Mechatronics (Part-XIV)- Exploring Industrial Automation

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Check Out The Significant Roles Of Automation In Industries

Here we continue with the fourteenth part of our blog on mechatronics. Those who have missed our thirteenth blog can read it from Here. It will help to connect with the fourteenth part of the blog discussing about the significant applications of automation in industries. Let us explore the blog to find out in more details. Automation and technology would be a great boon if it were creative, if were more leisure, more opportunity to engage in raising family, providing guidance to the young, all the staff we say we need.

What is Industrial Automation?

Industrial automation deals primarily with the automation of manufacturing, quality control and material handling processes. General purpose controllers for industrial processes include Programmable logic controllers, stand-alone I/O modules, and computers. Industrial automation is to replace the decision making of humans and manual command-response activities with the use of mechanised equipment and logical programming commands. One trend is increased use of Machine vision to provide automatic inspection and robot guidance functions; another is a continuing increase in the use of robots. Industrial automation is simply required in industries. The integration of control and information across the enterprise enables industries to optimise industrial process operations. Energy efficiency in industrial processes has become a higher priority. Semiconductor companies like Infineon Technologies are offering 8-bit micro-controller applications for example found in motor controls, general purpose pumps, fans, and e-bikes to reduce energy consumption and thus increase efficiency.

Industry 4.0

The rise of industrial automation is directly tied to the “fourth industrial revolution”, which is better known now as Industry 4.0. Originating from Germany, Industry 4.0 encompasses numerous devises, concepts, and machines. It, along with the advancement of the Industrial Internet of Things (formally known as the IoT or IIoT) which is “Internet of Things is a seamless integration of diverse physical objects in the Internet through a virtual representation”. These new revolutionary advancements have drawn attention to the world of automation in an entirely new light and shown ways for it to grow to increase productivity and efficiency in machinery and manufacturing facilities. Industry 4.0 works with the IIoT and software/hardware to connect in a way that (through communication technologies) add enhancements and improve manufacturing processes. Being able to create smarter, safer, and more advanced manufacturing is now possible with these new technologies. It opens up a manufacturing platform that is more reliable, consistent, and efficient that before. Implementation of systems such as SCADA is an example of software that takes place in Industrial Automation today. SCADA is supervisory data collection software, just one of the many used in Industrial Automation. Industry 4.0 vastly covers many areas in manufacturing and will continue to do so as time goes on.

Industrial Robotics

Industrial robotics is a sub-branch in the industrial automation that aids in various manufacturing processes. Such manufacturing processes include; machining, welding, painting, assembling and material handling to name a few. Industrial robots utilizes various mechanical, electrical as well as software systems to allow for high precision, accuracy and speed that far exceeds any human performance. The birth of industrial robot came shortly after World War II as United States saw the need for a quicker way to produce industrial and consumer goods. Servos, digital logic and solid state electronics allowed engineers to build better and faster systems and overtime these systems were improved and revised to the point where a single robot is capable of running 24 hours a day with little or no maintenance. In 1997, there were 700,000 industrial robots in use, the number has risen to 1.8M in 2017.

To be continued in the next blog...

Mechatronics (Part-XIII)- Smart Automations In Highways, Home And Laboratory Technologies

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Know About The Applications Of Smart Automations In Highways, Home and Laboratory Technologies

Now we continue with the thirteenth part of our blog on mechatronics. Those who have missed our twelfth blog can read it from Here. It will help to connect with the thirteenth part of the blog discussing about the applications of smart automations in highways, home and laboratory technologies. Let us explore the blog to find out in more details. By 2018, automation is going to be in full swing in the world. There are estimates that it could replace 50 percent of our jobs. That is an enormous shift. But even if we go through a phase where we have an unemployment valley from automation, there will be new jobs and new things for us to do.

How Automation Emerged in Highway?

As demands for safety and mobility have grown and technological possibilities have multiplied, interest in automation has grown. Seeking to accelerate the development and introduction of fully automated vehicles and highways, the United States Congress authorized more than $650 million over six years for intelligent transport systems (ITS) and demonstration projects in the 1991 Intermodal Surface Transportation Efficiency Act (ISTEA). Congress legislated in ISTEA that "the Secretary of Transportation shall develop an automated highway and vehicle prototype from which future fully automated intelligent vehicle-highway systems can be developed. Such development shall include research in human factors to ensure the success of the man-machine relationship. The goal of this program is to have the first fully automated highway roadway or an automated test track in operation by 1997. This system shall accommodate installation of equipment in new and existing motor vehicles". Full automation commonly defined as requiring no control or very limited control by the driver; such automation would be accomplished through a combination of sensor, computer, and communications systems in vehicles and along the roadway. Fully automated driving would, in theory, allow closer vehicle spacing and higher speeds, which could enhance traffic capacity in places where additional road building is physically impossible, politically unacceptable, or prohibitively expensive. Automated controls also might enhance road safety by reducing the opportunity for driver error, which causes a large share of motor vehicle crashes. Other potential benefits include improved air quality (as a result of more-efficient traffic flows), increased fuel economy, and spin-off technologies generated during research and development related to automated highway systems.

Automation in Waste Management and Home

Automated waste collection trucks prevent the need for as many workers as well as easing the level of labour required to provide the service. Home automation (also called domotics) designates an emerging practice of increased automation of household appliances and features in residential dwellings, particularly through electronic means that allow for things impracticable, overly expensive or simply not possible in recent past decades.

Automation in Laboratory Technology

Automation is essential for many scientific and clinical applications. Therefore, automation has been extensively employed in laboratories. From as early as 1980 fully automated laboratories have already been working. However, automation has not become widespread in laboratories due to its high cost. This may change with the ability of integrating low-cost devices with standard laboratory equipment. Auto samplers are common devices used in laboratory automation.

To be continued in the next blog...

Mechatronics (Part-XII)- Automation In Recent And Emerging Applications

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Check Out The Role Of Automation In Recent And Emerging Applications

Here we continue with the twelfth part of our blog on mechatronics. Those who have missed our eleventh blog can read it from Here. It will help to connect with the twelfth part of the blog discussing about the different role of automation in recent and emerging applications. Let us explore the blog to find out in more details. Automation provides us with wondrous increases of production and information, but does it tell us what to do with men the machines displace? Modern industry gives us the capacity for unparallel wealth-but where is our capacity to make the wealth meaningful to the poor of every nation?

Cognitive Automation

Cognitive automation, as a subset of artificial intelligence is an emerging genus of automation enabled by cognitive computing. Its primary concern is the automation of clerical tasks and workflows that consist of structuring unstructured data. Cognitive automation relies on multiple disciplines: natural language processing, real-time computing, machine learning algorithms, big data analytics and evidence-based learning. According to Deloitte, cognitive automation enables the replication of human tasks and judgment "at rapid speeds and considerable scale". Such tasks include:

• Document redaction
• Data extraction and document synthesis / reporting
• Contract management
• Natural language search
• Customer, employee, and stakeholder on boarding
• Manual activities and verification
• Follow up and email communications

Recent and Emerging Applications- Automated Retail

i) Food and Drink

The food retail industry has started to apply automation to the ordering process; McDonald's has introduced touch screen ordering and payment systems in many of its restaurants, reducing the need for as many cashier employees. The University of Texas at Austin has introduced fully automated cafe retail locations. Some Cafes and restaurants have utilized mobile and tablet "apps" to make the ordering process more efficient by customers ordering and paying on their device. Some restaurants have automated food delivery to customers’ tables using a Conveyor belt system. The use of robots is sometimes employed to replace waiting staff.

ii) Stores

Many supermarkets and even smaller stores are rapidly introducing Self checkout systems reducing the need for employing checkout workers. In the United States, the retail industry employs 15.9 million people as of 2017 (around 1 in 9 Americans in the workforce). Globally, an estimated 192 million workers could be affected by automation according to research by Eurasia Group. 

Online shopping could be considered a form of automated retail as the payment and checkout are through an automated Online transaction processing system, with the share of online retail accounting jumping from 5.1% in 2011 to 8.3% in 2016. However, two-thirds of books, music and films are now purchased online. In addition, automation and online shopping could reduce demands for shopping malls, and retail property, which in America is currently estimated to account for 31% of all commercial property or around 7 billion square feet. Amazon has gained much of the growth in recent years for online shopping, accounting for half of the growth in online retail in 2016. Other forms of automation can also be an integral part of online shopping, for example the deployment of automated warehouse robotics such as that applied by Amazon using Kiva Systems.

iii) Automated Mining

Automated mining involves the removal of human labor from the mining process. The mining industry is currently in the transition towards automation. Currently it can still require a large amount of human capital, particularly in the third world where labor costs are low so there is less incentive for increasing efficiency through automation.

iv) Automated Video Surveillance

The Defense Advanced Research Projects Agency (DARPA) started the research and development of automated visual surveillance and monitoring (VSAM) program, between 1997 and 1999, and airborne video surveillance (AVS) programs, from 1998 to 2002. Currently, there is a major effort underway in the vision community to develop a fully automated tracking surveillance system. Automated video surveillance monitors people and vehicles in real time within a busy environment. Existing automated surveillance systems are based on the environment they are primarily designed to observe, i.e., indoor, outdoor or airborne, the amount of sensors that the automated system can handle and the mobility of sensor, i.e., stationary camera vs. mobile camera. The purpose of a surveillance system is to record properties and trajectories of objects in a given area, generate warnings or notify designated authority in case of occurrence of particular events.

To be continued in the next blog...

 

Mechatronics (Part-XI)- Automation Tools And Limitations

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Know About The Different Automation Tools And Their Limitations

Now we continue with the eleventh part of our blog on mechatronics. Those who have missed our tenth blog can read it from Here. It will help to connect with the eleventh part of the blog discussing different automation tools and their limitations. Let us explore the blog to find out in more details. Automation is a great profit but it's a real potential trouble area for society. Automation is going to cause unemployment, and we need to prepare it.

Automation Tools

Engineers can now have numerical control over automated devices. The result has been a rapidly expanding range of applications and human activities. Computer-aided technologies now serve as the basis for mathematical and organizational tools used to create complex systems. Notable examples of CAx include Computer-aided design(CAD software) and Computer-aided manufacturing (CAM software). The improved design, analysis, and manufacture of products enabled by CAx has been beneficial for industry. Information technology, together with industrial machinery and processes, can assist in the design, implementation, and monitoring of control systems. One example of an industrial control system is a programmable logic controller (PLC). PLCs are specialized hardened computers which are frequently used to synchronize the flow of inputs from (physical) sensors and events with the flow of outputs to actuators and events. 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. Service personnel who monitor and control through HMIs can be called by different names. In industrial process and manufacturing environments, they are called operators or something similar. In boiler houses and central utilities departments they are called stationary engineers. Different types of automation tools exist:

• ANN –Artificial neural network
• DCS –Distributed Control System
• HMI –Human Machine Interface
• SCADA –Supervisory Control and Data Acquisition
• PLC –Programmable Logic Controller
• Instrumentation
• Motion control
• Robotics

When it comes to factory automation, Host Simulation Software (HSS) is a commonly used testing tool that is used to test the equipment software. HSS is used to test equipment performance with respect to Factory Automation standards (timeouts, response time, processing time).

Limitations to Automation

Current technology is unable to automate all the desired tasks. Many operations using automation have large amounts of invested capital and produce high volumes of product, making malfunctions extremely costly and potentially hazardous. Therefore, some personnel are needed to ensure that the entire system functions properly and that safety and product quality are maintained. As a process becomes increasingly automated, there is less and less labor to be saved or quality improvement to be gained. This is an example of both diminishing returns and the logistic function. As more and more processes become automated, there are fewer remaining non-automated processes. This is an example of exhaustion of opportunities. New technological paradigms may however set new limits that surpass the previous limits.

Current Limitation

Many roles for humans in industrial processes presently lie beyond the scope of automation. Human-level pattern recognition, language comprehension, and language production ability are well beyond the capabilities of modern mechanical and computer systems (but see Watson (computer)). 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. Overcoming these obstacles is a theorized path to post-scarcity economics.

Paradox Automation

The paradox of automation says that the more efficient the automated system, the more crucial the human contribution of the operators. Humans are less involved, but their involvement becomes more critical.If an automated system has an error, it will multiply that error until it’s fixed or shut down. This is where human operators come in.A fatal example of this was Air France Flight 447, where a failure of automation put the pilots into a manual situation they were not prepared for. 

To be continued in the next blog...

Mechatronics (Part-X)- Automation In Manufacturing And Health Industries

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Know About The Role Of Automation In Various Sectors Like Manufacturing And Health Industries

Here we continue with the tenth part of our blog on mechatronics. Those who have missed our ninth blog can read it from Here. It will help to connect with the tenth part of the blog discussing about the role of automation in manufacturing and health industries. Let us explore the blog to find out in more details. In words of Alain Dehaze:

"Warp speed developments in technology-automation,artificial intelligence, and the arrival of the sharing economy-are transforming how we work.Beyond technology, traditional working patterns are also being disrupted by changes in society,organizations and workforce management,leading to the rise of a more independent and dispersed workforce".

Automation in Manufacturing

Lights out manufacturing is a production system with no human workers, to eliminate labor costs. Lights Out Manufacturing grew in popularity in the U.S. when General Motors in 1982 implemented humans “hands-off” manufacturing in order to “replace risk-averse bureaucracy with automation and robots”. However, the factory never reached full “lights out” status. The expansion of Lights Out Manufacturing requires:

• Reliability of equipment
• Long term mechanic capabilities
• Planned preventative maintenance
• Commitment from the staff

Automation in Health

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 vice versa.[citation needed] Hazardous operations, such as oil refining, the manufacturing of industrial chemicals, and all forms of metal working, were always early contenders for automation. The automation of vehicles could prove to have a substantial impact on the environment, although the nature of this impact could be beneficial or harmful depending on several factors. Because automated vehicles are much less likely to get into accidents compared to human-driven vehicles, some precautions built into current models (such as anti-lock brakes or laminated glass) would not be required for self-driving versions. Removing these safety features would also significantly reduce the weight of the vehicle, thus increasing fuel economy and reducing emissions per mile. Self-driving vehicles are also more precise with regard to acceleration and breaking, and this could contribute to reduced emissions. Self-driving cars could also potentially utilize fuel-efficient features such as route mapping that is able to calculate and take the most efficient routes. Despite this potential to reduce emissions, some researchers theorize that an increase of production of self-driving cars could lead to a boom of vehicle ownership and use. This boom could potentially negate any environmental benefits of self-driving cars if a large enough number of people begin driving personal vehicles more frequently. Automation of homes and home appliances is also thought to impact the environment, but the benefits of these features are also questioned. A study of energy consumption of automated homes in Finland showed that smart homes could reduce energy consumption by monitoring levels of consumption in different areas of the home and adjusting consumption to reduce energy leaks (such as automatically reducing consumption during the nighttime when activity is low). This study, along with others, indicated that the smart home’s ability to monitor and adjust consumption levels would reduce unnecessary energy usage. However, new research suggests that smart homes might not be as efficient as non-automated homes. A more recent study has indicated that, while monitoring and adjusting consumption levels does decrease unnecessary energy use, this process requires monitoring systems that also consume a significant amount of energy. This study suggested that the energy required to run these systems is so much so that it negates any benefits of the systems themselves, resulting in little to no ecological benefit.

Convertibility and Turnaround Time

Another major shift in automation is the increased demand for flexibility and convertibility in manufacturing processes. Manufacturers are increasingly demanding the ability to easily switch from manufacturing Product A to manufacturing Product B without having to completely rebuild the production lines. Flexibility and distributed processes have led to the introduction of Automated Guided Vehicles with Natural Features Navigation. Digital electronics helped too. Former analogue-based instrumentation was replaced by digital equivalents which can be more accurate and flexible, and offer greater scope for more sophisticated configuration, parametrization and operation. This was accompanied by the fieldbus revolution which provided a networked (i.e. a single cable) means of communicating between control systems and field level instrumentation, eliminating hard-wiring. Discrete manufacturing plants adopted these technologies fast. The more conservative process industries with their longer plant life cycles have been slower to adopt and analogue-based measurement and control still dominates. The growing use of Industrial Ethernet on the factory floor is pushing these trends still further, enabling manufacturing plants to be integrated more tightly within the enterprise, via the internet if necessary. Global competition has also increased demand for Reconfigurable Manufacturing Systems.

Continued in the next blog...

Mechatronics (Part-IX)- Significant Applications Of Automations In Space and Computers

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Find Out The Important Applications Of Automations In Computers and Space

Now we continue with the ninth part of our blog on mechatronics. Those who have missed our eighth blog can read it from Here. It will help to connect with the ninth part of the blog discussing about the advantages, disadvantages and societal impact of automationimportant applications of automations in space and computers. Let us explore the blog to find out in more details. In words of Mark Cuban:

“Whatever you are studying right now, if you are not getting up to speed on deep learning, neutral networks, and so on you lose. We are going through the process where software will automate software, automation will automate automation.”

Significant Applications of Automations

The automatic telephone switchboard was introduced in 1892 along with dial telephones. 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. 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. 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. One of the most important developments in the steel industry during the 20th century was continuous wide strip rolling, developed by Armco in 1928. Before automation many chemicals were made in batches. 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. 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 and Computer Advancements

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 systems, fire-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).

Continued in the next blog...

Mechatronics (Part-VIII)- Advantages, Disadvantages And Societal Impact Of Automation

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Find Out The Advantages, Disadvantages and Societal Impact Of Automation

Here we continue with the eighth part of our blog on mechatronics. Those who have missed our seventh blog can read it from Here. It will help to connect with the eighth part of the blog discussing about the advantages, disadvantages and societal impact of automation. Let us explore the blog to find out in more details. In words of Tom Peters:

“For a blue-collar worker, the driving force behind change was factory automation using programmable machine tools. For an office worker, it’s office automation using computer technology: enterprise-resource-planning systems, groupware, intranets, extranets, expert systems, the Web and E-Commerce.”

Advantages and Disadvantages of Automation

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. 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. 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)
• 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.
• Leads to further environmental damage and could compound climate change

Societal Impact of Automation

Increased automation can often cause workers to feel anxious about losing their jobs as technology renders their skills or experience unnecessary. Early in the Industrial Revolution, when inventions like the steam engine were making some job categories expendable, workers forcefully resisted these changes. Luddites, for instance, were English textile workers who protested the introduction of weaving machines by destroying them. Similar movements have sprung up periodically ever since. For most of the nineteenth and twentieth centuries, the most influential of these movements were led by organized labor, which advocated for the retraining of workers whose jobs were rendered redundant by machines. Currently, the relative anxiety about automation reflected in opinion polls seems to correlate closely with the strength of organized labor in that region or nation. For example, while a recent study by the Pew Research Center indicated that 72% of Americans are worried about increasing automation in the workplace, 80% of Swedes see automation and artificial intelligence as a good thing, due to the country’s still-powerful unions and a more robust national safety net. Automation is already contributing significantly to unemployment, particularly in nations where the government does not proactively seek to diminish its impact. In the United States, 47% of all current jobs have the potential to be fully automated by 2033, according to the research of experts Carl Benedikt Frey and Michael Osborne. Furthermore, wages and educational attainment appear to be strongly negatively correlated with an occupation’s risk of being automated. Prospects are particularly bleak for occupations that do not presently require a university degree, such as truck driving. Even in high-tech corridors like Silicon Valley, concern is spreading about a future in which a sizable percentage of adults have little chance of sustaining gainful employment. As the example of Sweden suggests, however, the transition to a more automated future need not inspire panic, if there is sufficient political will to promote the retraining of workers whose positions are being rendered obsolete.

Continued in the next blog...

Mechatronics (Part-VII)- Control Systems In Automation

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Find Out In Details About The Control Systems Used In Automation

Now we continue with the seventh part of our blog on mechatronics. Those who have missed our sixth blog can read it from Here. It will help to connect with the seventh part of the blog discussing about control systems used in automation. Let us explore the blog to find out in more details.

Open and Closed Loop Control in Automation

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. 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.' 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. 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. The theoretical basis of closed loop automation is control theory.

Control Actions

1. Discrete Control (On/Off)

One of the simplest types of control is on-off control. An example is the 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.

2. PID Controller 

A proportional–integral–derivative controller (PID controller) is a control loop feedback mechanism (controller) widely used in industrial control systems. In a PID loop, the controller continuously calculates an error value  as the difference between a desired set point and a measured process variable and applies a correction based on proportional, integral, and derivative terms, respectively (sometimes denoted P, I, 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 analogue control systems; originally in mechanical controllers, and then using discrete electronics and latterly in industrial process computers.

3. Sequential Control and Logical Sequence on System State Control

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. An 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 push button 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. 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 insure 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.

Continued in the next blog...

Mechatronics (Part-VI)- Introducing Industrial Automation

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All You Need To Know About Industrial Automation

Here we continue with the sixth part of our blog on mechatronics. Those who have missed our fifth blog can read it from Here. It will help to connect with the sixth part of the blog introducing about industrial automation. Let us explore the blog to find out in more details. In word of Bill Gates:

“The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the efficiency”.

What is Automation?

Automation is the technology by which a process or procedure is performed without human assistance. Automation 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. Some processes have been completely automated. 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, hydraulic, pneumatic, 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 labour savings, savings in electricity costs, savings in material costs, and improvements to quality, accuracy and precision. The term automation, inspired by the earlier word automatic (coming from automaton), was not widely used before 1947, when Ford established an automation department. It was during this time that industry was rapidly adopting feedback controllers, which were introduced in the 1930s. 

Phrase 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. 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. Two-step level controls for fluids, a form of discontinuous variable structure controls, was developed by the Banu Musa brothers. They also described a feedback controller. Thomas Newcomen invented the steam engine in 1713, and this date marks the accepted beginning of the Industrial Revolution; however, its roots can be traced back into the 17th century. 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. 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. An automatic flour mill was developed by Oliver Evans in 1785, making it the first completely automated industrial process.The centrifugal governor, which was invented by Christian Huygens in the seventeenth century, was used to adjust the gap between millstones. Another centrifugal governor was used by a Mr. Bunce of England in 1784 as part of a model steam crane. 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. 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. 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-Lotzdeveloped the theory of discontinuous automatic controls, which found military applications during the Second World War to fire control systems and aircraft navigation systems.

Continued in the next blog...

Mechatronics (Part-V)- Know Everything About Servomechanism

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All You Need To Know In Details About Servomechanism

Now we continue with the fifth part of our blog on mechatronics. Those who have missed our fourth blog can read it from Here. It will help to connect with the fifth part of the blog discussing about the automated device in short known as Servo and the underlying mechanism known as Servomechanism. Let us explore the blog to find out in more details.

In control engineering a servomechanism, sometimes shortened to servo, is an automatic device that uses error-sensing negative feedback to correct the action of a mechanism. It usually includes a built-in encoder or other position feedback mechanism to ensure the output is achieving the desired effect.The term correctly applies only to systems where the feedback or error-correction signals help control mechanical position, speed or other parameters.For example, an automotive power window control is not a servomechanism, as there is no automatic feedback that controls position.By contrast a car's cruise control uses closed-loop feedback, which classifies it as a servomechanism.

Applications of Servomechanism

Position Control

A common type of servo provides position control. Commonly, servos are electrical, hydraulic or pneumatic. They operate on the principle of negative feedback, where the control input is compared to the actual position of the mechanical system as measured by some sort of transducer at the output. Any difference between the actual and wanted values (an "error signal") is amplified (and converted) and used to drive the system in the direction necessary to reduce or eliminate the error. This procedure is one widely used application of control theory. Typical servos can give a rotary (angular) or linear output.

Speed Control

Speed control via a governor is another type of servomechanism. The steam engine uses mechanical governors; another early application was to govern the speed of water wheels. Prior to World War II the constant speed propeller was developed to control engine speed for maneuvering aircraft. Fuel controls for gas turbine engines employ either hydromechanical or electronic governing.

Others

Speed control via a governor is another type of servomechanism. The steam engine uses mechanical governors; another early application was to govern the speed of water wheels. Prior to World War II the constant speed propeller was developed to control engine speed for maneuvering aircraft. Fuel controls for gas turbine engines employ either hydromechanical or electronic governing.

Servomotor

A servomotor is a specific type of motor that is combined with a rotary encoder or a potentiometer to form a servomechanism. This assembly may in turn form part of another servomechanism. A potentiometer provides a simple analog signal to indicate position, while an encoder provides position and usually speed feedback, which by the use of a PID controller allow more precise control of position and thus faster achievement of a stable position (for a given motor power). Potentiometers are subject to drift when the temperature changes whereas encoders are more stable and accurate.Servomotors are used for both high-end and low-end applications. On the high end are precision industrial components that use a rotary encoder. On the low end are inexpensive radio control servos (RC servos) used in radio-controlled models which use a free-running motor and a simple potentiometer position sensor with an embedded controller. The term servomotor generally refers to a high-end industrial component while the term servo is most often used to describe the inexpensive devices that employ a potentiometer. Stepper motors are not considered to be servomotors, although they too are used to construct larger servomechanisms. Stepper motors have inherent angular positioning, owing to their construction, and this is generally used in an open-loop manner without feedback. They are generally used for medium-precision applications. RC servos are used to provide actuation for various mechanical systems such as the steering of a car, the control surfaces on a plane, or the rudder of a boat. Due to their affordability, reliability, and simplicity of control by microprocessors, they are often used in small-scale robotics applications. A standard RC receiver (or a microcontroller) sends pulse-width modulation (PWM) signals to the servo. The electronics inside the servo translate the width of the pulse into a position. When the servo is commanded to rotate, the motor is powered until the potentiometer reaches the value corresponding to the commanded position.

To be continued in the next blog...

Mechatronics (Part-IV)- Image Processing From Machine Vision In Automatic Inspection

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Find Out About The Processing Of Images Obtained From Machine Vision For Automatic Inspection

Here we continue with the fourth part of our blog on mechatronics. Those who have missed our third blog can read it from Here. It will help to connect with the fourth part of the blog discussing about the processing of images obtained from machine vision for the purpose of automatic inspection. Let us explore the blog to find out in more details.

Image Processing

After an image is acquired, it is processed.Multiple stages of processing are generally used in a sequence that ends up as a desired result. A typical sequence might start with tools such as filters which modify the image, followed by extraction of objects, then extraction (e.g. measurements, reading of codes) of data from those objects, followed by communicating that data, or comparing it against target vales to create and communicate "pass/fail" results. Machine vision image processing methods include:

Stitching/Registration: Combining of adjacent 2D or 3D images.

Thresholding: Thresholding starts with setting or determining a gray value that will be useful for the following steps. The value is then used to separate portions of the image, and sometimes to transform each portion of the image to simply black and white based on whether it is below or above that grayscale value.

Pixel Counting: Counts the number of light or dark pixels

Segmentation: Partitioning a digital image into multiple segments to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze.

Edge detection: finding object edges.

Color Analysis: Identify parts, products and items using color, assess quality from color, and isolate features using color.

Blob Detection and Extraction: Inspecting an image for discrete blobs of connected pixels (e.g. a black hole in a grey object) as image landmarks. 

Neural Net / Deep Learning / Machine Learning Processing: weighted and self-training multi-variable decision making.

Pattern Recognition: Including template matching. Finding, matching, and/or counting specific patterns. This may include location of an object that may be rotated, partially hidden by another object, or varying in size.

Optical Character Recognition: Automated reading of text such as serial numbers.

Gauging/Metrology: Measurement of object dimensions (e.g. in pixels, inches or millimeters) 

Comparison Against Target Values to Determine a "Pass or Fail" or "Go/No Go" Result: For example, with code or bar code verification, the read value is compared to the stored target value. For gauging, a measurement is compared against the proper value and tolerances. For verification of alpha-numberic codes, the OCR'd value is compared to the proper or target value. For inspection for blemishes, the measured size of the blemishes may be compared to the maximums allowed by quality standards.

Output

A common output from automatic inspection systems is pass/fail decisions. These decisions may in turn trigger mechanisms that reject failed items or sound an alarm. Other common outputs include object position and orientation information for robot guidance systems.Additionally, output types include numerical measurement data, data read from codes and characters, counts and classification of objects, displays of the process or results, stored images, alarms from automated space monitoring MV systems, and process control signals. This also includes user interfaces, interfaces for the integration of multi-component systems and automated data interchange.

Imaging Based Robot Guidance

Machine vision commonly provides location and orientation information to a robot to allow the robot to properly grasp the product. This capability is also used to guide motion that is simpler than robots, such as a 1 or 2 axis motion controller.The overall process includes planning the details of the requirements and project, and then creating a solution. This section describes the technical process that occurs during the operation of the solution. Many of the process steps are the same as with automatic inspection except with a focus on providing position and orientation information as the end result.

Market

The global Machine Vision market is expected to reach USD 15.46 billion by the end of 2022 with 8.18% CAGR during the forecast period 2017-2022. Machine Vision Market is growing with positive growth in all regions. Increasing application areas year on year and advancement in technology and integration is driving the market on a global scale. Asia Pacific is dominating the global market with more than 30% of market share followed by Europe standing as the second biggest market due to heavy demand from the automotive and healthcare industry. North America stands as the third biggest market.

Continued in the next blog...

Mechatronics (Part-III)- Machine Vision In Automatic Inspection

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Find Out In Details About The Role Of Machine Vision In Automatic Inspection

Now we continue with the third part of our blog on mechatronics. Those who have missed our second blog can read it from Here. It will help to connect with the third part of the blog discussing about the role of machine vision in automatic inspection. Let us explore the blog to find these out in more details.

Machine vision (MV) is the technology and methods used to provide imaging-based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine vision is a term encompassing a large number of technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as a systems engineering discipline can be considered distinct from computer vision, a form of computer science. It attempts to integrate existing technologies in new ways and apply them to solve real world problems. The term is also used in a broader sense by trade shows and trade groups; this broader definition also encompasses products and applications most often associated with image processing. Definitions of the term "Machine vision" vary, but all include the technology and methods used to extract information from an image, as opposed to image processing, where the output is another image. The information extracted can be a simple good-part/bad-part signal, or more a complex set of data such as the identity, position and orientation of each object in an image. The information can be used for such applications as automatic inspection, damage quantification and robot and process guidance in industry, or for security monitoring. This field encompasses a large number of technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as a systems engineering discipline can be considered distinct from computer vision, a form of basic computer science; machine vision attempts to integrate existing technologies in new ways and apply them to solve real world problems in a way that meets the requirements of industrial automation and similar application areas.The term is also used in a broader sense by trade shows and trade groups such as the Automated Imaging Association and the European Machine Vision Association. This broader definition also encompasses products and applications most often associated with image processing.The primary uses for machine vision are automatic inspection and industrial robot/process guidance.

Imaging Based Automatic Inspection, Sorting and Damage Quantification

The primary uses for machine vision are imaging-based automatic inspection and sorting and robot guidance; in this section the former is abbreviated as "automatic inspection". The overall process includes planning the details of the requirements and project, and then creating a solution.A number of previous studies have also focused on machine vision applications in infrastructure contexts to estimate damage and load states. 

Methods and Sequence of Operation

The first step in the automatic inspection sequence of operation is acquisition of an image, typically using cameras, lenses, and lighting that has been designed to provide the differentiation required by subsequent processing. MV software packages and programs developed in them then employ various digital image processing techniques to extract the required information, and often make decisions (such as pass/fail) based on the extracted information.

Equipment

The components of an automatic inspection system usually include lighting, a camera or other imager, a processor, software, and output devices. The imaging device (e.g. camera) can either be separate from the main image processing unit or combined with it in which case the combination is generally called a smart camera or smart sensor. When separated, the connection may be made to specialized intermediate hardware, a custom processing appliance, or a frame grabber within a computer using either an analog or standardized digital interface (Camera Link, CoaXPress). MV implementations also use digital cameras capable of direct connections (without a framegrabber) to a computer via FireWire, USB or Gigabit Ethernet interfaces.

Imaging

While conventional (2D visible light) imaging is most commonly used in MV, alternatives include multispectral imaging, hyperspectral imaging, imaging various infrared bands, line scan imaging, 3D imaging of surfaces and X-ray imaging. Key divisions within MV 2D visible light imaging are monochromatic vs. color, resolution, and whether or not the imaging process is simultaneous over the entire image, making it suitable for moving processes. Though the vast majority of machine vision applications are solved using two-dimensional imaging, machine vision applications utilizing 3D imaging are a growing niche within the industry. The most commonly used method for 3D imaging is scanning based triangulation which utilizes motion of the product or image during the imaging process. A laser is projected onto the surfaces of an object and viewed from a different angle. In machine vision this is accomplished with a scanning motion, either by moving the workpiece, or by moving the camera & laser imaging system. The line is viewed by a camera from a different angle; the deviation of the line represents shape variations. Lines from multiple scans are assembled into a depth map or point cloud.Stereoscopic vision is used in special cases involving unique features present in both views of a pair of cameras. Other 3D methods used for machine vision are time of flight and grid based. One method is grid array based systems using pseudorandom structured light system as employed by the Microsoft Kinect system circa 2012.

Continued in the next blog...

Mechatronics (Part-II)- Machine Vision Imaging Based Automatic Inspection

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Know About Automatic Inspection Based On Machine Vision Imaging

Here we continue with the second part of our blog on mechatronics. Those who have missed our first blog can read it from Here. It will help to connect with the second part of the blog discussing about automatic inspection based on machine vision imaging. Let us explore the blog to find out in more details. In words of Kan Goldberg: 

"We're fascinated with robots because they are reflections of ourselves".

Introducing Machine Vision

Machine vision (MV) is the technology and methods used to provide imaging-based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine vision is a term encompassing a large number of technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as a systems engineering discipline can be considered distinct from computer vision, a form of computer science. It attempts to integrate existing technologies in new ways and apply them to solve real world problems. The term is also used in a broader sense by trade shows and trade groups; this broader definition also encompasses products and applications most often associated with image processing. Definitions of the term "Machine vision" vary, but all include the technology and methods used to extract information from an image, as opposed to image processing, where the output is another image. The information extracted can be a simple good-part/bad-part signal, or more a complex set of data such as the identity, position and orientation of each object in an image. The information can be used for such applications as automatic inspection, damage quantification and robot and process guidance in industry, or for security monitoring.  This field encompasses a large number of technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as a systems engineering discipline can be considered distinct from computer vision, a form of basic computer science; machine vision attempts to integrate existing technologies in new ways and apply them to solve real world problems in a way that meets the requirements of industrial automation and similar application areas. The term is also used in a broader sense by trade shows and trade groups such as the Automated Imaging Association and the European Machine Vision Association. This broader definition also encompasses products and applications most often associated with image processing. The primary uses for machine vision are automatic inspection and industrial robot/process guidance. 

Imaging Based Automatic Inspection, Sorting and Damage Quantification

The primary uses for machine vision are imaging-based automatic inspection and sorting and robot guidance. in this section the former is abbreviated as "automatic inspection". The overall process includes planning the details of the requirements and project, and then creating a solution. A number of previous studies have also focused on machine vision applications in infrastructure contexts to estimate damage and load states.

Methods and Sequence of Operation

The first step in the automatic inspection sequence of operation is acquisition of an image, typically using cameras, lenses, and lighting that has been designed to provide the differentiation required by subsequent processing. MV software packages and programs developed in them then employ various digital image processing techniques to extract the required information, and often make decisions (such as pass/fail) based on the extracted information.

Equipments

The components of an automatic inspection system usually include lighting, a camera or other imager, a processor, software, and output devices.

Continued in the next blog...

Mechatronics (Part-I)- Streamline Multiphysics

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A Brief Introduction To The Multidisciplinary Field of Mechatronics 

Let us introduce the basic concept of mechatronics with a wonderful quote of Tracy Morgan indirectly reflecting the concept:

"I have friends who are black, white, purple, gay, straight, Martian, yellow, old, and young. I have friends who are animals and a few who I believe to be robots. All of them are people to me. In my mind, it's not about what you look like or what you do; it's about who you are inside".

Mechatronics is a multidisciplinary field of science that includes a combination of mechanical engineering, electronics, computer science engineering, telecommunications engineering, systems engineering and control engineering. As technology advances, the subfields of engineering multiply and adapt. Mechatronics' aim is a design process that unifies these subfields. Originally, mechatronics just included the combination of mechanics and electronics, therefore the word is a combination of mechanics and electronics; however, as technical systems have become more and more complex the definition has been broadened to include more technical areas. The word "mechatronics" originated in Japanese-English and was created by Tetsuro Mori, an engineer of Yaskawa Electric Corporation. The word "mechatronics" was registered as trademark by the company in Japan with the registration number of "46-32714" in 1971. However, afterward the company released the right of using the word to public, and the word "mechatronics" spread to the rest of the world. Nowadays, the word is translated in each language and the word is considered as an essential term for industry. French standard NF E 01-010 gives the following definition: “approach aiming at the synergistic integration of mechanics, electronics, control theory, and computer science within product design and manufacturing, in order to improve and/or optimize its functionality". Many people treat "mechatronics" as a modern buzzword synonymous with robotics and "electromechanical engineering". A mechatronics engineer unites the principles of mechanics, electronics, and computing to generate a simpler, more economical and reliable system. The term "mechatronics" was coined by Tetsuro Mori, the senior engineer of the Japanese company Yaskawa in 1969. An industrial robot is a prime example of a mechatronics system; it includes aspects of electronics, mechanics, and computing to do its day-to-day jobs. Engineering cybernetics deals with the question of control engineering of mechatronic systems. It is used to control or regulate such a system (see control theory). Through collaboration, the mechatronic modules perform the production goals and inherit flexible and agile manufacturing properties in the production scheme. Modern production equipment consists of mechatronic modules that are integrated according to a control architecture. The most known architectures involve hierarchy, polyarchy, heterarchy, and hybrid. The methods for achieving a technical effect are described by control algorithms, which might or might not utilize formal methods in their design. Hybrid systems important to mechatronics include production systems, synergy drives, planetary exploration rovers, automotive subsystems such as anti-lock braking systems and spin-assist, and everyday equipment such as autofocus cameras, video, hard disks, and CD players.

Continued in the next blog...