Lowering Your Environmental Entropy
You might recall from some of your engineering courses the concept of ‘entropy’ in determining overall plant efficiency and performance. Much of your plant improvement activities are actually geared to lowering the entropy of your plant’s processes to improve its efficiency. But you might be surprised to learn that entropy applies to your plant information as well. Claude Shannon, known as the Father of Information Theory, worked out information entropy equations at Bell Labs in the late 1940s. The entropy of data is related to its uncertainty. The higher your data uncertainty is, the higher its entropy. High entropy in your plant process results in a high heat rate and lower plant productivity. High information entropy means you know little about what is actually going on at your plant. As environmental engineers, we depend on the quality of information because much of it derives from things that are not directly seen, but are measured. Lots of data has to be collected from diverse points, aggregated, used in complex calculations and summarized.There are many ways that uncertainty can creep into your results and get amplified along the way.