Sensors are now so commonplace in production automation that it is hard to imagine a factory without them. Most factories use many different types of sensors to count product quantities, schedule steps in an automated process or ensure optimal production conditions, but by their very nature, the electronic signals that sensors already transmit can be collected for insightful data analysis. Even a simple binary pulse from a sensor is a potential source of data that can be monitored to streamline operations. How often a photoelectric beam is interrupted (by products on a conveyor, for example) can be captured and recorded to calculate operating speeds, which can be adjusted to maximize productivity as part of a larger manufacturing process.
The types of data that sensors can capture are practically limitless. They can record quantities, volumes, distances, weights, dimensions, shapes, colors, positioning, temperatures, thermal activity, vibration, reflectivity, curvature, surface variations, material composition, response to sound waves, proximity to physical obstacles, visual or auditory information, texture patterns, steps in a programmed sequence and almost anything else. Any value a sensor can observe can be a data point, and any data point can be measured over time.
In this way, the whole philosophy of IIoT is part of the trend towards “Big Data” analytics to make insight-driven business decisions. Simply put, the more data manufacturers collect from their installed sensors, the more they understand about the capabilities of their own systems. They can leverage this “actionable” data to improve processes at any level of production. And these improvements can lead to leaner, more productive results, giving them a distinct fulfillment advantage over competitors.