One flow of data to information to knowledge for plants and facilities has centered around connecting physical measurements to operators and engineers with the necessary mechanical, electrical, and chemical expertise. And this is not anything new. Industrial environments have long been a rich source of time-series data. data consists of a sequence of data points collected at regular intervals. For example, the temperature readings of a boiler over time represent time-series data.
This information allows equipment operators and hong kong whatsapp number data engineers to monitor equipment and process statuses and make informed decisions about operation and maintenance.
Though this process from data to knowledge is not new for industrial plants, it has changed over the years. Before the third industrial revolution in the mid-20th century, data collection in industrial settings relied on manual processes. Operators would conduct rounds at predetermined intervals. They recorded data points using various tools and methods, from analog gauges to manual sampling and from paper logs to punch cards.
Industrial organizations used these methods to generate, collect, and analyze data for day-to-day operations. In fact, the industry recognized the importance of instrumentation (that generate and manage industrial data) so much that Richard Rimbach and other industrial experts formed the Instrument Society of America (now known as the International Society of Automation) in 1945.