Academic and pedagogical options in CIM laboratory CIM in universities.

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Presentation transcript:

Academic and pedagogical options in CIM laboratory CIM in universities

 Software Engineers  Mechanical Engineers  Electronics engineers  Industrial Engineering Integration between different concepts and technologies

Software  3D Graphic Display (real time and over the web) 3D Graphic Display (real time and over the web)  Real time software Real time software  ERP software.. ERP software..  Simulation Software Simulation Software  Web access and control Web access and control  Data mining Data mining  Artificial Intelligence: Artificial Intelligence:  Statistical analysis  HMI: Human-Machine Interfaces  Introduction To Probability  Data bases and Information Systems (עיצוב וניהול בסיסי נתונים )  Image Processing and Image analysis

3D Graphic Display  Rendering a 3D world: Object, camera, Point of view.  Computational geometric (גאומטריה חישובית): Translation, Rotation and scaling (Matrix)  Computational Complexity (סיבוכיות חישובית ) and optimization.(Millions of calculation to display single frame)  Modeling, presentation and simulation Back to software

Real-time software  PLC Programs  Robot control and programming  Integration of different devices: Magnetic sensor on the conveyer detected pallet and initiate robotic program  Integration of complicated system() Back to software

ERP software  Basic concepts; MRP, CRM, ERP, SCM etc.  Use and understand the included MRP software.  Integrate with other ERP (SAP, Oracle etc)  Write specific module (CRM, MRP..) : From scratch, based on ours open sources or other Back to software

Simulation software  Logic Simulation and Graphic Simulation  Modeling, presentation and simulation :Simulation of shape, operation and integration of different objects.  Open source for Dispatching and Scheduling algorithmic Back to software

Web access and control  Web based data entry (thin client architecture)  Real time 3D display over the internet (Browser based client server architecture)  Monitoring over the web  Operation and control over the web Back to software

Data mining  Tracking, logging, and storing data  Data warehouse: multiple data sources.  Data integrity and validity.

Artificial Intelligence:  Decision system, and Decision support systems  Scheduling and dynamic scheduling  Dynamic and adaptive control  Machine vision Back to software