CHAPTER 2-Demand Forecasting
Transcript of CHAPTER 2-Demand Forecasting
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PRODUCTIONPLANNING AND
CONTROL(MEFB 433)
Dr. Weria Khaksar
Email: [email protected]
Room No. BN-03-08
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2- DEMANDFORECASTING
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Common Fea"%re! #n A11Forea!"!&
. Te+ a!!%me "a" "e !ame!+!"em "a" e5#!"ed #n "e a!"67#11 on"#n%e #n "e %"%re.
2. Forea!"! are no" ere" anda"%a1 re!%1"! %!%a11+ d#8er romred#"ed ,a1%e! (ERROR).
3. Forea!" o $ro%! o #"em! "end"o 'e more a%ra"e "an#nd#,#d%a1!.
4. Forea!" a%ra+ derea!e! a!
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2- Demand Forea!"#n$E1emen"! o a Good Forea!"&
Te orea!" !o%1d 'e&
.T#me1+
2.A%ra"e3.Re1#a'1e
4.Mean#n$%1
9.Ba!ed on a !#m1e and%nder!"anda'1e me"od
:.Co!"-e8e"#,e
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2- Demand Forea!"#n$S"e! #n "e Forea!"#n$ Proe!!&
. De"erm#ne "e %ro!e o "eorea!".
2. E!"a'1#! a "#me or#;on.
3. Se1e" a orea!"#n$ "en#
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2- Demand Forea!"#n$Forea!" A%ra+&
A%ra+ o a orea!" #! m#n#m#;#n$ "eorea!" error.
A%ra+ # one o "e a"or! oroo!#n$ a orea!"#n$ "en#
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2- Demand Forea!"#n$Forea!" A%ra+&
Tree ommon1+ %!ed mea!%re! or!%mmar#;#n$ #!"or#a1 error! are&
. Mean A'!o1%"e De,#a"#on (MAD)& ',era$easolute error
2. Mean S
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2- Demand Forea!"#n$Forea!" A%ra+&
E5am1e& Com%"e MAD6 MSE and MAPE or "eo11o7#n$ da"a6 !o7#n$ a"%a1 and red#"edn%m'er! o ao%n"! !er,#ed.
2 24 25
23 26
3 26 25
7 20 27
5 23 22
6 2 27
4 26 24
8 2 26
2 24 25
23 26
3 26 25
7 20 27
5 23 22
6 2 27
4 26 24
8 2 26
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2- Demand Forea!"#n$Forea!" A%ra+&
E5am1e& Com%"e MAD6 MSE and MAPE or "eo11o7#n$ da"a6 !o7#n$ a"%a1 and red#"edn%m'er! o ao%n"! !er,#ed.
2 24 25 7 0.9
23 26 -3 3 2.729
3 26 25 2 2 2 0.769
7 20 27 -7 7 26 2.09
5 23 22 7 0.79
6 2 27 5 5 5 .89
4 26 24 -2 2 2 0.769
8 2 26 -7 7 26 2.89
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2 24 25 7 0.9
23 26 -3 3 2.729
3 26 25 2 2 2 0.769
7 20 27 -7 7 26 2.09
5 23 22 7 0.79
6 2 27 5 5 5 .89
4 26 24 -2 2 2 0.769
8 2 26 -7 7 26 2.89
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2- Demand Forea!"#n$Forea!" A%ra+&
Tree ommon1+ %!ed mea!%re! or!%mmar#;#n$ #!"or#a1 error! are&
. MAD& /e#$"! a11 error! e,en1+.
2. MSE& /e#$"! error! aord#n$ "o"e#r !
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2- Demand Forea!"#n$Aroae! "o Forea!"#n$&
Tere are "7o $enera1 aroae!&
=UALITATI>E APPROACES& or sue!ti,e inuts#whi!h o(ten oose re!ise numeri!al des!rition.ermit in!lusion o( SOFT INFORMATION like human
(a!tors# ersonal oinions and hun!hes. ;hesein(ormation are di
=UANTITATI>E APPROACES& =n,ol,e either theroe!tion o( histori!al data or the de,eloment o(asso!iati,e models. ;hey use ARD DATA. >suallya,oid ersonal oinions.
IN PRACTISE6 EITER OR BOT
APPROACES MIGT BE USED TO
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2- Demand Forea!"#n$Common Forea!" Ten#
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2- Demand Forea!"#n$Common Forea!" Ten#
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2- Demand Forea!"#n$Common Forea!" Ten#nit /old# I
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