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Advance in Mechatronics
Muzammil Nakadey, Shaikh Moinuddin, Merchant Bilal 1
Mechanical Department, 2nd
Abstract— Mechatronics does not have a
definite definition; However, Mechatronics could
roughly be defined as an interdisciplinary
engineering with a synergistic combination of
mechanical engineering. The portmanteau
"Mechatronics" was first coined by Mr. Tetsuro
Mori, a senior engineer of the Japanese company
Yaskawa, in 1969.The major advantages of
Mechatronics Systems are that they are simpler,
economical, reliable and versatile systems when
integrated than being operated as individual
systems. Due to these major advantages, its field
of application is very vast like Automotives,
Defence, Medical, Smart consumer products,
Manufacturing, etc. Cars, CD players, washing
machines, railways are all examples of
mechatronic systems. The main characteristic
(and driving force) of recent advances is the
progressively tighter coupling of mechanic and
electronic components with software.
In this paper we survey current developments
and discuss future trends in mechatronics, the
future of mechatronics will specifically see a
move towards a high degree
of adaptability and self-organization.
Keywords— Mechatronics, Actuators,
Automation, Miniaturization, Modularization,
Mechatronics is “the application of
microelectronics in mechanical engineering” (the
original definition suggested by MITI of Japan).
Previously, mechatronics just meant
complementing mechanical parts with some
electrical units, a typical representant being a photo
camera. Today, mechatronics is an area combining
a large number of advanced techniques from
engineering, in particular sensor and actuator
technology, with computer science methods. Figure
1 depicts the three areas of mechatronics and their
Typical examples of mechatronic systems are
automotive applications, e.g. advanced braking
systems, fly/steer-by wire or active suspension, but
also DVD-players or washing machines.
Mechatronic systems are characterized by a
combination of basic mechanical devices with a
processing unit monitoring and controlling it via a
number of actuators and sensors. The introduction
of mechatronics is a tight integration of mechanical,
electrical and information-driven units.
Fig. 1 Areas of Mechatronics
II. CHANGES IN THE NATURE OF TECHNOLOGICAL PROCESSORS
In the era prior to the invention of the
electromagnetic induction dynamo (1830-40) by
Michael Faraday, all “machines” (technological
processes and products) were mechanical (M) in
nature, i.e., composed essentially of mechanical
units. Since mechanical units exhibit large inertia,
machines of this era tended to be large,
cumbersome, slow, “uni-functional” and “non-user
friendly (difficult to control and maintain)”.
However, it sufficed for the innovators of such
machines to be well versed in mechanical sciences
By the late 19th century, since electrical (E1)
energy can be transmitted and transformed much
more easily than mechanical energy, the energy
receiving and manipulating units within machines
(technological processes and products) started to be
replaced by functionally comparable electric units. As
a result, machines became more compact, controllable
A technological transformation occurred with the
advent of analog electronic (E2) valves in the
earlier half of the last century. This transformation
accelerated after the 1950s owing to the
development of transistors, digital electronics and
power electronics (E3). Wherever possible,
electrical functional units were replaced by such
electronic units so as to attain several orders
superior performance in terms of size,
controllability and user-friendliness. The synergistic
combination of E1, E2, and E3 technologies may be
collectively referred to as E technologies
The second half of the last century saw dramatic
changes in technological processes and products
owing to the rapid extension of earlier successes in
electronic technologies towards the development of
a bewildering array of digital computational units
(computers): general purpose integrated chips (IC),
application specific ICs (ASIC), microprocessors
(µp), etc. These functional units are now so small in
size (miniaturized) that they can be embedded
within the functional units.
III. STATE OF ART
Modeling & Tools: In a certain sense, modeling
and even model driven development, i.e. the
generation of executable code from a model, has
long been existing in the mechatronic world to
improve software quality based on model analysis.
Code Generation: Based on such a specification,
model based development ideally requires the
generation of code which meets all real time
constraints. This requires the code generator to
know about all platform specific constraints like
speed and number of processors or available
memory. Only a very few research oriented
approaches exist to support a uniform modeling of
the behavior of all system components including the
specification of real time constraints and a
corresponding code generation.
Processes: The above description focused on
modeling the software part of mechatronic systems.
One of the most prominent problems in current
industrial development and even research
approaches is however the lack of integration
between the different disciplines, namely
mechanical and electrical engineering and computer
science or software engineering more specifically.
Usually, the mechanical engineer starts with
designing the shape and mechanical parts, then the
electrical engineer plans the wiring and finally the
software engineer has to write the code. This
approach leads to a lot of design errors and costly
rework when it is finally noticed that some parts do
not fit together or the simple layout of processors
and memory make certain software solutions
Analysis & Tools: A rather large percentage of
mechatronic systems are deployed in safety critical
areas (e.g. the automotive or rail domain). This
makes analysis of mechatronic systems (or first of
all, their models) one of the main areas of work for
software engineers employed in the design of such
systems. Since its invention in the late 80’s model
checking has become a standard technique for
verification, in particular for hardware systems.
The main advantage of model checking which
makes it interesting for mechatronic systems is its
(almost) full automation, providing tool support for
analysis. Notwithstanding recent advances and
success stories, the main challenge is still the so-
called state explosion problem: model checking
techniques (most often) rely on a search of the
whole state space, and this can grow to arbitrarily
large dimensions. For Example: SAT solvers are
combined with decision procedures (giving so-
called SMT-solvers), model checking with specific
AI search methods, bounded model checking is
parallelized or model checking combined with
static analysis methods.
Mechatronic systems present a further challenge
for verification as they belong to the area of hybrid
systems, characterized by a combination of discrete
and continuous parts. The software constitutes the
discrete part, while the continuous dynamics
corresponds to the physical system with its sensors
and actuators. Verification of hybrid systems today
is still in its infancy. System models in this class are
written as timed automata, and a number of tools
support verification of timed automata with respect
to reachability or even temporal logic specified
properties. Automation can still only partially be
achieved; the algorithms employed in the model
checking are not guaranteed to terminate anymore.
In order to make the actual system fit into the
required subclass, approximations of the real
system are used.
Fig. 2 Composition of Mechatronics system
IV.FUTURE DEVELOPMENTS AND CHALLENGES
We believe that future mechatronic systems will
consist of several autonomously acting agents
capable of monitoring their own physical
environment as well exchanging information with
other agents. Constructing the software of advanced
systems requires a number of significant changes of
current software engineering techniques. In
particular, the following issues have to be addressed
to build the next generation systems properly.
A. Current software design processes are
tailored towards a particular domain rather than
spanning over all involved domains.
B. Modeling formalisms allow for a description
of static systems but not for their volatility. Model
transformations are meant for transforming models
towards a particular use on a platform but not for
describing the change in that model.
C. Analysis techniques mainly rely on the
knowledge about a global state space and cannot
cope with properties only emerging due to the
volatility of systems.
D. Secure exchange of information is usually
based on a central unit and cannot manage
decentralized highly distributed systems of agents
dynamically building as well as resolving clusters.
The integration of mechanical, electrical and
software parts poses challenges which so far have
only partly been addressed. For the analysis of
today’s mechatronic systems we can identify the
Precise hybrid modeling: No hybrid
modeling techniques exist today which are
able to describe the diverse parts of a
mechatronic system in a uniform and precise
way. Current formalisms try to simply
combine some of the existing modeling
language from the three areas but most often
without giving a meaning to the mixed use of
Integrated hybrid analysis: The three
disciplines involved in the construction of
mechatronic systems all have analysis
techniques on their own. Instead of applying
these in isolation, an integrated analysis
framework is needed in which a particular
type of analysis in one area supports & relies
on analysis in another area.
Fig. 3 Example of Miniaturization
Verification Systems with discrete and
continuous parts are intrinsically difficult to verify.
Model checking of hybrid systems and the transfer
of known verification techniques to the domain of
hybrid systems remains a challenge.
Volatility Evolution according to new data from
the environment will be one main characteristic of
future advanced mechatronic systems. The behavior
of such systems will thus not be completely fixed
during design, but is allowed to adapt to
environmental changes. The permitted degree of
change might partially be laid down by model
transformations being part of the model itself.
Verification thus has to show that the system
remains safe under all possible influences from the
V. FUTURE TRENDS IN MECHATRONICS ENGINEERING
By definition, automation is the replacement of
human labour. And technology is (just) a bag of
tools that come in the form of hardware and/or
software. A tool is something that assists in
performing existing tasks better or enables new
tasks to be performed. In other words, it somehow
replaces human labour, i.e., automates the task.
Thus progress in technology (through mechatronics,
or otherwise) is synonymous to automation. Human
activity can be broadly divided into two categories:
individual or collective (social). Individual
activities may be purely mental or combined with
physical activity. Irrespective of whether it is
reflexive or reflective, any human physical act
requires effort at five levels:
i. Setting the goal (a purely mental activity).
ii. Sensing the environment through the five
sensory organs: eyes, ears, skin, tongue, and nose.
iii. Communicating the sensory signals to the
central neural processor called the brain.
iv. Fusing the signals to recognize patterns of
interest and output the command signals to human
v. Performing the physical task using limbs
A remarkable human ability is to learn from the
results obtained from past acts so as to perform
better when executing similar tasks in the future.
This learning ability provides human beings with
the ability to act as autonomous units. A further
ability lies in communicating with other human
beings so as to undertake collective tasks.
The above description of human abilities provides a
basis for understanding trends in mechatronics.
A. Sensing and sensor fusion (task ii) will be
the next capability to be acquired by mechatronic
systems. Already, many mechatronic units possess
rudimentary sensing abilities. For instance, modern
air conditioning units are able to sense air
temperature and humidity through separate sensors
and fuse the signals through fuzzy logic reasoning.
Likewise, sensors in the form of transducers have
long been used to enable feedback control in
machines. However, there is still a long way to go.
Sensors produce copious amounts of data that need
to be digested to discover patterns of interest before
control can be effected through the “actuators”.
Advances in high-speed microcomputers and signal
processing algorithms have now opened the door
for the exploitation of sensors exploiting a wide
range of physical, chemical and, even, biological
phenomena. While actuators are limited in variety,
the variety of possible sensors is almost unlimited.
For instance cutting forces in CNC machining
(Figure 4) and its consequences (e.g., tool fracture)
can today be monitored and controlled using
commercially available devices capable of sensing
machining noise, machine vibrations, acoustic
emission, drive motor current, etc. Future
mechatronic engineers will have to possess deeper
understanding of natural sciences so as to cope with
the growing variety of sensors.
Fig. 4 CNC Machine
B. Machine learning: Intelligence means
adapting to the environment and improving
performance over time. Within the domain of
mechatronic engineering, “there has been
considerable interest in learning through the use of
ANN and fuzzy logic for applications in control and
robotics, autonomous guided vehicles (AGV), etc.,
that require mainly reflective intelligence when
performed by human operators and tasks, such as
machine diagnostics, requiring combinations of
reflexive intelligence and low level reflective
intelligence.” This interest will continue well into
Fig. 5 Example of sensing and sensor fusion: Robots
C. Autonomization refers to the development
of the ability to survive and perform robustly while
the external environment changes. With progress in
sensor and learning technologies, tomorrow’s
mechatronic devices can be expected to become
progressively more autonomous. They will be able
to reset their local goals autonomously under
changing external environments so as to meet the
broad system-level goals set by human beings.
D. Modularization will be a consequence of
autonomization. Mechatronic sub-units will come
in modular form, i.e., with all the abilities required
for local goal setting, control, and learning
encapsulated within the sub-unit. Thus, in time,
every mechatronic sub-unit will be self-contained
E. Miniaturization refers to the trend towards
mechatronic units of significantly smaller size
(Figure 3). Progress in precision engineering, newer
materials (composites, diamond coatings, etc.), and
nano-technologies will contribute to this
F. Links to the Internet: The Internet will
become ubiquitous within the mechatronic world.
Every autonomous mechatronic unit will be
connected via broadband and satellite networks to
the rest of the world. Each mechatronic device will
be able to access the information and knowledge
base available on the Internet so as to optimize its
own performance. At the same time, it will be able
to communicate its operational status to remote
G. Societies of devices: The metaphor of
society is very similar to that used by Minsky in his
book “The Society of Mind”. He says: “[M]ind is
made up of many smaller processes. These we’ll
call agents. Each mental agent by itself can only do
simple things that need no mind or thought at all.
Yet when we join these agents and societies in
certain special ways this leads to true intelligence.”
Once a mechatronic device has become
autonomous, locally intelligent, and able to
communicate extensively via the Internet, it can
join “societies” of devices with a common purpose
In this article, we have sketched current, future
trends and advancement in the development of
mechatronic systems. In particular, we have
discussed the challenges involved in the
construction of future advanced systems.
Summarizing, these can be roughly divided into
two categories: the challenges arising from the
collaboration of several different disciplines (which
is already an issue today), and those due to the
aspect of self-coordination which seems to be a
main characteristic distinguishing current from
future mechatronic systems. These are challenges to
all involved disciplines, but in particular to software
engineering. Key to a success in mastering them is
the joint effort and collaboration of disciplines,
within computer science and engineering.
Healthy thanks to Prof. Aamir Siwani and Prof. Rashid for
their proper guidance and co-operation.
 Nitaigour Premchand Mahalik, Mechatronics, McGraw-
Hill International Edition, 2012
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