Automation in Manufacturing

102605
Back to Automation in Manufacturing

Module 6: Introduction to Modeling and Simulation

  1. Q1(g). Can we simulate transportation, manufacturing and health system?20222m

    Module 6: Introduction to Modeling and Simulation

    Can we simulate transportation, manufacturing and health system?

    View this question on its own page →
    Worked Solution

    Answer

    Yes. Transportation, manufacturing and health-care systems can be simulated using mathematical/computer models. Simulation helps study system behaviour, test alternatives and predict performance without experimenting directly on the real system.

  2. Q1(i). Which technique is used for solution of nonlinear programming?20222m

    Module 6: Introduction to Modeling and Simulation

    Which technique is used for solution of nonlinear programming?

    View this question on its own page →
    Worked Solution

    Answer

    Nonlinear programming can be solved using iterative numerical optimization techniques, such as the gradient (steepest-descent) method, Newton's method, or sequential quadratic programming (SQP). The appropriate method depends on the objective function and constraints.

  3. Q8(a). Explain system modelling. Write differences between continuous and discrete event.202214m

    Module 6: Introduction to Modeling and Simulation

    Explain system modelling. Write differences between continuous and discrete event.

    View this question on its own page →
    Worked Solution

    Answer

    System modelling

    System modelling is the process of developing a mathematical, logical or computer representation of a real system so that its structure, behaviour and interactions can be studied. A model contains the important entities, variables, relationships, inputs and outputs of the actual system.

    Continuous vs. discrete-event systems

    Continuous system Discrete-event system
    State variables change continuously with time. State changes occur at specific points/events.
    Usually represented using differential/algebraic equations. Usually represented using event logic, state transitions and queues.
    Time advances continuously. System state changes when an event occurs.
    Example: temperature variation, fluid level, motor speed. Example: arrival/departure of jobs, machine failure/repair, production-line queues.

    In short: Continuous simulation tracks continuously varying quantities, whereas discrete-event simulation tracks changes caused by individual events.