This document provides a summary of a company's production planning processes. It discusses that the company manufactures two types of ventilators and saw increased demand last year. To improve efficiency, it implemented forecasting, linear programming, and material requirements planning (MRP). Forecasting used linear regression on historical sales and store data to predict next year's monthly demand. Linear programming was used to determine the optimal production mix to maximize profits given time and budget constraints. MRP was applied to schedule ordering of components to ensure sufficient materials and avoid excess inventory or missing parts based on the production plans.
B.COM Unit – 4 ( CORPORATE SOCIAL RESPONSIBILITY ( CSR ).pptx
Production Planning Methods: Forecasting, Linear Programming & MRP
1. A production example
Ramon Savinon
Sophie Leroux 1939653
Stephanie Soares
9764925
2. Introduction
The base of the model is a fictional
company located in the Dominican
Republic
Its headquarters is located in Santo
Domingo, and it supplies appliances
stores in 3 main cities
3. Lead factors:
High cost of electricity
Humidity factor is very high
4. The company manufactures two types
of ventilators: floor and ceiling
The demand for this product raised in
the past year, in order to be more
efficient, they implemented production
control methods such as:
Forecasting
Linear Programming
MRP
5. Forecasting
The forescating method used was a
type of regression called linear
regression. It tries to evaluate the
correlation beetween two variables.
10. Equations for each product
regression equation for product one
b= 14.68762
equation
1= 212.109+14.68s
a= 212.109
regression variables for product two
b= 13.44119
equation
2= 158.7976+13.44s
a= 158.7976
11. Forecast for the next year
expected stores to service in the next year per month
product one forecast product two forecast
27 517.469 26 508.23
25 488.109 26 508.23
30 561.509 28 535.11
26 502.789 28 535.11
26 502.789 25 494.79
25 488.109 29 548.55
28 532.149 30 561.99
30 561.509 30 561.99
28 532.149 30 561.99
28 532.149 29 548.55
26 502.789 27 521.67
29 546.829 25 494.79
30 561.509 28 535.11
12. Linear Programming
Linear Programming is a specific class
of mathematical problems.
It was first used during the First World
War to solve complex problems in
warfare.
Later on, it was developed by George
B. Dantzig, who is regarded as the
father of LP.
15. To solve this problem, LINDO was
used.
LINDO is a software that is frequently
used to solve linear and non linear
problems.
16. Linear Programming
Optimal Production
1800
1600
1400
Objective Function
1200
1000
Optimal solution
Constraints
800
600
400
200
0
0 200 400 600 800 1000 1200 1400 1600
17. Linear Programming
Optimal solution:
◦ Floor ventilator: 480 units
◦ Ceiling ventilator: 650 units
Maximum profit: 95 100 $.
18. Material Requirement
Planning
Inventory control system that assures
a good flow of production since it:
◦ Avoids excess inventory
◦ Avoids missing components
19. Material Requirement
Planning
MRP suggests ordering schedule
providing:
◦ Quantities
◦ Time of ordering (leading time)
» In order for a certain number of
products to be ready at a given time.
20. Material Requirement
Planning
Important considerations:
Quantities (product structure diagrams)
Lead time
Lot sizes: Lot sizes might not be equal to
the needed quantity, resulting in
exceeding inventory. The MRP, when
used on a weekly basis, includes these
values in the calculations to ensure a
good utilization of the stock and avoid
financial and material loss.
21. Material Requirement
Planning
Applying MRP to our problem:
From linear programming, we found
optimal monthly production values for
each product:
Product 1 : 480 units (ie: 480 units need to be ready
by the end of week 4).
Product 2 : 650 units
***Assuming lot size of 100 for all components and
subassemblies
22. Material Requirement
Planning
Product Structure Diagram for Product
1 (floor ventilators)
Product 1
SA 1 SA 2
(1unit/product) (2 units/prod.)
C1 C3 C4
C2
(1 (1 (1
(2 units/prod.)
unit/product) unit/product) unit/product)
23. Material Requirement
Planning
Product Structure Diagram for Product
2 (ceiling ventilators)
Product 2
SA 1
SA 2
(1
(2 units/prod.)
unit/product)
C1
C2 C3
(1
(2 units/prod.) (2 units/prod)
unit/product)