Advanced Farm Power and Machinery

Course Information
TitleΑΝΑΛΥΣΗ ΓΕΩΡΓΙΚΩΝ ΜΗΧΑΝΩΝ ΚΑΙ ΜΗΧΑΝΗΜΑΤΩΝ / Advanced Farm Power and Machinery
CodeΜΥΝ703
FacultyAgriculture, Forestry and Natural Environment
SchoolAgriculture
Cycle / Level2nd / Postgraduate
Teaching PeriodSpring
CommonYes
StatusActive
Course ID420000877
Class Information
Academic Year2016 – 2017
Class PeriodWinter
Faculty Instructors
Weekly Hours4
Class ID
600053372
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Examination)
Learning Outcomes
Upon successful completion of this ourse students will: 1. know the basic principles of fault detection in rural machinery 2. be able to design fault warning systems based on sensors 3. be able to develop fault detection software based on AI
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Work in teams
  • Work in an international context
  • Work in an interdisciplinary team
  • Generate new research ideas
  • Design and manage projects
  • Respect natural environment
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Analytical study of structural and functional elements of machinery, tractors and basic agricultural machinery.
Keywords
vibrations, fault detection, prediction, neural networks
Educational Material Types
  • Notes
  • Slide presentations
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Description
Powerpoint, lab exercises
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures60✓
Tutorial30✓
Project120✓
Written assigments90
Total300
Student Assessment
Description
80% Written exams 20% Written assignment
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Formative, Summative)
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Assignment (Formative, Summative)
  • Written Exam with Problem Solving (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
Σημειώσεις μαθήματος "Ανάλυση Γεωργικών Μηχανημάτων"
Last Update
14-11-2015