Principles of Automation and Control

The discussion in this chapter revolves around the general introduction and the basic definition of the concepts of automation and control. Automation and control are closely interrelated fields with the advent of Industry 4.0. Automation deals with the integration of technologies that can enable systems to carry out tasks without human intervention or with minimal intervention. On the other hand, control is a process of monitoring and manipulating the variables of a system in order to achieve the desired outputs. Hence, an automated system comprises the control system, information, communication and technology system, actuator, and effective feedback mechanism. The emergence of Industry 4.0 technologies focuses on improvement in efficiency, profitability, systems’ flexibility, manufacturing processes, product quality, cost, and time effectiveness with a significant reduction in manufacturing process errors. These improvements can be aided by putting in place a system with effective automation and control. This chapter further explores the differences between mechanization and automation and draws a correlation between automation and artificial intelligence. Also, the capabilities underlying the Artificial Intelligence (AI) technology are highlighted. Furthermore, the classes of automation are explained including the procedures for automation design. In addition, the merits and demerits of automation are highlighted and the chapter ends with the automation of production lines and different work layout configurations. The concept of automation is central to industrial society and is prevalent in the engineering industries (manufacturing, process industries, etc.)

In this chapter, the concepts of automated processes and systems including the elements of system automation are explained. In process automation, digital technologies are often used to automate complex manufacturing or business processes. This includes the use of the system to perform tasks and the integration of software, information and communication technology, data acquisition, and storage sub-systems. A system may go through several processes that are time sensitive and repetitive before obtaining the final output. Process automation prevents variation and bottlenecks associated with these processes such as errors, and data loss while improving speed and communication among other sub-systems. System automation is a subset of Mecha-tronics engineering that involves the integration of a sensing system, control mechanisms, and drive system (actuators). The three basic elements of an automation system that must be synergized include: the power system, the program of instructions or codes to direct the process, and the control mechanism to actuate the instructions. This chapter also delves into the systems operations, programming and classes of automated systems. The two major classes of the control system; open and closed loop control systems otherwise known as the non-feedback and feedback control systems respectively are discussed including their designs. The Proportional Integral Derivative (PID) controllers will continue to be important in several industrial applications because they utilize a control loop feedback mechanism to control process variables and are highly stable and accurate in achieving control tasks.

This chapter discusses the levels of automation (LOA). The degree to which a system, process or task is automated is referred to as the level of automation. They are: manual, semi-automatic and fully automatic depending on the level of human involvement, the system or processes to be automated and the end users’ requirements. At the lowest level; the manual represents the human control level while the fully automatic level represents the computer controls level. At the semi-automatic level, the control activities involve both human and computer controls. The human control tasks include sensory processing for information acquisition, perception for information analysis, decision-making based on cognitive processing for action selection, and response selection for action implementation. Furthermore, this chapter also highlights the elements of system automation and classes of automated systems. The identification and specifications of the elements of the system’s automation based on the end-user requirements are a critical aspect of the control design phase. The major elements of the system’s automation include a sensor, a controller, an actuator, a power component, a motor and drives, a communication protocol, a human-machine interface, etc. Classes of automation systems could also be fixed, programmable, flexible, integrated, or cognitive automation depending on the need. The future of fully autonomous systems is exciting and promising although many industrial processes and systems are semi-autonomous thus relying on human factors such as physical, mental and technical capabilities such as intuition, perception, sensitivity, observation, experience, and judgment to arrive at effective decision making as it relates to system’s control.

This chapter presents the control system and its functions, types, examples, and representation of the process control systems. A control system is a system that regulates, directs, commands, and manages the performance of other sub-systems using a control loop. Basically, there are two major types of control systems, viz; the open and closed loop control systems. For the open loop control system, control action is independent of the desired output. This control system is referred to as a non-feedback control because of the absence of a feedback path. Although they are simple in design and relatively inexpensive but are less accurate compared to the closed-loop control system. On the other hand, for the closed-loop control system, control action is a function of the desired output. This control system is referred to as feedback control because of the presence of the feedback path. Although it is complex in design and expensive but more accurate compared to the open loop control system. To enhance the performance of basic controls, many modern systems incorporate advanced controls such as advanced regulatory controls, advanced process controls, multivariable predictive control, non-linear multivariable predictive control, fuzzy logic control, inferential measurements, etc. Advanced controls are a set of technologies employed to address a specific control deficiency in a system. While the basic controls facilitate the control of a system’s basic operations, advanced controls are incorporated to enhance the performance of the basic controls.

This chapter deals with the control devices used in automation such as Programmable Logic Devices (PLD), Programmable Logic Controller (PLC), Programmable Automation Controller (PAC), Personal Computer (PC), etc. The goal of the control devices in automation is to achieve an efficient, robust and reliable system control. Basically, system control devices include input devices (for raw data input), processing devices (for processing raw data into information), output devices (to disseminate the processed data and information), and storage devices (for the retention of processed data and information). The sensors feed the main controller with the input data acquired from the environment. Following the processing of the data, the decision is made by the main controller on the control action to take and this decision is communicated to the actuator for execution. The actuator in turn drives the final control device to implement the control action. The programming language is crucial in achieving optimum efficiency. While the PLC follows a scan-based program execution, PC software is usually event-driven. In terms of cost efficiency, indicators such as performance, expandability, and ruggedness are important considerations. The initial cost of a PC may be higher than that of a PLC as a PC is more suitable for processing of complex network loads. PLC may be initially inexpensive but as the demand for processing power increases, the PC-based system becomes more cost-effective. In terms of expandability, PLC usually offers support to standard industrial equipment but when an external control is needed, a PC is more suited. PLC does not require additional protection equipment compared to PC.

Industrial automation tools are of a wide range of tools that are employed for industrial automation. These tools comprise various control systems that incorporate diverse sub-systems or devices to enhance industrial processes. Notable examples include Computer-aided design (CAD software) and Computer-aided manufacturing (CAM software), Artificial Neural Networks (ANN), Distributed Control Systems (DCS), Human-Machine Interface (MHI), Supervisory Control and Data Acquisition System (SCADA), instrumentation and robotics, etc. They are beneficiaries in the area of product development (improved design, analysis, and manufacture of products), quality control time and cost-effectiveness amongst others. This chapter emphasizes industrial automation tools and components. Furthermore, the application of industrial automation in robotics, packaging systems, computer numeric control systems, tool monitoring systems, advanced inspection systems as well as flexible manufacturing systems were discussed in this chapter. Industrial automation tools can significantly influence industrial processes with a reduction in manufacturing lead time, improvement in product quality, and effective process monitoring.

This chapter provides a practical demonstration of how a system’s automation can be achieved. Some specific examples presented include the automation of irrigation systems, waste segregator, gasifiers, biodiesel plants, biogas plants, lawn mowers, assembly line automation as well as the automation and control of the suspension system of a railcar. The details of the design and components required for the automation of these systems are highlighted. The chapter presents practical guided approaches by which system automation can be achieved depending on the end-users requirements. The practical examples highlight the integration of sensors (for measuring conditions/parameters), controllers (for processing inputs and decision-making) as well as actuators (for effecting changes) with minimal or no human interference. System automation is connected to the engineering field called mechatronics which is an interdisciplinary engineering branch comprising a combination of mechanical, computer, electrical and electronic systems. The automation of systems will enhance profitability, improved production rate, product quality, and safety.

Lack of access to potable water has become an issue of concern in our society. In order to satisfy the increasing water demands of the galloping population in Nigerian communities, it is essential to use smart technology to manage water resources. The purpose of this research work is to ensure that inaccessibility to water as a result of pump failure is detected in real-time through smart technology. To solve this daunting challenge, an Arduino microcontroller and Liquid Crystal Display (LCD) were used to switch on and switch off the submersible pump at a predetermined Water Level (WL) in the tank and also to determine the pump availability hours. The WL in the tank was monitored using an Arduino microcontroller, sensors, relays, and LCD. A Global System for Mobile telecommunication (GSM) module was also used to create an interactive medium between the user/maintenance team and the system to monitor the submersible pump reliability based on engineering theory and concept. The system was tested by introducing varying volumes of water in a constructed water distribution system prototype in the laboratory. The microcontroller was efficient in controlling the system; the pump was able to switch on and switch off when the WL in the tank was 50% and 100%, respectively. As an autonomous system, it was capable of taking decisions automatically without human interference. The system was able to send feedback via SMS to alert the user/maintenance team to check the pump whenever it failed to pump water at WL≤ 50%. This innovative design system will help to monitor and manage water distribution properly and it should be considered for use in schools, hospitals, residences, offices, etc. to ensure the availability of water always, save energy consumption and help in combating covid-19.

One of the major problems with waste generation today is the huge percentage of plastics in its composition. The automated waste segregator is a mechatronic system that solves this problem by the incorporation of high calibrated sensors and mechanical properties into its design to enable the smooth segregation of plastics and metals. It is capable of detecting and separating these components as soon as they get to its sensing unit with the aid of capacitive proximity sensors and ultrasonic sensors. The capacitive proximity sensor made with plated iron detects the type of material in range either plastics or metals based on their di-electric constant. A 12V DC geared motor made with aluminum and iron of high torque and speed characteristics is connected to the lids to enable its automatic open and close mechanism. Also, a microcontroller (PIC18F452) was used to control the entire segregation process of the system and is capable of storing and implementing the software in real-time. The sensors are controlled by the PICI8F452 microcontroller and based on the sensor readings, pulses are sent from the controller to the geared motor for the fast action of lid opening. The results of the performance evaluation indicated that the automated waste segregator has the capacity to identify and sort wastes into plastics, metals and any other waste with the aid of a capacitive sorting technique.

Robotics finds application in firefighting services. This work considers a robot that is able to detect fire and extinguish it. The robot operates automatically, avoiding obstacles, and at the same time, it is capable of detecting, tracking, and extinguishing flames. To achieve the best performance with an effective implementation, a modular design strategy was adopted, where the robot is divided into a number of logical modules based on functionality. The design consists of five main modules: the master controller, motor control, proximity control, fire detection and fire extinguishing module. Each module is associated with appropriate sensors and actuators. The information from various sensors and key hardware elements is processed via the PIC18F452 microcontroller. This is then interfaced with the master controller which coordinates and schedules the task of the entire robotic system. The performance evaluation indicates the robot’s capability to detect and extinguish flames, hence, this work will generate interest as well as innovations in the field of robotics while working towards practical and obtainable solutions to save lives and mitigate the risk of property damage.

Hand-gesture interpretation and control in robotics describe the interconnection between human and machine elements in the computer vision world. Pruning a structured environment is time-consuming and labor-intensive. Therefore, it requires management by a self-propelled machine. The path planning mode allows the robot to move along a specified path. Various studies on lawn mower robots focus more on obstacle avoidance with hand gesture interpretation and control implemented to take care of path definition. This study targets the development of a solar-powered lawn mower robot using hand gesture control as a path-planning technique. The robotic system continuously operates using charged batteries via solar energy stored in photovoltaic cells. The robot control mechanism was implemented via the use of infrared sensors to avoid obstruction on its path, and hand gesture interpretation via a DSP processor for path planning. The performance evaluation of the robot was based on field experiments and simulations using SolidWorks, defined in terms of area covered, lawn availability, energy utility, and optimum turning velocity. The evaluation revealed that the machine’s efficiency is almost 100% based on the area covered, the percentage availability of the robot is 95%, and the average energy utility of 7.7 KWh was also obtained. The optimum turning velocity of 0.096 m/s at work with a completion time of 20 minutes was obtained by simulation. This robot is useful for any environment, both structured and semi-structured.

The global emission regulations and fossil fuel pollution control have necessitated the need to study the effect of injector fuel splitting time and flow rate on engine performance. To achieve this, an automated prototyped 4-cylinder injector engine was developed to replicate the real-time activities of the injector system in the internal combustion (IC) engine. Arduino Nano open-source platform was used to integrate the various component parts such as the fuel injector, fuel tank, submersible fuel pump injector rail, transparent plastic chamber, flexible hose, Engine Control Unit (ECU), connecting wires, frame, Liquid Crystal Display (LCD), switch button, relay module, current sensor, potentiometer, Arduino nano, and pressure sensor that were used for the design experiment. Programmable circuit board microcontroller, Arduino (Integrated Development Environment) IDE, and C++ coding language were used to achieve the smart regulations of the injector operation system to replicate the real-time situation when the engine is running. This was achieved by incorporating Arduino microcontroller ATMEGA328, C++, and Arduino IDE software. The Arduino programming initiates the injection system and measures the injection output parameters. The system was designed to vary the splitting time delay between the four injectors and to measure the flow rate of the fuel injected. The experimental study showed that at a very high splitting time delay, the amount of fuel injected is more than the fuel injected at a relatively low splitting time delay with an average flow rate of 4.36 l/min at 50 microseconds and 0.02 l/min at 500 microseconds for high and low splitting time, respectively. This study will help the stakeholders in the automotive industry to virtualize the invisible situation of the fuel injector in real-time performance in the engine.