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: Avraham Shtub, Jonathan F. Bard, Shlomo Globerson, Project Management: Processes, Methodologies, and Economics (2nd Edition) Pearson, Prentice Hall, 2005 - 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)