Industrial Automation

Industrial automation facilitates to increase the product quality, reliability and production rate while reducing production and design cost by adopting new, innovative and integrated technologies and services.
industrial automation is a set of technologies that uses control systems and devices, such as computer software and robotics, to enable automatic operation of industrial processes and machinery without the need for human operators. Industrial automation eliminates the possibility of human error, reduces costs, saves time, and achieves higher performance.
On the other hand, automation replaces the human involvement with the use of logical programming commands and powerful machines. Industrial automation can be achieved by several different means, including mechanical, electrical, electronic, hydraulic, pneumatic, and computers. Usually, two or more of these means are used in combination. Today’s state-of-the-art factories, ships, and airplanes combine all of these techniques.

Industrial Automation Tools

gather and process data from sensors and control actuators. A solid-state control system that has a user-programmable memory for storing instructions for the purpose of implementing specific functions such as I/O control, logic, timing, counting, three mode (PID) control, communication, arithmetic, and data and file processing. The PLC continuously monitors and receives information from input devices or sensors, processes the information, and triggers the connected output devices, to complete the task in the industrial process or machinery.
a supervisory control and data acquisition (SCADA) system monitors and controls safety systems and gathers real-time, time-synchronized, high-resolution data for collaboration and visualization. Each SCADA system consists of several parts, including sensors, RTUs/PLCs, computer servers, computer workstations, communication infrastructure, computer networking equipment, and various peripherals.
An HMI is a software application that enables interaction and communication between a human operator and the machine, or production system. It translates complex data into accessible information, enabling better control of the production process and its various applications.
Artificial Neural Networks are the computational models inspired by the human brain. Artificial Neural Networks, in general – is a biologically inspired network of artificial neurons configured to perform specific tasks. Neural networks are data analysis methods and algorithms, indirectly based on the nervous systems of humans and animals. An artificial neural network is nonlinear in nature and, thus, represents an exceptionally powerful method of analyzing real-world data that allows modeling extremely difficult dependencies.
A distributed control system (DCS) is a broad term referring to a process in which the controlling elements are distributed throughout, rather than controlled centrally. In more general terms, a DCS is a process that requires separate computers at each step of the process. The concept behind DCS increases reliability and reduces installation costs through localization of control functions in the vicinity of process facilities, and also enables remote monitoring and supervision of processes. Today, the functionality provided by SCADA and DCS is very similar, but DCS is often used in large process facilities in which great reliability and safety is important (redundancy).
Robots are an indispensable part of today’s large manufacturing industries. These intelligent machines have taken over many of the tasks requiring high precision, speed and endurance. Safety first – for the humans interacting with them – followed by reliability and a very long lifetime are the key challenges in designing an industrial robot and thus large use of redundancy mechanisms – either hardware or software – and predictive maintenance strategies must be implemented to ensure productive and cost-effective solutions.