2.5 Modeling a System
Many things in the real world are complex and dynamic and hard to understand. In such
cases, we use a mechanism called modeling to simplify presentation of such things. It is then
easier to understand, to test their effects and different relationships.
A model can be described as an abstraction or approximation that is used to represent
reality. Good models enable us to explore and gain improved understanding of real-world
situations. This is not a new technique. Even ancient people had used diagrams as models to
present things.
Examples of models:
A written description of a battle
A physical mock-up of an ancient building
The use of symbols to represent money, numbers
Mathematical relationships
Today, scientists, engineers, managers and other professionals use different models to
understand complex problems and to present different solutions. In the context of
organizations, managers and decision makers use models to help them understand what is
happening in their organizations and make better decisions.
In general, models can be classified into various types as narrative, physical, schematic and mathematical.
Narrative Model:
A narrative model is based on words, spoken or written.
Both verbal and written descriptions of reality are considered narrative models.
In an organization, reports, documents and conversations concerning a system are all
important narratives
Computers can be used to develop narrative models.
Example: word processing
Physical Model:
A physical model is a tangible representation of reality.
Many physical models are computer designed or constructed.
Schematic Model:
A schematic model is a graphical representation of reality.
Graphs, charts, figures, diagrams, illustrations, and pictures are all types of schematic models.
Schematic models are used extensively in developing computer programs and systems.
Mathematical Model:
A mathematical model is an arithmetic representation of reality. Computers excel at solving
mathematical models.
Examples:
Retail chains have developed mathematical models to identify all the activities, effort, and
time associated with planning, building, and opening a new store so that they can forecast
how long it will take to complete a store.
A mathematical model developed to determine the total cost of a project.
TC = (V)(X) + FC where
TC = total cost
V = variable cost per unit
X = number of units produced
FC = fixed cost
When a model is developed, it is important to maintain its accuracy to use the model
effectively for problem solving. Otherwise the solutions obtained through the model may not
be valid. Models are usually based on assumptions and if they are not realistic assumptions, it
leads to inaccuracy. Therefore, the potential users should clearly understand these
assumptions.
2.4 System variables and Parameters
Some parts of a system are under direct management control, while others are not. This is
measured with respect to values in the system variable and parameters.
System variable - item controlled by decision-maker
Example: The price a company charges for its product is a system variable
because it can be controlled.
System parameter - value that cannot be controlled
Example: the cost of a raw material.
The number of pounds of a chemical that must be added to produce a
certain type of plastic is a quantity or value that is not controlled by
management; it is controlled by the laws of chemistry.
2.3 System performance and standards
Whether a system works properly, can be identified by evaluating its performance. System
performance can be measured in various ways. Two important indicators in the system
performance are efficiency and effectiveness.
Efficiency: measure of what is produced divided by consumed (output/input)
It may range from 0 to 100 percent
Example: The efficiency of a motor is the energy produced (in terms of work done)
divided by the energy consumed (in terms of electricity or fuel). Some motors have an
efficiency of 50 percent or less because of the energy lost to friction and heat
generation.
Efficiency is a relative term used to compare systems.
Example: a gasoline engine is more efficient than a steam engine because, for the
equivalent amount of energy input (gas or coal), the gasoline engine produces more
energy output.
Effectiveness: extent to which system attains its goals or objectives. It can be computed by
dividing the goals/objectives actually achieved by the total of the stated or expected
goals/objectives of the system.
Example: A company may have a objective to reduce damaged parts by 100 units. A
new control system may be installed to help achieve this objective. Actual reduction in
damaged parts, however, is only 85 units. The effectiveness of the control system is 85
percent (85/100 = 85%).
Effectiveness, like efficiency, is a relative term used to compare systems.
System performance standard: A specific objective of the system.
The system performance standard is defined considering both effectiveness and efficiency
of the system since the goal of a system is usually defined considering both these factors. The
status of the system (whether it is good or bad) is then described with respect to this
standard.
Example: A system performance standard for a particular marketing campaign might
be to have each sales representative sell $100,000 of a certain type of product each
year
A system performance standard for a certain manufacturing process might be to have no
more than 1 percent defective parts:
• Once standards are established, system performance is measured and compared
with the standard. Variances from the standard are determinants of system
performance.
2.2 System components and concepts
In abstract terms, a system consists of three main components and few communication links.
They are Input, Process and Output. Feedback is one communication link.
System boundary defines the scope of the system with respect to the environment it
operates. Simply, it defines the system by distinguishing it from everything else in the
environment.
Example 1: The Scope of a School System
We can identify goals, input, processing and output of a school system as follows:
System: School
Goal: Educate students
Input: Children, Teachers, Principal, Resources
Processing: Teaching and learning
Output: Educated students
A school (viewed as a system) illustrating the system boundary
Input: dirty car, water, cleaning ingredients, time, energy, skill,
knowledge
Processing mechanism: select the cleaning options: wash only/wash with wax/
wash with wax/ and hand dry
Feedback: your assessment of how clean the car is
Output: clean car
System types:
Considering various features, we can classify systems into different categories as follows:
• Simple or complex
• open or closed
• stable or dynamic
• adaptive or non-adaptive
• permanent or temporary
2 System and modeling concepts
2.1 What is a system?
A system is a collection of components which work together to achieve a specific goal.
These components are connected to maintain communication when they work together .
However, they have independent functionalities. Therefore, each component is another
system, named as a subsystem, which carries out tasks to achieve some objectives of the
original system.
Example 1: The Human Body
Our human body is a complex system which contains several components which acts as
subsystems. The human body consists of complex muscle, bone, respiratory, digestive and
circulatory subsystems, each providing a specific task of the overall system.
Let’s consider one such subsystem, respiratory which provides oxygen to human body. Some
components of the respiratory subsystem such as nasal passages, lungs etc. can be
considered as a subsystem. On other hand, respiratory system communicates with digestive
system as two independent components of human body.
Example 2: A School
A particular school can be considered as a component of education system in this country
(a university may be another one). At the same time, a school itself is a complete system that
includes a principal, teachers, equipment and classrooms which are its components.
Viewing complex systems as a collection of subsystems may help us handle complexity and
improve our understanding of the system.
