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School of Chemical and Environmental Engineering

Now offering two distinct diplomas: Chemical Engineering and Environmental Engineering

Project Management

1. COURSE INFORMATION:

School Environmental Engineering
Course Level Undergraduate
Course ID ENVE 4358 Semester 7th
Course Category Required
Course Modules Instruction Hours per Week ECTS

Lectures and Laboratory assignments

4
T=3, E=0, L=1

5
Course Type General background
Prerequisites  
Instruction/Exam Language Greek
The course is offered to Erasmus students No
Course URL https//www.eclass.tuc.gr/courses/MHPER268/  (in Greek)

 

2. LEARNING OUTCOMES

Learning Outcomes

The course aims at rendering students familiar to the project management and programming by using modern methods and techniques.

At the completion of the course we expect that students will have acquired theory and will be comfortable with algorithms and mathematical models as well as generic and specialized software so that to make thoughtful and sound decisions and they can efficiently manage a large spectrum of problems related with project management. They will be capable to document, to quantify, and to evaluate alternatives for decision analysis, and also to undertake project and investment appraisal as well as to optimize business operations.  

General Competencies/Skills
  • Decision making
  • Work autonomously
  • Work in an international frame
  • Capacity to criticize and self-knowledge
  • Advance free, creative  and causative thinking

3. COURSE SYLLABUS

  • Introduction : project characteristics, responsibilities of project managers, activities and life cycle of projects, conditions of success 
  • Project economics – quantitative techniques  for decision making
  • Maths of financial transactions – Time value of money
  • Financial maths – annuities – loans
  • Project appraisal : investment appraisal, sensitivity analysis, break even, expected value, utility theory
  • Life-cycle costing : Cost items and analysis, uncertainty, life-cycle cost model
  • Evaluation and project selection : cost-benefit and cost-effectiveness analysis, decision making under uncertainty – decision trees
  • Probabilities and risk. Subjective probability distributions. Expected value criterion. Bayes theorem and information value
  • Activity based approach : management, objective, time, cost, quality, human resources, risk, inputs, innovation
  • Organizational model, work breakdown structure
  • Mathematical programming for project management: metwork and transport problems.
  • Project scheduling : GANTT graph, Critical Path Method, Crashing
  • Program Evaluation and Review Technique (PERT) – simulation
  • Software hands-on: examples: new product development, construction projects, R&D
  • Resources management : classification, smoothing and resource allocation, priority rules, critical chain
  • Budgeting and project monitoring: Design, management techniques, cash flow, cost monitoring and time scheduling

4. INSTRUCTION and LEARNING METHODS - ASSESSMENT

Lecture Method Direct (face to face)
Use of Information and Communication Technology Power point presentations; E-class support
Instruction Organisation Activity Workload per Semester
(hours)
- Lectures 36
- Tutorials 30
- Lab assignments 24
- Autonomous study 35
Course Total 125

Assessment Method

Ι. Written final examination (70%).
- Questions of theoretical knowledge.
- Theoretical problems to be resolved.

ΙΙ. Laboratory exercises – mid-term examination (30%).

III. Group and autonomous assignments (%).

5. RECOMMENDED READING

- Recommended Book Resources:

- Recommended Article/Paper Resources:

  • T. Klastorin, Project Management: Tools and Trade offs, Pearson Learning Solutions, 2nd Edition, 2011.
  • Rory Burke, FUNDAMENTALS of PROJECT MANAGEMENT - Tools and Techniques, Burke Publishing 2014
  • Schoemaker, P. J.H., “The Expected Utility Model: Its Variants, Purposes, Evidence, and Limitations,” Journal of Economic Literature, June, 1982, 20(2), 529-563.

6. INSTRUCTORS

Course Instructor: Associate Professor S. Rozakis (Faculty- EnvEng)
Lectures: Associate Professor S. Rozakis (Faculty- EnvEng)
Tutorial exercises:  
Laboratory Exercises: Associate Professor S. Rozakis (Faculty- EnvEng)