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For a hierarchical presentation of automation topics, see Outline of automation. For other uses, see Automation (disambiguation).Not to be confused with automaton.

Automation is the technology by which a process or procedure is performed with minimal human assistance.[1] Automation [2] or automatic control is the use of various control systems for operating equipment such as machinery, processes in factories, boilers and heat treating ovens, switching on telephone networks, steering and stabilization of ships, aircraft and other applications and vehicles with minimal or reduced human intervention.

Automation covers applications ranging from a household thermostat controlling a boiler, to a large industrial control system with tens of thousands of input measurements and output control signals. In control complexity, it can range from simple on-off control to multi-variable high-level algorithms.

In the simplest type of an automatic control loop, a controller compares a measured value of a process with a desired set value, and processes the resulting error signal to change some input to the process, in such a way that the process stays at its set point despite disturbances. This closed-loop control is an application of negative feedback to a system. The mathematical basis of control theory was begun in the 18th century and advanced rapidly in the 20th.

Automation has been achieved by various means including mechanical, hydraulicpneumatic, electrical, electronic devices and computers, usually in combination. Complicated systems, such as modern factories, airplanes and ships typically use all these combined techniques. The benefit of automation includes labor savings, savings in electricity costs, savings in material costs, and improvements to quality, accuracy, and precision.

The World Bank‘s World Development Report 2019 shows evidence that the new industries and jobs in the technology sector outweigh the economic effects of workers being displaced by automation.[3]

Job losses and downward mobility blamed on Automation has been cited as one of many factors in the resurgence of nationalist and protectionist politics in the US, UK and France, among other countries since 2010s.[4][5][6][7][8]

The term automation, inspired by the earlier word automatic (coming from automaton), was not widely used before 1947, when Ford established an automation department.[2] It was during this time that industry was rapidly adopting feedback controllers, which were introduced in the 1930s.[9]

Open-loop and closed-loop (feedback) control

Fundamentally, there are two types of control loop; open loop control, and closed loop feedback control.

In open loop control, the control action from the controller is independent of the “process output” (or “controlled process variable”). A good example of this is a central heating boiler controlled only by a timer, so that heat is applied for a constant time, regardless of the temperature of the building. (The control action is the switching on/off of the boiler. The process output is the building temperature).

In closed-loop control, the control action from the controller is dependent on the process output. In the case of the boiler analogy, this would include a thermostat to monitor the building temperature, and thereby feedback a signal to ensure the controller maintains the building at the temperature set on the thermostat. A closed loop controller, therefore, has a feedback loop which ensures the controller exerts a control action to give a process output the same as the “Reference input” or “set point”. For this reason, closed-loop controllers are also called feedback controllers.[10]

The definition of a closed loop control system according to the British Standard Institution is ‘a control system possessing monitoring feedback, the deviation signal formed as a result of this feedback being used to control the action of a final control element in such a way as to tend to reduce the deviation to zero.’ [11]

Likewise, a Feedback Control System is a system which tends to maintain a prescribed relationship of one system variable to another by comparing functions of these variables and using the difference as a means of control.[11] The advanced type of automation that revolutionized manufacturing, aircraft, communications, and other industries, is feedback control, which is usually continuous and involves taking measurements using a sensor and making calculated adjustments to keep the measured variable within a set range.[12][13] The theoretical basis of closed-loop automation is control theory.

Control actions

Main article: Control system

Discrete control (on/off)[edit]

One of the simplest types of control is on-off control. An example is a thermostat used on household appliances which either opens or closes an electrical contact. (Thermostats were originally developed as true feedback-control mechanisms rather than the on-off common household appliance thermostat.)

Sequence control, in which a programmed sequence of discrete operations is performed, often based on system logic that involves system states. An elevator control system is an example of sequence control.

PID controller

Main article: PID Controller

proportional–integral–derivative controller (PID controller) is a control loop feedback mechanism (controller) widely used in industrial control systems.

e(t)

In a PID loop, the controller continuously calculates an error value {\displaystyle e(t)} as the difference between a desired setpoint and a measured process variable and applies a correction based on proportionalintegral, and derivative terms, respectively (sometimes denoted PI, and D) which give their name to the controller type.

The theoretical understanding and application dates from the 1920s, and they are implemented in nearly all analog control systems; originally in mechanical controllers, and then using discrete electronics and latterly in industrial process computers.

Sequential control and logical sequence or system state control

Main article: Programmable logic controller

Sequential control may be either to a fixed sequence or to a logical one that will perform different actions depending on various system states. An example of an adjustable but otherwise fixed sequence is a timer on a lawn sprinkler.

States refer to the various conditions that can occur in a use or sequence scenario of the system. An example is an elevator, which uses logic based on the system state to perform certain actions in response to its state and operator input. For example, if the operator presses the floor n button, the system will respond depending on whether the elevator is stopped or moving, going up or down, or if the door is open or closed, and other conditions.[14]

Early development of sequential control was relay logic, by which electrical relays engage electrical contacts which either start or interrupt power to a device. Relays were first used in telegraph networks before being developed for controlling other devices, such as when starting and stopping industrial-sized electric motors or opening and closing solenoid valves. Using relays for control purposes allowed event-driven control, where actions could be triggered out of sequence, in response to external events. These were more flexible in their response than the rigid single-sequence cam timers. More complicated examples involved maintaining safe sequences for devices such as swing bridge controls, where a lock bolt needed to be disengaged before the bridge could be moved, and the lock bolt could not be released until the safety gates had already been closed.

The total number of relays, cam timers, and drum sequencers can number into the hundreds or even thousands in some factories. Early programming techniques and languages were needed to make such systems manageable, one of the first being ladder logic, where diagrams of the interconnected relays resembled the rungs of a ladder. Special

computers called programmable logic controllers were later designed to replace these collections of hardware with a single, more easily re-programmed unit.

In a typical hard wired motor start and stop circuit (called a control circuit) a motor is started by pushing a “Start” or “Run” button that activates a pair of electrical relays. The “lock-in” relay locks in contacts that keep the control circuit energized when the pushbutton is released. (The start button is a normally open contact and the stop button is normally closed contact.) Another relay energizes a switch that powers the device that throws the motor starter switch (three sets of contacts for three-phase industrial power) in the main power circuit. Large motors use high voltage and experience high in-rush current, making speed important in making and breaking contact. This can be dangerous for personnel and property with manual switches. The “lock-in” contacts in the start circuit and the main power contacts for the motor are held engaged by their respective electromagnets until a “stop” or “off” button is pressed, which de-energizes the lock in relay.[15]

Commonly interlocks are added to a control circuit. Suppose that the motor in the example is powering machinery that has a critical need for lubrication. In this case, an interlock could be added to ensure that the oil pump is running before the motor starts. Timers, limit switches, and electric eyes are other common elements in control circuits.

Solenoid valves are widely used on compressed air or hydraulic fluid for powering actuators on mechanical components. While motors are used to supply continuous rotary motion, actuators are typically a better choice for intermittently creating a limited range of movement for a mechanical component, such as moving various mechanical arms, opening or closing valves, raising heavy press rolls, applying pressure to presses.

Computer control

Computers can perform both sequential control and feedback control, and typically a single computer will do both in an industrial application. Programmable logic controllers (PLCs) are a type of special purpose microprocessor that replaced many hardware components such as timers and drum sequencers used in relay logic type systems. General purpose process control computers have increasingly replaced stand-alone controllers, with a single computer able to perform the operations of hundreds of controllers. Process control computers can process data from a network of PLCs, instruments, and controllers in order to implement typical (such as PID) control of many individual variables or, in some cases, to implement complex control algorithms using multiple inputs and mathematical manipulations. They can also analyze data and create real-time graphical displays for operators and run reports for operators, engineers, and management.

Control of an automated teller machine (ATM) is an example of an interactive process in which a computer will perform a logic derived response to a user selection based on information retrieved from a networked database. The ATM process has similarities with other online transaction processes. The different logical responses are called scenarios. Such processes are typically designed with the aid of use cases and flowcharts, which guide the writing of the software code. The earliest feedback control mechanism was the water clock invented by Greek engineer Ctesibius (285–222 BC)

History

It was a preoccupation of the Greeks and Arabs (in the period between about 300 BC and about 1200 AD) to keep accurate track of time. In Ptolemaic Egypt, about 270 BC, Ctesibius described a float regulator for a water clock, a device not unlike the ball and cock in a modern flush toilet. This was the earliest feedback controlled mechanism.[16] The appearance of the mechanical clock in the 14th century made the water clock and its feedback control system obsolete.

The Persian Banū Mūsā brothers, in their Book of Ingenious Devices (850 AD), described a number of automatic controls.[17] Two-step level controls for fluids, a form of discontinuous variable structure controls, was developed by the Banu Musa brothers.[18] They also described a feedback controller.[19][20]

Industrial Revolution in Western Europe

The introduction of prime movers, or self-driven machines advanced grain mills, furnaces, boilers, and the steam engine created a new requirement for automatic control systems including temperature regulators (invented in 1624; see Cornelius Drebbel), pressure regulators (1681), float regulators (1700) and speed control devices. Another control mechanism was used to tent the sails of windmills. It was patented by Edmund Lee in 1745.[21] Also in 1745, Jacques de Vaucanson invented the first automated loom. The design of feedback control systems up through the Industrial Revolution was by trial-and-error, together with a great deal of engineering intuition. Thus, it was more of an art than a science. In the mid-19th century mathematics was first used to analyze the stability of feedback control systems. Since mathematics is the formal language of automatic control theory, we could call the period before this time the prehistory of control theory.

In 1771 Richard Arkwright invented the first fully automated spinning mill driven by water power, known at the time as the water frame.[22] An automatic flour mill was developed by Oliver Evans in 1785, making it the first completely automated industrial process.[23][24]

The centrifugal governor, which was invented by Christian Huygens in the seventeenth century, was used to adjust the gap between millstones.[25][26][27] Another centrifugal governor was used by a Mr. Bunce of England in 1784 as part of a model steam crane.[28][29] The centrifugal governor was adopted by James Watt for use on a steam engine in 1788 after Watt’s partner Boulton saw one at a flour mill Boulton & Watt were building.[21]

The governor could not actually hold a set speed; the engine would assume a new constant speed in response to load changes. The governor was able to handle smaller variations such as those caused by fluctuating heat load to the boiler. Also, there was a tendency for oscillation whenever there was a speed change. As a consequence, engines equipped with this governor were not suitable for operations requiring constant speed, such as cotton spinning.[21]

Several improvements to the governor, plus improvements to valve cut-off timing on the steam engine, made the engine suitable for most industrial uses before the end of the 19th century. Advances in the steam engine stayed well ahead of science, both thermodynamics and control theory.[21]

The governor received relatively little scientific attention until James Clerk Maxwell published a paper that established the beginning of a theoretical basis for understanding control theory. Development of the electronic amplifier during the 1920s, which was important for long distance telephony, required a higher signal to noise ratio, which was solved by negative feedback noise cancellation. This and other telephony applications contributed to control theory. In the 1940s and 1950s, German mathematician Irmgard Flugge-Lotz developed the theory of discontinuous automatic controls, which found military applications during the Second World War to fire control systems and aircraft navigation systems.[12]

20th century

Relay logic was introduced with factory electrification, which underwent rapid adaption from 1900 through the 1920s. Central electric power stations were also undergoing rapid growth and operation of new high-pressure boilers, steam turbines and electrical substations created a large demand for instruments and controls. Central control rooms became common in the 1920s, but as late as the early 1930s, most process control was on-off. Operators typically monitored charts drawn by recorders that plotted data from instruments. To make corrections, operators manually opened or closed valves or turned switches on or off. Control rooms also used color-coded lights to send signals to workers in the plant to manually make certain changes.[30]

Controllers, which were able to make calculated changes in response to deviations from a set point rather than on-off control, began being introduced the 1930s. Controllers allowed manufacturing to continue showing productivity gains to offset the declining influence of factory electrification.[31]

Factory productivity was greatly increased by electrification in the 1920s. U. S. manufacturing productivity growth fell from 5.2%/yr 1919-29 to 2.76%/yr 1929-41. Alexander Field notes that spending on non-medical instruments increased significantly from 1929–33 and remained strong thereafter.[31]

The First and Second World Wars saw major advancements in the field of mass communication and signal processing. Other key advances in automatic controls include differential equationsstability theory and system theory (1938), frequency domain analysis (1940), ship control (1950), and stochastic analysis (1941).

Starting in 1958, various systems based on solid-state[32][33] digital logic modules for hard-wired programmed logic controllers (the predecessors of programmable logic controllers (PLC)) emerged to replace electro-mechanical relay logic in industrial control systems for process control and automation, including early Telefunken/AEG LogistatSiemens Simatic [de], Philips/Mullard/Valvo [deNorbitBBC SigmatronicACEC LogacecAkkord [deEstacord, Krone Mibakron, Bistat, Datapac, Norlog, SSR, or Procontic systems.[32][34][35][36][37][38]

In 1959 Texaco’s Port Arthur refinery became the first chemical plant to use digital control.[39] Conversion of factories to digital control began to spread rapidly in the 1970s as the price of computer hardware fell.

Significant applications

The automatic telephone switchboard was introduced in 1892 along with dial telephones.[40] By 1929, 31.9% of the Bell system was automatic. Automatic telephone switching originally used vacuum tube amplifiers and electro-mechanical switches, which consumed a large amount of electricity. Call volume eventually grew so fast that it was feared the telephone system would consume all electricity production, prompting Bell Labs to begin research on the transistor.[41]

The logic performed by telephone switching relays was the inspiration for the digital computer. The first commercially successful glass bottle blowing machine was an automatic model introduced in 1905.[42] The machine, operated by a two-man crew working 12-hour shifts, could produce 17,280 bottles in 24 hours, compared to 2,880 bottles made by a crew of six men and boys working in a shop for a day. The cost of making bottles by machine was 10 to 12 cents per gross compared to $1.80 per gross by the manual glassblowers and helpers.

Sectional electric drives were developed using control theory. Sectional electric drives are used on different sections of a machine where a precise differential must be maintained between the sections. In steel rolling, the metal elongates as it passes through pairs of rollers, which must run at successively faster speeds. In paper making the paper sheet shrinks as it passes around steam heated drying arranged in groups, which must run at successively slower speeds. The first application of a sectional electric drive was on a paper machine in 1919.[43] One of the most important developments in the steel industry during the 20th century was continuous wide strip rolling, developed by Armco in 1928.[44]

Before automation many chemicals were made in batches. In 1930, with the widespread use of instruments and the emerging use of controllers, the founder of Dow Chemical Co. was advocating continuous production.[45]

Self-acting machine tools that displaced hand dexterity so they could be operated by boys and unskilled laborers were developed by James Nasmyth in the 1840s.[46] Machine tools were automated with Numerical control (NC) using punched paper tape in the 1950s. This soon evolved into computerized numerical control (CNC).

Today extensive automation is practiced in practically every type of manufacturing and assembly process. Some of the larger processes include electrical power generation, oil refining, chemicals, steel mills, plastics, cement plants, fertilizer plants, pulp and paper mills, automobile and truck assembly, aircraft production, glass manufacturing, natural gas separation plants, food and beverage processing, canning and bottling and manufacture of various kinds of parts. Robots are especially useful in hazardous applications like automobile spray painting. Robots are also used to assemble electronic circuit boards. Automotive welding is done with robots and automatic welders are used in applications like pipelines.

Space/computer age

With the advent of the space age in 1957, controls design, particularly in the United States, turned away from the frequency-domain techniques of classical control theory and backed into the differential equation techniques of the late 19th century, which were couched in the time domain. During the 1940s and 1950s, German mathematician Irmgard Flugge-Lotz developed the theory of discontinuous automatic control, which became widely used in hysteresis control systems such as navigation systemsfire-control systems, and electronics. Through Flugge-Lotz and others, the modern era saw time-domain design for nonlinear systems (1961), navigation (1960), optimal control and estimation theory (1962), nonlinear control theory (1969), digital control and filtering theory (1974), and the personal computer (1983).

Advantages and disadvantages

Perhaps the most cited advantage of automation in industry is that it is associated with faster production and cheaper labor costs. Another benefit could be that it replaces hard, physical, or monotonous work.[47] Additionally, tasks that take place in hazardous environments or that are otherwise beyond human capabilities can be done by machines, as machines can operate even under extreme temperatures or in atmospheres that are radioactive or toxic. They can also be maintained with simple quality checks. However, at the time being, not all tasks can be automated, and some tasks are more expensive to automate than others. Initial costs of installing the machinery in factory settings are high, and failure to maintain a system could result in the loss of the product itself. Moreover, some studies seem to indicate that industrial automation could impose ill effects beyond operational concerns, including worker displacement due to systemic loss of employment and compounded environmental damage; however, these findings are both convoluted and controversial in nature, and could potentially be circumvented.[48]

The main advantages of automation are:

  • Increased throughput or productivity.
  • Improved quality or increased predictability of quality.
  • Improved robustness (consistency), of processes or product.
  • Increased consistency of output.
  • Reduced direct human labor costs and expenses.
  • Installation in operations reduces cycle time.
  • Can complete tasks where a high degree of accuracy is required.
  • Replaces human operators in tasks that involve hard physical or monotonous work (e.g., using one forklift with a single driver instead of a team of multiple workers to lift a heavy object)[49]
  • Reduces some occupational injuries (e.g., fewer strained backs from lifting heavy objects)
  • Replaces humans in tasks done in dangerous environments (i.e. fire, space, volcanoes, nuclear facilities, underwater, etc.)
  • Performs tasks that are beyond human capabilities of size, weight, speed, endurance, etc.
  • Reduces operation time and work handling time significantly.
  • Frees up workers to take on other roles.
  • Provides higher level jobs in the development, deployment, maintenance and running of the automated processes.

The main disadvantages of automation are:

  • Possible security threats/vulnerability due to increased relative susceptibility for committing errors.
  • Unpredictable or excessive development costs.
  • High initial cost.
  • Displaces workers due to job replacement.

Relationship to unemployment

Main article: Technological unemployment

Research by Carl Benedikt Frey and Michael Osborne of the Oxford Martin School argued that employees engaged in “tasks following well-defined procedures that can easily be performed by sophisticated algorithms” are at risk of displacement, and 47 percent of jobs in the US were at risk. The study, released as a working paper in 2013 and published in 2017, predicted that automation would put low-paid physical occupations most at risk, by surveying a group of colleagues on their opinions.[100] However, according to a study published in McKinsey Quarterly[101] in 2015 the impact of computerization in most cases is not the replacement of employees but automation of portions of the tasks they perform.[102] The methodology of the McKinsey study has been heavily criticized for being intransparent and relying on subjective assessments.[103] The methodology of Frey and Osborne has been subjected to criticism, as lacking evidence, historical awareness, or credible methodology.[104][105] In addition the OECD, found that across the 21 OECD countries, 9% of jobs are automatable.[106]

The Obama White House has pointed out that every 3 months “about 6 percent of jobs in the economy are destroyed by shrinking or closing businesses, while a slightly larger percentage of jobs are added”.[107] A recent MIT economics study of automation in the United States from 1990 to 2007 found that there may be a negative impact on employment and wages when robots are introduced to an industry. When one robot is added per one thousand workers, the employment to population ratio decreases between 0.18–0.34 percentages and wages are reduced by 0.25–0.5 percentage points. During the time period studied, the US did not have many robots in the economy which restricts the impact of automation. However, automation is expected to triple (conservative estimate) or quadruple (a generous estimate) leading these numbers to become substantially higher.[108]

Based on a formula by Gilles Saint-Paul, an economist at Toulouse 1 University, the demand for unskilled human capital declines at a slower rate than the demand for skilled human capital increases.[109] In the long run and for society as a whole it has led to cheaper products, lower average work hours, and new industries forming (i.e., robotics industries, computer industries, design industries). These new industries provide many high salary skill-based jobs to the economy. By 2030, between 3 and 14 percent of the global workforce will be forced to switch job categories due to automation eliminating jobs in an entire sector. While the number of jobs lost to automation is often offset by jobs gained from technological advances, the same type of job loss is not the same one replaced and that leading to increasing unemployment in the lower-middle class. This occurs largely in the US and developed countries where technological advances contribute to higher demand for highly skilled labor but demand for middle-wage labor continues to fall. Economists call this trend “income polarization” where unskilled labor wages are driven down and skilled labor is driven up and it is predicted to continue in developed economies.[110]

Unemployment is becoming a problem in the United States due to the exponential growth rate of automation and technology. According to Kim, Kim, and Lee (2017), “A seminal study by Frey and Osborne in 2013 predicted that 47% of the 702 examined occupations in the United States faced a high risk of decreased employment rate within the next 10–25 years as a result of computerization”. (p. 1). As many jobs are becoming obsolete, which is causing job displacement, one possible solution would be for the government to assist with a universal basic income (UBI) program. UBI would be a guaranteed, non-taxed income of around $1000 dollars per month, paid to all U.S. citizens over the age of 21. UBI would help those who are displaced, take on jobs that pay less money and still afford to get by. It would also give those that are employed with jobs that are likely to be replaced by automation and technology, extra money to spend on education and training on new demanding employment skills. UBI however, should be seen as a short term solution because it doesn’t fully address the issue of income inequality which will be exacerbated by job displacement.