Introduction

The use of computers to control a particular process in order to increase reliability and efficiency, often through the replacement of employees. For a manufacturer, this could entail using robotic assembly lines to manufacture a product.

Automation is the use of control systems (such as numerical control, programmable logic control, and other industrial control systems), in concern with other applications of information technology (such as computer-aided technologies [CAD, CAM], to control industrial machinery and processes, reducing the need for human intervention.

In the scope of industrialization, automation is a step beyond mechanization. Whereas mechanization provided human operators with machinery to assist them with the muscular requirements of work, automation greatly reduces the need for human sensory and mental requirements as well. Processes and systems can also be automated.

Automation plays an increasingly important role in the global economy and in daily experience. Engineers strive to combine automated devices with mathematical and organizational tools to create complex systems for a rapidly expanding range of applications and human activities. Many roles for humans in industrial processes presently lie beyond the scope of automation. Human-level pattern recognition, language recognition, and language production ability are well beyond the capabilities of modern mechanical and computer systems.

Tasks requiring subjective assessment or synthesis of complex sensory data, such as scents and sounds, as well as high-level tasks such as strategic planning, currently require human expertise.

In many cases, the use of humans is more cost-effective than mechanical approaches even where automation of industrial tasks is possible.Specialized hardened computers, referred to as programmable logic controllers (PLCs), are frequently used to synchronize the flow of inputs from (physical) sensors and events with the flow of outputs to actuators and events. This leads to precisely controlled actions that permit a tight control of almost any industrial process.

Human-machine interfaces (HMI) or computer human interfaces (CHI), formerly known as man-machine interfaces, are usually employed to communicate with PLCs and other computers, such as entering and monitoring temperatures or pressures for further automated control or emergency response.

Service personnel who monitor and control these interfaces are often referred to as stationary engineers.

During the 19th century a number of machines such as looms and lathes became increasingly self-regulating.

At the same time transfer-machines were developed, whereby a series of machine-tools, each doing one operation automatically, became linked in a continuous production line by pneumatic or hydraulic devices transferring components from one operation to the next.

In addition to these technological advances in automation, the theory of ‘scientific management’, which was based on the early time-and-motion studies of Frederick Winslow Taylor in Philadelphia, USA, in the 1880s was designed by Taylor to enhance the efficiency and productivity of workers and machines.

In the early 20th century, with the development of electrical devices and time-switches, more processes became automatically controlled, and a number of basic industries such as oil-refining, chemicals, and food-processing were increasingly automated.

The development of computers after World War II enabled more sophisticated automation to be used in manufacturing industries, for example iron and steel. The most familiar example of a highly automated system is perhaps an assembly plant for automobiles or other complex products.

Over the last few decades automation has evolved from the comparatively straightforward mechanization of tasks traditionally carried out by hand, through the introduction of complex automatic control systems, to the widespread automation of information collection and processing.

Impact

Automation has had a notable impact in a wide range of highly visible industries beyond manufacturing. Once-ubiquitous telephone operators have been replaced largely by automated telephone switchboards and answering machines.

Medical processes such as primary screening in electrocardiography or radiography and laboratory analysis of human genes, sera, cells, and tissues are carried out at much greater speed and accuracy by automated systems. Automated teller machines have reduced the need for bank visits to obtain cash and carry out transactions.

In general, automation has been responsible for the shift in the world economy from agrarian to industrial in the 19th century and from industrial to services in the 20th century.

The widespread impact of industrial automation raises social issues, among them its impact on employment. Historical concerns about the effects of automation date back to the beginning of the industrial revolution, when a social movement of English textile machine operators in the early 1800s known as the Luddites protested against Jacquard's automated weaving looms - often by destroying such textile machines- that they felt threatened their jobs.

One author made the following case- When automation was first introduced, it caused widespread fear. It was thought that the displacement of human operators by computerized systems would lead to severe unemployment.

Critics of automation contend that increased industrial automation causes increased unemployment; this was a pressing concern during the 1980s. One argument claims that this has happened invisibly in recent years, as the fact that many manufacturing jobs left the United States during the early 1990s was offset by a one-time massive increase in IT jobs at the same time. Some authors argue that the opposite has often been true, and that automation has led to higher employment.

Under this point of view, the freeing up of the labor force has allowed more people to enter higher skilled managerial as well as specialized consultant/contractor jobs (like cryptographers), which are typically higher paying.

One odd side effect of this shift is that "unskilled labour" is in higher demand in many first-world nations, because fewer people are available to fill such jobs.

At first glance, automation might appear to devalue labor through its replacement with less-expensive machines; however, the overall effect of this on the workforce as a whole remains unclear.

Today automation of the workforce is quite advanced, and continues to advance increasingly more rapidly throughout the world and is encroaching on ever more skilled jobs, yet during the same period the general well-being and quality of life of most people in the world have improved dramatically.

Advantages and disadvantages

The main advantages of automation are:

▪ Replacing human operators in tedious tasks. ▪ Replacing humans in tasks that should be done in dangerous environments (i.e. fire, space, volcanoes, nuclear facilities, under the water, etc) ▪ Making tasks that are beyond the human capabilities such as handling too heavy loads, too large objects, too hot or too cold substances or the requirement to make things too fast or too slow. ▪ Economy improvement. Sometimes and some kinds of automation implies improves in economy of enterprises, society or most of humankind. For example, when an enterprise that has invested in automation technology recovers its investment; when a state or country increases its income due to automation like Germany or Japan in the 20th Century or when the humankind can use the internet which in turn use satellites and other automated engines.

The main disadvantages of automation are:

▪ Technology limits. Current technology is unable to automate all the desired tasks. ▪ Unpredictable development costs. The research and development cost of automating a process is difficult to predict accurately beforehand. Since this cost can have a large impact on profitability, it's possible to finish automating a process only to discover that there's no economic advantage in doing so. ▪ Initial costs are relatively high. The automation of a new product required a huge initial investment in comparison with the unit cost of the product, although the cost of automation is spread in many product batches. The automation of a plant required a great initial investment too, although this cost is spread in the products to be produced.

Controversial factors

1. Unemployment. It is commonly thought that automation implies unemployment due to the fact that the work of a human being is replaced in part or completely by a machine. Nevertheless, the unemployment is caused by the economical politics of the administration like dismissing the workers instead of changing their tasks. Since the general economical policies of most of the industrial plants are to dismiss people, nowadays automation implies unemployment. In different scenarios without workers, automation implies more free time instead of unemployment like the case with the automatic washing machine at home. Automation does not imply unemployment when it makes tasks unimaginable without automation such as exploring mars with the Sojourner or when the economy is fully adapted to an automated technology as with the Telephone switchboard.

2. Environment. The costs of automation to the environment are different depending on the technology, product or engine automated. There are automated engines that consume more energy resources from the Earth in comparison with previous engines and those that do the opposite too.

3. Human being replacement. In the future there is a possibility that the Artificial intelligence could replace and improve a human brain and the robots would become not only fully automated but fully autonomous from the human beings (Technological singularity)

Kinds of Automation

Robotics

The mechanical structure of a robot must be controlled to perform tasks. The control of a robot involves three distinct phases - perception, processing, and action (robotic paradigms). Sensors give information about the environment or the robot itself (e.g. the position of its joints or its end effectors). This information is then processed to calculate the appropriate signals to the actuators (motors) which move the mechanical.

The processing phase can range in complexity. At a reactive level, it may translate raw sensor information directly into actuator commands. Sensor fusion may first be used to estimate parameters of interest (e.g. the position of the robot's gripper) from noisy sensor data. An immediate task (such as moving the gripper in a certain direction) is inferred from these estimates. Techniques from control theory convert the task into commands that drive the actuators.

At longer time scales or with more sophisticated tasks, the robot may need to build and reason with a "cognitive" model. Cognitive models try to represent the robot, the world, and how they interact. Pattern recognition and computer vision can be used to track objects. Mapping techniques can be used to build maps of the world. Finally, motion planning and other artificial intelligence techniques may be used to figure out how to act. For example, a planner may figure out how to achieve a task without hitting obstacles, falling over, etc.

Control systems may also have varying levels of autonomy. Direct interaction is used for hap tic or tele-operated devices, and the human has nearly complete control over the robot's motion. Operator-assist modes have the operator commanding medium-to-high-level tasks, with the robot automatically figuring out how to achieve them. An autonomous robot may go for extended periods of time without human interaction. Higher levels of autonomy do not necessarily require more complex cognitive capabilities. For example, robots in assembly plants are completely autonomous, but operate in a fixed pattern.

Laboratory automation

Laboratory automation is a multi-disciplinary strategy to research, develop, optimize and capitalize on technologies in the laboratory that enable new and improved processes. Laboratory automation professionals are academic, commercial and government researchers, scientists and engineers who conduct research and develop new technologies to increase productivity, elevate experimental data quality, reduce lab process cycle times, or enable experimentation that otherwise would be impossible.
The most widely known application of laboratory automation technology is laboratory robotics. More generally, the field of laboratory automation comprises many different automated laboratory instruments, devices, software algorithms, and methodologies used to enable, expedite and increase the efficiency and effectiveness of scientific research in laboratories.
The application of technology in today's laboratories is required to achieve timely progress and remain competitive. Laboratories devoted to activities such as high-throughput screening, combinatorial chemistry, automated clinical and analytical testing, diagnostics, large scale bio-repositories, and many others, would not exist without advancements in laboratory automation.
Some universities offer entire programs that focus on lab technologies. For example, Indiana University-Purdue University at Indianapolis offers a graduate program devoted to Laboratory Informatics. Also, the Keck Graduate Institute in California offers a graduate degree with an emphasis on development of assays, instrumentation and data analysis tools required for clinical diagnostics, high-throughput screening, genotyping, microarray technologies, proteomics, imaging and other applications.
In 1993, Dr. Rod Markin at the University of Nebraska Medical Center created one of the world's first clinical automated laboratory management systems. In the mid 1990s, he chaired a standards group called the Clinical Testing Automation Standards Steering Committee (CTASSC) of the American Association for Clinical Chemistry, which later evolved into an area committee of the Clinical and Laboratory Standards Institute.
In 2004, the National Institutes of Health (NIH) and more than 300 nationally recognized leaders in academia, industry, government, and the public completed the NIH Roadmap to accelerate medical discovery to improve health. The NIH Roadmap clearly identifies technology development as a mission critical factor in the Molecular Libraries and Imaging Implementation Group.

Automation tools

Different types of automation tools exist: • ANN - Artificial neural network - An artificial neural network (ANN), usually called "neural network" (NN), is a mathematical model or computational model that tries to simulate the structure and/or functional aspects of biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach to computation. In most cases an ANN is an adaptive system that changes its structure based on external or internal information that flows through the network during the learning phase. Neural networks are non-linear statistical data modeling tools. They can be used to model complex relationships between inputs and outputs or to find patterns in data.

• DCS - Distributed Control System – It refers to a control system usually of a manufacturing system, process or any kind of dynamic system, in which the controller elements are not central in location (like the brain) but are distributed throughout the system with each component sub-system controlled by one or more controllers. The entire system of controllers is connected by networks for communication and monitoring. DCS is a very broad term used in a variety of industries, to monitor and control distributed equipment. • Electrical power grids and electrical generation plants • Environmental control systems • Traffic signals • Water management systems • Oil refining plants • Chemical plants • Pharmaceutical manufacturing • Sensor networks • Dry cargo and bulk oil carrier ships

• HMI - Human Machine Interface - The term user interface is often used in the context of computer systems and electronic devices. The user interface of a mechanical system, a vehicle or an industrial installation is sometimes referred to as the human-machine interface (HMI). HMI is a modification of the original term MMI (man-machine interface). In practice, the abbreviation MMI is still frequently used although some may claim that MMI stands for something different now. Another abbreviation is HCI, but is more commonly used for human-computer interaction than human-computer interface. Other terms used are operator interface console (OIC) and operator interface terminal (OIT). However it is abbreviated, the terms refer to the 'layer' that separates a human that is operating a machine from the machine itself.

• SCADA - Supervisory Control and Data Acquisition - It generally refers to an industrial control system: a computer system monitoring and controlling a process. The process can be industrial, infrastructure or facility based as described below: 1. Industrial processes include those of manufacturing, production, power generation, fabrication, and refining, and may run in continuous, batch, repetitive, or discrete modes. 2. Infrastructure processes may be public or private, and include water treatment and distribution, wastewater collection and treatment, oil and gas pipelines, electrical power transmission and distribution, civil defense siren systems, and large communication systems. 3. Facility processes occur both in public facilities and private ones, including buildings, airports, ships, and space stations. They monitor and control HVAC, access, and energy consumption. • PLC - Programmable Logic Controller - A programmable logic controller (PLC) or programmable controller is a digital computer used for automation of electromechanical processes, such as control of machinery on factory assembly lines, amusement rides, or lighting fixtures. PLCs are used in many industries and machines. Unlike general-purpose computers, the PLC is designed for multiple inputs and output arrangements, extended temperature ranges, immunity to electrical noise, and resistance to vibration and impact. Programs to control machine operation are typically stored in battery-backed or non-volatile memory. A PLC is an example of a real time system since output results must be produced in response to input conditions within a bounded time, otherwise unintended operation will result.

• PAC - Programmable Automation Controller - A programmable automation controller (PAC) is a compact controller that combines the features and capabilities of a PC-based control system with that of a typical programmable logic controller (PLC). A PAC thus provides not only the reliability of a PLC, but also the task flexibility and computing power of a PC. PACs are most often used in industrial settings for process control, data acquisition, remote equipment monitoring, machine vision, and motion control. Additionally, because they function and communicate over popular network interface protocols like TCP/IP, OLE for process control (OPC) and SMTP, PACs are able to transfer data from the machines they control to other machines and components in a networked control system or to application software and databases. A PAC at the core of an automation system can integrate multiple field bus networks like RS-485, RS-232, RS-422, CAN, Ethernet, Ethernet/IP, and others.

• Instrumentation - An instrument is a device that measures or manipulates variables such as flow, temperature, level, or pressure. Instruments include many varied contrivances which can be as simple as valves and transmitters, and as complex as analyzers. Instruments often comprise control systems of varied processes. The control of processes is one of the main branches of applied instrumentation. Control instrumentation includes devices such as solenoids, valves, circuit breakers, and relays. These devices are able to change a field parameter, and provide remote or automated control capabilities. Transmitters are devices which produce an analog signal, usually in the form of a 4–20 mA electrical current signal, although many other options using voltage, frequency, or pressure are possible. This signal can be used to control other instruments directly, or it can be sent to a PLC, DCS, SCADA system, or other type of computerized controller, where it can be interpreted into readable values and used to control other devices and processes in the system. Instrumentation plays a significant role in both gathering information from the field and changing the field parameters, and as such are a key part of control loops. • Motion control - Motion control is a sub-field of automation, in which the position and/or velocity of machines are controlled using some type of device such as a hydraulic pump, linear actuator, or an electric motor, generally a servo. Motion control is an important part of robotics and CNC machine tools, however it is more complex than in the use of specialized machines, where the kinematics are usually simpler. The latter is often called General Motion Control (GMC). Motion control is widely used in the packaging, printing, textile, semiconductor production, and assembly industries.

• Robotics - Robotics is the engineering science and technology of robots, and their design, manufacture, application, and structural disposition. Robotics is related to electronics, mechanics, and software.

COMPUTER PROJECT

AUTOMATION

Made By:-

Ayush Bansal

IIIrd Year, 5th Semester

Roll No. – 09

Acknowledgment

I, Ayush Bansal, would like to express my gratitude to our Computer teacher,

Rizvi sir, for making the subject so easy and understandable to us that has helped me to put my best efforts to the assignment.

Thanking you

Ayush Bansal

Contents

• Introduction

• Impact

• Advantages & Disadvantages

• Kinds of automation

• Automation Tools

• Bibliography

Bibliography

1. www.wikipedia.com

2. www.google.com

3. www.encyclopedia.com