Related to Mechanical System Design.

1. JAHANGIRABAD INSTIUTE OF TECHNOLOGY
BARABANKI
Department of Mechanical Engineering
Decision Analysis
RAVI VISHWAKARMA
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 1

2. Decision Making
After having selected various alternatives for solution of a design
,designer faces the task of taking decision for suitable feasible
alternatives. The designer has to make assessment of the available
solutions in stages and then the promising ones should be examined in
detail.
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 2

3. Importance of Decision Making
To select the optimum solution
Stress on better performance due to increased
competition.
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 3

4. Elements of Decision Making
Strategies /alternatives available to the decision
marker
State of nature/events
Payoffs or outcomes
Objective
State of knowledge
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 4

5. Decision Making Under Multiple Criteria
Types of decision can be classified on the basis of risk involved and are
explained as below:
a)Decision Problems Under Certainty :This type of decision arises
when all information's regarding alternatives are completely available
and there is no uncertainty.
b) Decision Problems Under Risk: This type of decision arises when
such a problem exists in which analyst decides to include state of
nature, the probability of which in his views are known.
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 5

6. 10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 6
c) Decision Problems Under Uncertainty :This type of decisions
arises when such a problem exists for which the decision maker decides
to includes future states, The probability of which can not be estimated.
d)Decision Under Conflict: The state of nature are replaced by
courses of action determined by an opponent who is trying to maximize
his objective function. This type of decision theory usually is called
game theory.

7. Expected Monetary Value
The Expected Monetary Value is how much money you can
expect to make from a certain decision. As the expected monetary
value is based on probability, there is no quick and easy formula.
Calculating the Expected Monetary Value becomes more
complicated when you have more complex situations. This is
where a tree diagram comes in handy.
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 7

8. Utility Concept
Anything, which is capable of satisfying a human want, is defined as
utility. For example ,when a person feels hunger, he will be satisfied by
taking a loaf of broad, so we can say that bread is said to possess
utilioty.it is subjective one.it can not be measured accurately.it varies
from person to person and place to place. It can be measured only in
terms of money.
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 8

9. Baye’s Theorem
It is a unique method of calculating conditional probabilities.
Let A1 and A2 the set of events which are mutually exclusive and
exhaustive.
B=A Sample event which interest each of the A1 and A2.
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 9

10. System Simulation
Simulation means an operation in which a real situation, etc. is
represented in another form. For example a computer simulation of the
nuclear reaction.
Simulation has become a standard tool in business. When a
mathematical technique fails, we use simulation to save us. In
manufacturing, simulation is used in following areas:
I.To determine production schedule
II.To determine inventory levels, maintenance procedures
III.To do capacity planning
IV.To do process planning
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 10

11. Simulation Models
A model is an idealization of a real world situation that helps in the
analysis of a problem. Simulation involves use of models to various
environmental conditions to observe how they behave and thus explore
the nature of the results that might be obtained from the real-world
system.
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 11

12. Computer Simulation
The use of computers to carry out extensive simulations involving
graphical output has become common place. In fact, many people are
referring to these as computer experiments ,and there is the prediction
that this filed will eventually grow into a third domain of science,
coequal with the traditional domains of theory and experimentations.
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 12

13. Simulation Process
Simulation is the actual running of the model system to gain insight
into its performance. Its used to understand the expected performance
of the real system and to test the effectiveness of the system design.
Simulation is thus a descriptive tool, allowing us to experiment with
model instead of the factory. Simulation experiment requires multiple
runs, producing time histories of model variables.
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 13

14. Input -Output Model
Input output model shows a relationship between inputs provided to a
system, their influence on the system ,their types, their effectiveness,
outputs, and effect on system’s performance.
Measurable Output variables
Performance evaluation variables
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 14
Manufacturing Process
Fixed Variables
Input Variables

15. Limitation of Simulation Approach
Limitations of simulation are:
I.Simulation does nor generate optimum to problems as do other
quantitative techniques. It is a trial and error approach that may
produce different solution in repeated runs.
II.Simulation model does not produce answers by itself. It is ‘run’
rather than solved.
III.In very large and complex problem the large number of variables
and the inter-relationship between them makes the problem very
unwieldy and hard to program.
IV.Each simulation model is unique and its solutions and inferences are
not usually transferable to other problems.
V.A good simulation model may be very expensive.
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 15

16. Inventory Control
Inventory control, also known as stock control, involves regulating and
maximizing your company’s inventory. The goal of inventory control is
to maximize profits with minimum inventory investment, without
impacting customer satisfaction levels. Inventory control is also about
knowing where all your stock is and ensuring everything is accounted
for at any given time.
10/06/17 Ravi Vishwakarma ,Assistant Professor JIT 16