Talk to Me
Who done it?
By Bill Lydon, InTech, Chief Editor
Sometimes an old murder mystery novel or movie is referred to as a “who done it,” and when we have issues in automation, manufacturing, and production, we have the real-world equivalent. The plot of these novels and movies was for the good guys to find out who performed the murder. Throughout the movie the good guys uncover information and use these clues and their intuition to solve the mystery. The most powerful tools the good guys use are observation, questions, and validating information. These are good tools we all can use to understand who or what “done it” when faced with automation, manufacturing, and production problems and issues.
It is easy to jump to conclusions based on past experience or what obviously looks to be the problem. Many times at this point, it is good to step back and observe without judgment and ask, what is happening? As the great baseball coach Yogi Berra once stated, “You can observe a lot by just watching.” The most basic level of observation is the gathering of information by using our five senses: sight, smell, hearing, taste, and touch. Based on this information, we make qualitative and quantitative observations. As technical people, we tend to like quantitative information that is absolute. But both types of observations are valuable, and exploring qualitative observations can lead to uncovering information that is quantitative. An operator, for example, can tell us a production process is not running properly; this is generally a qualitative observation. We can then start looking at process data, running trend reports, and quantifying what is happening.
When problems are particularly difficult, we can make inferences that help explain an observation we have made. The inferences are based on past experiences and prior knowledge that help illustrate what is happening. Inferences are valuable, but in unusual situations, they become a velvet trap leading us to the wrong conclusions. Many times, we are strongly influenced by the last problem we solved and assume this one is similar. This is where it is valuable and instructive to validate information as we uncover it. I recall, for example, spending a great deal of time troubleshooting an automation problem and essentially going around in circles troubleshooting control loops. As it turned out, I was relying on sensor readings that should have been operating properly and accurately. Unfortunately, there was an issue with a sensor interface, resulting in bad measured data. After a considerable amount of time troubleshooting, I desperately started checking all the system components and identified the faulty sensor interface. The lesson is we need to be careful about the assumptions we make consciously and unconsciously when working on problems.
The popular fictional detective Sherlock Holmes’ companion, Dr. Watson, commented on a case, “This is indeed a mystery; what do you imagine it means?” Holmes replied, “I have no data yet. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.” In some situations, we need to really drill down by asking questions to get facts.
We can all benefit from listening, observing, questioning, and validating information.