design optimization of mechatronics system
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Design optimization of mechatronics system Submitted By : Submitted to : Mohit Soni (1) Mohit Soni (2) Mukul Pandya Himanshu Singh Rathore Sir Nalin Bhatt Naman Garg Lecturer (ME Dept.) Neeraj Sharma Nikhil Varandnani SKIT, Jaipur Nikhil


  1. Design optimization of mechatronics system Submitted By : Submitted to : Mohit Soni (1) Mohit Soni (2) Mukul Pandya Himanshu Singh Rathore Sir Nalin Bhatt Naman Garg Lecturer (ME Dept.) Neeraj Sharma Nikhil Varandnani SKIT, Jaipur Nikhil Karagwal Nishant kumar

  2. Table of contents Content Presenter name Slide NO. Introduction and need Mukul Pandya 1-4 Design of mechatronic Naman garg 5-12 system Optimization methods Mohit soni 13-18

  3. Optimization • A process of making something (as design,system or decision) as fully perfect,functional ,effective as posible. Design optimization of mechatronic system Refer to make the Design of mechatronics system as effective as it is possible in order to achieve high performance and functionality. Points to be discussed :-  A framework for mechatronic system design .  The method used to optimize the classical design of mechatronic system will identified and discussed .

  4. Introduction Need of design optimization of mechatronic system  To achieve better performance and control.  To design a product or a system which not only fulfill its task satisfactorily but also to be more efficient ,versatile, unique and cost effective than other systems.

  5. OPTIMISING METHODS OF DESIGNING IN MECHATRONICS SYSTEM

  6. DIFFERENT PHASES IN DESIGNING 1. Modeling : Block diagram or visual interface for creating intuitively understandable behavioral models of physical or abstract phenomena. The ability to encapsulate complexity and maintain several levels of sub model complexity is useful. 2. Simulation : Numerical methods for solving models containing differential, discrete, hybrid, partial, and implicit nonlinear se well as linear equations. Must have a lock for real-time operation and be capable of executing faster than real time. 3. Prototyping : A plug-in card is used to replace part of the model with actual hardware by interfacing to it with actuators and sensors. This is called a hardware-in the-loop simulation or rapid prototyping and must be executed in real time..

  7. SEQUENTIAL METHODS ARE AS FOLLOWS …

  8. Oakland high school presenting a design in a exhibition

  9. The mechatronic design methodology is concerned not only with producing high quality products but with maintaining them as well, an area referred to as life cycle design. • Several important life cycle factors are described below. • Delivery: Time, cost, and medium • Reliability: Failure rate, materials, and tolerances. • Maintainability: Modular design. • Serviceability: On board diagnostics, prognostics, and modular design. • Upgradeability: Future compatibility with current designs. • Disposability: Recycling and disposal of hazardous materials

  10. MODEL BASED CONTROLLING SYSTEM Model-based monitoring using intelligent sensors is an important technology holding much promise for improving manufacturing productivity and quality. In model-based monitoring the model is used to represent the ideal behavior of the structure. It is driven with the same inputs used for the process.

  11. Mechatronic methodology of machine design Development of technology leads to a continuous increase in demands on properties of designed products: • more functions, • higher efficiency and reliability, • lower demands on energy, • minimal size and weight, • lower cost. The following demands, brought about by development of technology, are increasing productivity of developers and designers. Shortening of development and design time is mainly desirable.

  12. DESIGNING A MODEL

  13. Optimization methods

  14. Parametric Optimization By a parametric optimization of a electromechanical system, we mean the process of finding those parameters of a mathematical description of a system from a set p of a admissible parameters at which a suitably selected objective function ψ (p)of those parameters reaches its extremities.

  15. Hill climb algorithm This is the simplest optimizing method being a variant of gradient method where the direction of the steepest hill is determined by searching its neighbourhood. Here the starting solution is generated at random. For the currently designed system a certain neighbourhood is generated using a finite set of transformation and the best minimum is chose from its neighbour.

  16. Tabu search algorithm At the ends of 1980’s professor fred grover designed a new approach to find the global minima, which he called tabu search. At present this method is among those used most frequently to solve combinatorial problems and finding the global minima.

  17. Optimal decoupling for improved MIMO control design

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