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This repository contains the files of my project for the "Production Planning" course at AUT (Tehran Polytechnic).

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1. Demand Forecasting

1. Demand Forecasting

 
 

2. S&OP

2. S&OP

 
 

3. MPS and MRP

3. MPS and MRP

 
 

README.md

README.md

 
 

final_report.docx

final_report.docx

 
 

final_report.pdf

final_report.pdf

 
 

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Production Planning

This repository contains the files of my project for the "Production Planning" course at Amirkabir University of Technology (Tehran Polytechnic).

Phase 1: Demand Forecasting

Description

The dataset contains 6 tables, containing the actual demands for 6 type of products belonging to 3 groups:

  • Group 1 (G1): M1, M3, and M4
  • Group 2 (G2): M2 and M5
  • Group 3 (G3): M6

This phase focuses on 3 major contributions:

  1. Predicting the demands for each group at the next 6 steps in the time series, implementing and using various forecasting methods such as Simple Exponential Smoothing (SES) and Linear Regression (LR).
  2. Conducting error analysis on the resulting predictions from the forecasting methods, calculating MFE and MAE for each of them.
  3. Calculating the tracking signal for each forecasting method.

Details

Our demand forecasting section contains 5 methods:

  1. Simple Exponential Smoothing (SES) with alpha=0.3.
  2. Simple Moving Average (SMA) with n=3.
  3. Weighted Moving Average (WMA) with weights=[0.2, 0.3, 0.5].
  4. Linear Regression (LR)
  5. Adjusted Linear Regression (ALR) with cycle_length=12.

Results

SES SMA WMA LR ALR

Error Analysis and Tracking Signal

This section's results can be found at ./1.%20Demand%20Forecasting/output.xlsx. However, we can have a glimpse at the tracking signals:

G1 G2 G3
SES 1.627202 1.494879 -5.000000
SMA -1.497890 -0.543943 -5.000000
WMA -2.279876 -1.372624 -5.000000
LR 4.758926 4.039556 3.254925
ALR 5.000000 3.809070 1.948311

Phase 2: S&OP

Description

In this phase, we use the forecasts of the first phase in the S&OP of these 3 product groups, modeling an LP problem and conducting sensitivity analysis on two of its parameters.

The objective function, constraints, parameters, and decision variables can be found at ./2. S&OP/report.pdf. Also, the implementation of this problem in Python's PuLP can be found at ./2. S&OP/notebook.ipynb. Moreover, the solved model is exported and saved at ./2. S&OP/model.json.

Results

total cost: 59338527006666.664
T20 T21 T22 T23 T24 T25
RP (434092, 147043, 5215) (434092, 147043, 5215) (434092, 147043, 5215) (434148, 147033, 4644) (434148, 147033, 4644) (434148, 147033, 4644)
OP (5788, 18832, 1413) (1, 11920, 0) (0, 0, 0) (0, 0, 0) (0, 0, 0) (0, 0, 0)
PI (434092, 147043, 5215) (0, 0, 0) (0, 0, 0) (56, 0, 0) (0, 0, 0) (0, 0, 0)
PD (0, 0, 0) (0, 0, 0) (0, 0, 0) (0, 10, 571) (0, 0, 0) (0, 0, 0)
IL (0, 0, 0) (-599, -2, -300) (655, -6002, -91) (0, -6089, 0) (-44, 8985, 273) (0, 0, 0)
IS (0, 0, 0) (0, 0, 0) (655, 0, 0) (0, 0, 0) (0, 8985, 273) (0, 0, 0)
IG (0, 0, 0) (599, 2, 300) (0, 6002, 91) (0, 6089, 0) (44, 0, 0) (0, 0, 0)
TW 187632 187632 187632 187464 187464 187464
OW 29157 13352 0 0 0 0
HW 167632 0 0 0 0 0
FW 0 0 0 168 0 0

Sensitivity Analysis

As said, sensitivity analysis is conducted on two following parameters:

Regular Salary

rs = 12000000,	total cost: 55962663006666.664
rs = 13000000,	total cost: 57087951006666.664
rs = 14000000,	total cost: 58213239006666.664
rs = 15000000,	total cost: 59338527006666.664
rs = 16000000,	total cost: 60463815006666.664
rs = 17000000,	total cost: 61589103006666.664
rs = 18000000,	total cost: 62714391006666.664

Hiring Cost

hc = 1200000,	total cost: 59137368606666.664
hc = 1600000,	total cost: 59204421406666.664
hc = 2000000,	total cost: 59271474206666.664
hc = 2400000,	total cost: 59338527006666.664
hc = 2800000,	total cost: 59405579806666.664
hc = 3200000,	total cost: 59472632606666.664
hc = 3600000,	total cost: 59539685406666.664

Phase 3: MPS and MRP

In the final phase, MPS is developed and MRP is conducted for each product group. More details can be found at ./3. MPS and MRP/notebook.ipynb and ./3. MPS and MRP/report.pdf.

MPS

Group 1

0 1 2 3 4 5 6 7 8 9 ... 15 16 17 18 19 20 21 22 23 24
Forecast 0.0 109970.0 109970.0 109970.0 109970.0 108673.0 108673.0 108673.0 108673.0 108210.0 ... 108701.0 108701.0 108548.0 108548.0 108548.0 108548.0 108526.0 108526.0 108526.0 108526.0
Order 0.0 101008.0 107570.0 82990.0 92990.0 81660.0 69276.0 62743.0 59740.0 75777.0 ... 70151.0 58829.0 61655.0 53822.0 56719.0 59315.0 60527.0 54358.0 53500.0 62392.0
Demand 0.0 101008.0 107570.0 82990.0 92990.0 81660.0 69276.0 108673.0 108673.0 108210.0 ... 108701.0 108701.0 108548.0 108548.0 108548.0 108548.0 108526.0 108526.0 108526.0 108526.0
PoH 4740.0 119950.0 12380.0 145608.0 52618.0 187176.0 117900.0 9227.0 116772.0 8562.0 ... 6483.0 114000.0 5452.0 113122.0 220792.0 112244.0 219936.0 111410.0 219102.0 110576.0
ATP 0.0 7640.0 0.0 40238.0 0.0 2539.0 0.0 0.0 80701.0 0.0 ... 0.0 95734.0 0.0 162396.0 100184.0 0.0 101333.0 0.0 100326.0 0.0
MPS 0.0 216218.0 0.0 216218.0 0.0 216218.0 0.0 0.0 216218.0 0.0 ... 0.0 216218.0 0.0 216218.0 216218.0 0.0 216218.0 0.0 216218.0 0.0

Group 2

0 1 2 3 4 5 6 7 8 9 ... 15 16 17 18 19 20 21 22 23 24
Forecast 0.0 41469.0 41469.0 41469.0 41469.0 39742.0 39742.0 39742.0 39742.0 38261.0 ... 36780.0 36780.0 32990.0 32990.0 32990.0 32990.0 39005.0 39005.0 39005.0 39005.0
Order 0.0 37048.0 38661.0 32388.0 30016.0 28078.0 29133.0 33582.0 27698.0 28652.0 ... 22506.0 19947.0 23133.0 26109.0 20192.0 22460.0 19769.0 18557.0 18004.0 18910.0
Demand 0.0 37048.0 38661.0 32388.0 30016.0 28078.0 29133.0 39742.0 39742.0 38261.0 ... 36780.0 36780.0 32990.0 32990.0 32990.0 32990.0 39005.0 39005.0 39005.0 39005.0
PoH 3160.0 110257.0 71596.0 39208.0 9192.0 125259.0 96126.0 56384.0 16642.0 122526.0 ... 41548.0 4768.0 115923.0 82933.0 49943.0 16953.0 122093.0 83088.0 44083.0 5078.0
ATP 0.0 6032.0 0.0 0.0 0.0 25654.0 0.0 0.0 0.0 41413.0 ... 0.0 0.0 52251.0 0.0 0.0 0.0 68905.0 0.0 0.0 0.0
MPS 0.0 144145.0 0.0 0.0 0.0 144145.0 0.0 0.0 0.0 144145.0 ... 0.0 0.0 144145.0 0.0 0.0 0.0 144145.0 0.0 0.0 0.0

Group 3

0 1 2 3 4 5 6 7 8 9 ... 15 16 17 18 19 20 21 22 23 24
Forecast 0.0 1657.0 1657.0 1657.0 1657.0 1379.0 1379.0 1379.0 1379.0 1252.0 ... 1139.0 1139.0 1093.0 1093.0 1093.0 1093.0 1230.0 1230.0 1230.0 1230.0
Order 0.0 1497.0 1195.0 1558.0 1280.0 1426.0 1342.0 1074.0 1041.0 1133.0 ... 821.0 1122.0 1122.0 856.0 1019.0 842.0 1074.0 815.0 947.0 855.0
Demand 0.0 1497.0 1195.0 1558.0 1280.0 1426.0 1342.0 1379.0 1379.0 1252.0 ... 1139.0 1139.0 1122.0 1093.0 1093.0 1093.0 1230.0 1230.0 1230.0 1230.0
PoH 1975.0 90570.0 89375.0 87817.0 86537.0 85111.0 83769.0 82390.0 81011.0 79759.0 ... 72586.0 71447.0 70325.0 69232.0 68139.0 67046.0 65816.0 64586.0 63356.0 62126.0
ATP 0.0 63994.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
MPS 0.0 90092.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

MRP

Group 1

0 1 2 3 4 5 6 7 8 9 ... 15 16 17 18 19 20 21 22 23 24
Gross Requirements 0.0 216218.0 0.0 216218.0 0.0 216218.0 0.0 0.0 216218.0 0.0 ... 0.0 216218.0 0.0 216218.0 216218.0 0.0 216218.0 0.0 216218.0 0.0
Scheduled Receipts 0.0 216218.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
PoH 4740.0 4740.0 4740.0 4740.0 4740.0 4740.0 4740.0 4740.0 4740.0 4740.0 ... 4740.0 4740.0 4740.0 4740.0 4740.0 4740.0 4740.0 4740.0 4740.0 4740.0
Net Requirements 0.0 0.0 0.0 216218.0 0.0 216218.0 0.0 0.0 216218.0 0.0 ... 0.0 216218.0 0.0 216218.0 216218.0 0.0 216218.0 0.0 216218.0 0.0
Planned Order Receipt 0.0 0.0 0.0 216218.0 0.0 216218.0 0.0 0.0 216218.0 0.0 ... 0.0 216218.0 0.0 216218.0 216218.0 0.0 216218.0 0.0 216218.0 0.0
Planned Order Release 0.0 0.0 216218.0 0.0 216218.0 0.0 0.0 216218.0 0.0 216218.0 ... 216218.0 0.0 216218.0 216218.0 0.0 216218.0 0.0 216218.0 0.0 0.0

Group 2

0 1 2 3 4 5 6 7 8 9 ... 15 16 17 18 19 20 21 22 23 24
Gross Requirements 0.0 144145.0 0.0 0.0 0.0 144145.0 0.0 0.0 0.0 144145.0 ... 0.0 0.0 144145.0 0.0 0.0 0.0 144145.0 0.0 0.0 0.0
Scheduled Receipts 0.0 144145.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
PoH 3160.0 3160.0 3160.0 3160.0 3160.0 3160.0 3160.0 3160.0 3160.0 3160.0 ... 3160.0 3160.0 3160.0 3160.0 3160.0 3160.0 3160.0 3160.0 3160.0 3160.0
Net Requirements 0.0 0.0 0.0 0.0 0.0 144145.0 0.0 0.0 0.0 144145.0 ... 0.0 0.0 144145.0 0.0 0.0 0.0 144145.0 0.0 0.0 0.0
Planned Order Receipt 0.0 0.0 0.0 0.0 0.0 144145.0 0.0 0.0 0.0 144145.0 ... 0.0 0.0 144145.0 0.0 0.0 0.0 144145.0 0.0 0.0 0.0
Planned Order Release 0.0 0.0 0.0 0.0 144145.0 0.0 0.0 0.0 144145.0 0.0 ... 0.0 144145.0 0.0 0.0 0.0 144145.0 0.0 0.0 0.0 0.0

Group 3

0 1 2 3 4 5 6 7 8 9 ... 15 16 17 18 19 20 21 22 23 24
Gross Requirements 0.0 90092.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Scheduled Receipts 0.0 90092.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
PoH 1975.0 1975.0 1975.0 1975.0 1975.0 1975.0 1975.0 1975.0 1975.0 1975.0 ... 1975.0 1975.0 1975.0 1975.0 1975.0 1975.0 1975.0 1975.0 1975.0 1975.0
Net Requirements 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Planned Order Receipt 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Planned Order Release 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

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This repository contains the files of my project for the "Production Planning" course at AUT (Tehran Polytechnic).

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python mrp production-planning master-schedule

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