What is Mechatronics?
Mechatronics is a natural stage in the evolutionary process of modern engineering design. The development of the computer, and then the microcomputer, embedded computers, and associated information technologies and software advances, made mechatronics an imperative in the latter part of the twentieth century. Standing at the threshold of the twenty-first century, with expected advances in integrated bioelectro- mechanical systems, quantum computers, nano- and pico-systems, and other unforeseen developments, the future of mechatronics is full of potential and bright possibilities.

The definition of mechatronics has evolved since the original definition by the Yasakawa Electric Company. In trademark application documents, Yasakawa defined mechatronics in this way:
The word, mechatronics, is composed of “mecha” from mechanism and the “tronics” from electronics. In other words, technologies and developed products will be incorporating electronics more and more into mechanisms, intimately and organically, and making it impossible to tell where one ends and the other begins.

As in Book "MECHATRONICS AN INTRODUCTION" written by "Robert H. Bishop" Published by "CRC Press"

The task of the anaesthetist is to control the continuum between consciousness and unconsciousness, pain and analgesia, muscle activity and relaxation—inhibition of activation and enhancement of inhibition. During an operation, an anaesthetized patient is part of a ‘feedback circuit’ (Figure 1). Changes in variables such as blood pressure and respiratory rate are monitored and stability is restored by adjustments to ventilation and drug dosage. The decision-maker and controller in this loop is the anaesthetist, who will make an individual judgment on how best to respond to, say, low blood pressure, tachypnoea or a decreasing oxygen saturation. Computer programs employing ‘fuzzy logic’ are intended to imitate human thought processes in these complex circumstances but to function at greater speed. A simple computerized system might be based on the rule ‘if X then do Y’. The drawback of such programs is that a large number of rules are needed to deal with every possible situation. In addition, if two or more indices are being measured the rule then becomes ‘if X and Y, then Z’ and the number of rules multiplies vastly. Fuzzy logic works by drastically reducing the number of rules and using proportionate amounts of each rule; and it can also ‘learn’ by assessing responses to changes in output. It thus opens the way to automation in circumstances that would be difficult or impossible to model with simple linear mathematics.

"Fuzzy logic and decision-making in anaesthetics" by " Paul Grant & Ole Naesh" in "
J O U R N A L O F T H E R O Y A L S O C I E T Y O F M E D I C I N E V o l u m e 9 8 J a n u a r y 2 0 0 5"

Shows the application of the Fuzzy Logic in different areas.

Fuzzy Logic

Fuzzy logic was developed by Lotfi A. Zadeh in the 1960s in order to provide mathematical rules and functions which permitted natural language queries. Fuzzy logic provides a means of calculating intermediate values between absolute true and absolute false with resulting values ranging between 0.0 and 1.0. With fuzzy logic, it is possible to calculate the degree to which an item is a member. For example, if a person is .83 of tallness, they are " rather tall. " Fuzzy logic calculates the shades of gray between black/white and true/false. Fuzzy logic is a super set of conventional (or Boolean) logic and contains similarities and differences with Boolean logic. Fuzzy logic is similar to Boolean logic, in that Boolean logic results are returned by fuzzy logic operations when all fuzzy memberships are restricted to 0 and 1. Fuzzy logic differs from Boolean logic in that it is permissive of natural language queries and is more like human thinking; it is based on degrees of truth.
The word “fuzzy” is perhaps no longer fuzzy to many engineers today. Fuzzy systems and fuzzy control theories as an emerging technology targeting industrial applications have added a promising new dimension to the existing domain of conventional control systems engineering. It is now a common belief that when a complex physical system does not provide a set of differential or difference equations as a precise or reasonably accurate mathematical model, particularly when the system description requires certain human experience in linguistic terms, fuzzy systems and fuzzy control theories have some salient features and distinguishing merits over many other approaches. Fuzzy control methods and algorithms, including many specialized software and hardware available on the market today, may be classified as one type of intelligent control. This is because fuzzy systems modeling, analysis, and control incorporate a certain amount of human knowledge into its components (fuzzy sets, fuzzy logic, and fuzzy rule base). Using human expertise in system modeling and controller design is not only advantageous but often necessary.
(For more detail go to web site: http://www.dementia.org/~julied/logic/)

Precision is not truth.
Henri E. B. Matisse, 1869–1954
Impressionist painter

An Introduction to CFD

Computational Fluid Dynamics (CFD) is a computational technology that enables us to field of the dynamics for things that flow. Using CFD, we can build a computational model that represents a system or device that we want to study. For years, CFD analysis has been reserved for specialists. With today’s drive to get higher performing products to market faster, this restriction is no longer acceptable and lot of new software exists that puts CFD into the designers’ familiar CAD environment and automates the CFD modeling process. With this the designers get too quickly and easily simulate their designs, perform design variation and even optimize their product designs. In the analysis we apply the fluid flow physics and chemistry to the virtual prototype, and the software will output a prediction of the fluid dynamics and related physical phenomena. Using this we can build a virtual prototype of the system or device that we wish to analyze and then apply real-world physics and chemistry to the model, and the software will provide you with images and data, which predict the performance of that design. Some of the examples are simulation for fast blade design, Navier Stokes simulation for loss analysis and profile improvement for all turbine components, Navier-Stokes stage simulation for performance prediction of complete machines, including the interaction of rotating and stationary components, transonic airfoil and rotro-airframe interaction etc.

In the past few decades, the Finite Element Method (FEM) has been developed into a key indispensable technology in the modelling and simulation of various engineering systems. In the development of an advanced engineering system, engineers have to go through a very rigorous process of modelling, simulation, visualization, analysis, designing, prototyping, testing, and finally, fabrication/construction. As such, techniques related to modelling and simulation in a rapid and effective way play an increasingly important role in building advanced engineering systems, and therefore the application of the FEM has multiplied rapidly.

G. R. Liu
S. S. Quek

(As Written in their Book:
The Finite Element Method: A Practical Course)

A Great book to understand the basics of Finite Element Method

“Software is not natural. It does not age, rust, decay, break, melt, evaporate, vibrate, or float. The laws of nature do not apply to software.”

All traditional logic habitually assumes that precise symbols are being employed. It is therefore not applicable to this terrestrial life but only to an imagined celestial existence.
Bertrand Russell, 1923
British philosopher and Nobel Laureate

In the years to come, CAD will steadily improve engineering productivity by speeding the design process, suggesting options along the way, and identifying problems earlier. The software will “think” for designers and anticipate what they are creating. Finite element analysis (FEA) and Computational Fluid Dynamics (CFD) are widely used engineering analysis techniques in the world today. Engineers employ FEA & CFD to simulate how a physical system (usually an engineered product or manufacturing process) will respond to expected loading conditions. Practical applications of FEA & CFD include structural analysis of bridges and buildings, impact or crash analysis of automobiles, aerodynamic analysis of airplanes and airfoils, electromagnetic analysis of AC and DC motors, injection molding simulation of plastic parts, fluid flow analysis in channels and pipes and heat transfer through residential and commercial buildings.