System Definition and Components
System
A system is an organized set of interrelated components that work together to achieve a common objective by accepting inputs, processing them, and producing outputs.
Key idea: Every system has a purpose, structure, and behavior over time.
Real-Life Example: University System
- Input: Students, faculty, syllabus, infrastructure
- Process: Teaching, exams, evaluation
- Output: Graduates, results, degrees
System Diagram
Components of a System
A system is made up of several basic components.
Main Components
- Input – Resources entering the system
- Process – Transformation of inputs
- Output – Final result
- Feedback – Performance information
- Control – Corrective actions
- Boundary – Limits of the system
- Environment – External factors affecting the system
System Components with Examples
| Component | Meaning | Real-Life Example (ATM System) |
|---|---|---|
| Input | Data/resources entering system | ATM card, PIN, amount |
| Process | Conversion activity | Verification, transaction |
| Output | Final result | Cash, receipt |
| Feedback | Performance information | Balance update |
| Control | Ensures correctness | PIN validation rules |
| Boundary | System limits | ATM machine casing |
| Environment | External influence | Bank server, power supply |
Stochastic Activities
Stochastic activities are activities whose outcomes are uncertain and depend on probability or randomness.
These systems cannot be predicted with 100% accuracy.
Characteristics
- Involves randomness
- Uses probability
- Results vary each time
Real-Life Examples
- Traffic flow at a signal – Arrival of vehicles is random
- Stock market prices – Prices fluctuate unpredictably
- Customer arrival in a bank – Depends on chance
Picture Representation
Deterministic vs Stochastic
| Basis | Deterministic | Stochastic |
| Outcome | Fixed | Random |
| Prediction | Exact | Probabilistic |
| Example | Payroll system | Weather forecast |
Continuous Systems
A continuous system is one in which state variables change continuously over time.
Characteristics
- No sudden jumps
- Time is continuous
- Usually described by differential equations
Real-Life Examples
- Temperature change in a room
- Water level in a tank
- Speed of a moving car
Picture Representation
Discrete Systems
A discrete system is one in which state variables change at specific points in time.
Characteristics
- Changes occur in steps
- Time intervals are fixed
- Events driven
Real-Life Examples
- Attendance system (marked once per day)
- Bank transaction system
- Digital clock
Picture Representation
Continuous vs Discrete Systems
| Basis | Continuous System | Discrete System |
| Time | Continuous | Fixed intervals |
| Change | Smooth | Step-wise |
| Example | Temperature | ATM transactions |
| Representation | Differential equations | Difference equations |
System Modeling
System modeling is the process of representing a real-world system using diagrams, mathematical equations, or simulation models to study its behavior.
Purpose of System Modeling
- Understand system behavior
- Predict future performance
- Improve efficiency
- Support decision making
Types of System Models
1. Physical Models
- Tangible representation
- Example: Building blueprint
2. Mathematical Models
- Uses equations
- Example: Profit = Revenue – Cost
3. Simulation Models
- Imitates real-world operation
- Example: Traffic simulation software
Steps in System Modeling (Exam-Oriented)
- Define the problem
- Identify system boundaries
- Identify variables
- Build model
- Validate model
- Analyze results
Picture Representation
Real-Life Example of System Modeling
Hospital Management System
- Input: Patients, doctors, equipment
- Process: Diagnosis, treatment
- Output: Recovered patients
- Model Use: Reduce waiting time using simulation
Short Notes (For Quick Revision)
- A system is a set of interacting components
- Stochastic systems involve randomness
- Continuous systems change smoothly
- Discrete systems change at fixed times
- System modeling helps in decision making
Types of Models
A model is a simplified representation of a real-world system used to understand, analyze, and predict system behavior.
Classification of Models
Models are broadly classified into:
- Physical Models
- Mathematical Models
- Simulation Models
- Corporate (Enterprise-wide) Models
Physical Models
A physical model is a tangible, real, or scaled-down representation of a system.
Characteristics
- Can be seen and touched
- Easy to understand
- Costly to modify
Static Physical Model
A static physical model represents a system at a particular point in time. It does not show changes over time.
Features
- No time element
- Shows structure only
Real-Life Examples
- Organization chart
- Building blueprint
- Map of a city
Diagram
Dynamic Physical Model
A dynamic physical model shows how a system behaves or changes over time.
Features
- Time-dependent
- Demonstrates movement or flow
Real-Life Examples
- Working model of a car engine
- Water flow model in a dam
- Conveyor belt system in a factory
Diagram
Mathematical Models
A mathematical model represents a system using mathematical equations, formulas, and variables.
Characteristics
- Abstract in nature
- Easy to modify
- Highly accurate for analysis
Static Mathematical Model
A static mathematical model represents a system using equations that do not involve time.
Examples
- Profit = Revenue – Cost
- Simple interest formula
Example Explanation
Profit of a company calculated for one financial year is static because it does not depend on time intervals.
Dynamic Mathematical Model
A dynamic mathematical model includes time as a variable and shows system behavior over a period.
Examples
- Population growth model
- Inventory control model
- Sales forecasting over months
Simple Representation
Comparison: Static vs Dynamic Models
| Basis | Static Model | Dynamic Model |
|---|---|---|
| Time | No time factor | Time dependent |
| Change | No change | Continuous change |
| Usage | Snapshot analysis | Trend analysis |
| Example | Balance sheet | Cash flow forecast |
Full Corporate Model
A full corporate model is a comprehensive model that represents the entire organization as a single integrated system.
Purpose
- Strategic planning
- Policy evaluation
- Long-term decision making
Components Covered
- Finance
- Marketing
- Operations
- Human Resources
- Information Systems
Real-Life Example
ERP (Enterprise Resource Planning) systems like SAP
Diagram Representation
Types of System Study
System study is the detailed examination of an existing system to understand its structure, functioning, and problems.
Types of System Study
System Survey
- Preliminary investigation
- Identifies problem areas
- Determines feasibility
Example: Studying current attendance system before automation
System Analysis
- Detailed study of system requirements
- Data flow analysis
- Identifies user needs
Tools Used: DFD, Flowcharts
System Design
- Converts requirements into solution
- Logical and physical design
Example: Designing database and user interface
System Development
- Coding and implementation
- Hardware and software setup
System Testing
- Checks correctness and reliability
- Unit testing, system testing
System Implementation
- System installation
- User training
- Data migration
System Maintenance
- Error correction
- Performance improvement
System Study Life Cycle (Exam Diagram)
Key Differences: System Study vs System Modeling
| Basis | System Study | System Modeling |
| Focus | Understanding system | Representing system |
| Tools | Interviews, DFD | Models, equations |
| Output | Requirements | Predictive analysis |
MCA Exam Tips
- Write definitions clearly
- Use tables for comparisons
- Draw simple diagrams
- Give at least one real-life example