The manufacturing process for a single product can be modified much easier in order to improve its efficiency and productivity, compared to a plant floor where several different products are being produced. Higher Return on Investment is the prime motivation for automation, and improving the parameter becomes more complex as the production capacity increases in difficulty.
Robots aren’t plug & play devices, especially not in an industrial setting. They require considerable prep-work, ranging from the initial design stage, to implementation, to regressive testing & troubleshooting. Things can get even more complicated when you are trying to achieve a great degree of automation through robots that work in conjunction, not just from the technical point of view, but from the financial side as well.
It can be stated without a doubt that economic efficiency serves as the prime motivator for adopting automation technologies. Directly, or indirectly, operational efficiency also leads to a reduction in waste products and allows companies to minimize their energy needs. The US Environmental Protection Agency has repeatedly recognized these benefits and encouraged shift-over to automated electronic reporting and advanced monitoring technologies.
In today’s world of industrial automation solutions, efficiency is one of the most heavily scrutinized aspects of automated control systems. Any part of an assembly line that is not operating at its maximum efficiency is going to end up costing more money in an energy analysis. In such an analysis, the energy usage of the components becomes the area with the most emphasis.
Robots have served as the backbone of the manufacturing industry for decades, replacing humans in repetitive, laborious and time-consuming tasks. Advancements in engineering introduced robots to Artificial Intelligence (AI) and soon, the idea of collaborative robots took over. The scope of having a machine understand and work with you was promising, triggering developers to vigorously work on the idea. Simultaneous advancements in technology and boom in processing capabilities, turned the entire idea into practicality.
Many beginner automation enthusiasts often fail to establish appreciable differences between Supervisory Control & Data Acquisition (SCADA) and Human Machine Interfaces (HMIs). They often confuse both these entities as being similar and working for the same end-result. While the latter may be true, as in the end achieving automation is the desired result, the two terms are quite different and have limited overlap.