Learning Outcomes
By the end of the module student should be able to: (i) develop dynamic tools for systems thinking including methods to elicit and map the structure of complex systems; (ii) to develop tools for modeling and dynamic simulation of complex systems; (iii) apply procedures for testing and improving the simulation models; (iv) design and evaluate policies for improving the dynamic behavior of systems.
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
Course Content (Syllabus)
Introduction: fundamental system concepts; the object of a system dynamics analysis.
System Structure and Dynamic Behavior: open and closed systems; positive-negative feedback loop; S-curve dynamics; oscillation, overshoot and collapse; other modes of behavior.
Causal-Loop Diagrams: construction principles; loop identification.
Stocks and Flows: diagramming notation; mathematical formulation; stocks and flows diagrams; graphical integration.
Mathematical Formulation of Positive Feedback Loop: analytical solution for the linear first-order system; doubling times; non linear systems.
Mathematical Formulation of Negative Feedback Loop: analytical solution for the linear first-order system; time constants and half-times; zero-value goal structure; initial conditions; system compensation.
Mathematical Formulation of S-shaped Growth: Verhulst growth; Richards’ model; Weibull model.
Modeling Decision Making: principles for modeling decision making; formulating rate equations.
Delays: material delays; information delays; estimating the duration and distribution of delays.
Introduction to PowerSim Software Package: flow diagram modeling; defining the time; computational sequence; overview of operators; function definitions.
Case Studies in Industrial Management Using the System Dynamics Approach (PowerSim models).
