each helps to identify control loops that are subject to operator intervention. Whether due to inconsistent sensor readings, high variability due to poor mechanics, or poor controller tuning, these metrics offer valuable insight into the frequency and duration of those interventions.
Confidence Game
Lots of things can go wrong at a typical production facility. Production processes are inherently dynamic and they can be difficult to control. Some are just plain dangerous. One reason why production staff choose to operate processes in a mode other than auto is a lack of confidence in the process and its associated instrumentation. If a valve is sticky or a sensor is worn out, then both control and confidence can be compromised. Production staff regularly cite a lack of confidence when choosing to operate processes manually. More often than not their lack of confidence is a symptom of a bigger issue.
Stepping Down
Lost confidence shouldn’t be equated strictly with manual operation. Plenty of processes that are running in automatic are designed to operate in an alternate setting. Consider one or more loops intended for operation in remote cascade in conjunction with an MPC solution. If the MPC solution’s models are outdated and staff lack confidence in its ability maintain safe operation, then they may choose to step it down and operate the loops in automatic mode.
Learning Curve
In the complex world of process automation the answer may simply be to provide more education. Even a modest sized production facility operates hundreds of PID control loops using a thousand or more different instruments. Such an expanse of systems and processes can be overwhelming. On the surface manual operation may appear like the right approach for production staff that haven’t been thoroughly trained.
Among others, the goals of automation are to improve control and to increase profitability. Technologies that monitor plant-wide performance can help process manufacturers to achieve those goals by identifying individual control loops that are not operating as intended. Metrics such as Mode Changes and Percent Time in Normal are tools that quantify the frequency and the duration of those interventions.
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