RANE industries warehouse management

1. SAS Assignment
(RANE INDUSTRIES)
BY
K.VINOTH
13MBA1078

2. Objective
 To design a warehouse layout to align finished goods based on their
classification.
 To place finished goods in warehouse for easy handling based on
their consumption.
 To forecast the inventory level of warehouse.

3. Product classification
 The products are classified based on their consumption
 The highly consumed products are named as classification A
 The moderately consumed products are named as consumption B
 Lowly consumed products are named as consumption C
 Product of classification A should go to lane 1
 Product of classification B should go to lane 2
 Product of classification C should go to lane 3

4. Warehouse layout
IN
OUT
LANE 2
LANE 1
LANE 3

5. SAS coding's for warehouse
management:
proc import datafile="E:New
foldersheet1.xls" out=work.data1;
run;
proc import datafile="E:New
foldersheet2.xls" out=work.data2;
run;
proc sql;
create table work.combined as
select*
from work.data1, work.data2
where data1.ABC=data2.ABC
order by data1.Part_No;
quit;
proc import datafile="E:New
foldersheet5.xls" out=work.data3;
run;
proc sql;
create table work.combinedlane as
select*
from work.combined, work.data3
where combined.ABC=data3.ABC
order by combined.Part_No;
quit;

6. SAS code to compute lag and
regression:
proc import datafile="E:New
foldersheet7.xls" out=work.data5;
run;
data data5;
set data5;
par1lag=lag1(par1);
run;
data data5;
set data5;
par2lag=lag1(par2);
run;
data data5;
set data5;
par3lag=lag1(par3);
run;
data data5;
set data5;
par4lag=lag1(par4);
run;

7. data data5;
set data5;
par5lag=lag1(par5);
run;
data data5;
set data5;
par6lag=lag1(par6);
run;
data data5;
set data5;
par7lag=lag1(par7);
run;
data data5;
set data5;
par8lag=lag1(par8);
run;
data data5;
set data5;
par9lag=lag1(par9);
run;
data data5;
set data5;
par10lag=lag1(par10);
run;

8. data data5;
set data5;
par11lag=lag1(par11);
run;
data data5;
set data5;
par12lag=lag1(par12);
run;
data data5;
set data5;
par13lag=lag1(par13);
run;
data data5;
set data5;
par14lag=lag1(par14);
run;
data data5;
set data5;
par15lag=lag1(par15);
run;
ODS html file='E:New foldervinoth.html';
proc reg data=work.data5;
model par1=par1lag;
run;
proc reg data=work.data5;
model par2=par2lag;
run;
proc reg data=work.data5;
model par3=par3lag;
run;

9. proc reg data=work.data5;
model par4=par4lag;
run;
proc reg data=work.data5;
model par5=par5lag;
run;
proc reg data=work.data5;
model par6=par6lag;
run;
proc reg data=work.data5;
model par7=par7lag;
run;
proc reg data=work.data5;
model par8=par8lag;
run;
proc reg data=work.data5;
model par9=par9lag;
run;
proc reg data=work.data5;
model par10=par10lag;
run;
proc reg data=work.data5;
model par11=par11lag;
run;
proc reg data=work.data5;
model par12=par12lag;
run;
proc reg data=work.data5;
model par13=par13lag;
run;

10. proc reg data=work.data5;
model par13=par13lag;
run;
proc reg data=work.data5;
model par14=par15lag;
run;
proc reg data=work.data5;
model par15=par15lag;
run;
ODS html close;
run;

11. Conclusion
 Based on the regression equation obtained we can able to forecast
the inventory level of the warehouse for the fore coming months.