• Keine Ergebnisse gefunden

Short-Term Planning of an Integrated Industrial Complex

N/A
N/A
Protected

Academic year: 2022

Aktie "Short-Term Planning of an Integrated Industrial Complex"

Copied!
19
0
0

Wird geladen.... (Jetzt Volltext ansehen)

Volltext

(1)

SHORT-TERM PLANNING O F AN INTEGRATED I N D U S T R I A L COMPLEX

I g o r Z i m i n G e r m a n Surguchev

A p r i l 1 9 7 5

R e s e a r c h M e m o r a n d a are i n f o r m a l p u b l i c a t i o n s r e l a t i n g t o ongoing o r p r o j e c t e d areas of re- search a t I I A S A . T h e v i e w s e x p r e s s e d are t h o s e o f t h e a u t h o r s , and do n o t n e c e s s a r i l y r e f l e c t t h o s e of I I A S A .

(2)
(3)

Short-Term P l a n n i n g of a n I n t e g r a t e d I n d u s t r i a l Complex

I g o r Zimin and German Surguchev

1. I n t r o d u c t i o n

The d e s i g n and c o n s t r u c t i o n of modern i n t e g r a t e d i n d u s - t r i a l complexes i n v o l v e c o n s i d e r a t i o n o f a g r e a t number o f v a r i a b l e s s u c h a s l o c a t i o n , c a p a c i t y , e n e r g y , economy, e t c . , and a number of r e s p e c t i v e c a l c u l a t i o n s a s w e l l . The v a r i a b l e s embrace t h e f o l l o w i n g p r o b l e m s :

-

r e s o u r c e d i s t r i b u t i o n t a s k s ,

-

c h o i c e of t h e equipment t y p e s and c a p a c i t i e s ,

-

t r a n s p o r t p r o b l e m s , and o t h e r s .

Modern i n t e g r a t e d i n d u s t r i a l complexes r e p r e s e n t a c o m p i l a t i o n of s e p a r a t e p r o d u c t i o n d i v i s i o n s o r i n t e g r a t e d u n i t s which a r e d e s t i n e d t o p e r f o r m t h e s u c c e s s i v e - p a r a l l e l o p e r a t i o n s .

The c h a r a c t e r i s t i c f e a t u r e s o f t h e l a r g e - s c a l e i n t e g r a t e d complexes i n c l u d e g r e a t f l o w s of raw m a t e r i a l , e n e r g y , f i n a l p r o d u c t s and i n f o r m a t i o n . The c o m p l i c a t e d and e x p e n s i v e e q u i p - ment i n c l u d e d i n s u c h i n t e g r a t e d complexes demands t h e p e r f e c t o r g a n i z a t i o n of t h e work, s i n c e e v e n s m a l l i n a c c u r a c i e s i n t h e d e s i g n and c o n t r o l of t h e l a r g e - s c a l e i n t e g r a t e d complexes i n - v o l v e g r e a t l o s s e s o f p r o d u c t i o n , q u a l i t y and s o on.

The e f f e c t i v e n e s s o f t h e work of t h e s e complexes i s d e - f i n e d , t o a c o n s i d e r a b l e e x t e n t , n o t by t h e e f f e c t i v e n e s s of t h e work of t h e s e p a r a t e p r o d u c t i o n d i v i s i o n s , b u t by t h e m u t u a l j o b . T h i s i s a main c h a r a c t e r i s t i c f e a t u r e of most of

t h e i n t e g r a t e d i n d u s t r i a l complexes i n t h e c h e m i c a l , machine- b u i l d i n g , and m e t a l l u r g i c a l i n d u s t r i e s .

A s a c r i t e r i o n of t h e o p t i m a l work of t h e l a r g e - s c a l e c o m p l e x e s , a c e r t a i n summarized i n d e x , which c h a r a c t e r i z e s t h e work o f t h e whole complex, s h o u l d b e g i v e n . Sometimes s u c h a c r i t e r i o n i s c o n s i d e r e d t o be t h e t o t a l i d l e t i m e of a l l t h e u n i t s . I n some c a s e s t h i s c r i t e r i o n p r o v e s t o b e i n s u f f i c i e n t l y common a s i t d o e s n o t f u l l y c h a r a c t e r i z e t h e m u t u a l a c t i o n s o f t h e s e p a r a t e u n i t s and p r o d u c t i o n d i v i s i o n s . A more common c r i t e r i o n can b e t h e p r o d u c t i v i t y o f t h e whole i n -

d u s t r i a l complex. I n t h i s c a s e t h e t a s k c a n b e c o n s i d e r e d a s m i n i m i z a t i o n of t h e t i m e f o r p e r f o r m i n g a g i v e n number o f p r o - d u c t i o n c y c l e s o r m a x i m i z a t i o n o f p r o d u c t i o n c y c l e s d u r i n g a g i v e n t i m e .

(4)

L e t u s c o n s i d e r one of t h e p o s s i b l e a p p r o a c h e s t o t h e s o l u t i o n of t h e problems o f s u c h t y p e s .

2 . Problem S t a t e m e n t

Although t h e g e n e r a l p r o j e c t s c h e d u l i n g problem under

l i m i t e d r e s o u r c e s r e m a i n s u n s o l v e d f o r p r a c t i c a l - s i z e d p r o b l e m s , some s i m p l i f i e d a p p r o a c h e s c a n be s u g g e s t e d f o r t h e rough

i n v e s t i g a t i o n of t h e problem. One of t h e s e schemes i s con- s i d e r e d i n t h i s p a p e r . I t a l l o w s o n e t o c o n s t r u c t a r a t i o n a l

( p o s s i b l y non-optimal from a s t r i c t l y m a t h e m a t i c a l s t a n d p o i n t ) s c h e d u l e t h r o u g h man-machine i n t e r a c t i o n .

The machine s e q u e n c i n g problem, which h a s r e c e i v e d con- s i d e r a b l e e x p o s u r e i n t h e l i t e r a t u r e , i s a s p e c i a l c a s e of g e n e r a l p r o j e c t s c h e d u l i n g . I n t h i s c a s e t h e p r e c e d e n c e n e t - work h a s a s p e c i a l s t r u c t u r e s o t h a t a l l t h e a c t i v i t i e s ( o t h e r t h a n what may b e f i r s t and l a s t dummy a c t i v i t i e s ) have e x a c t l y one p r e d e c e s s o r and o n e s u c c e s s o r (see F i g u r e 1 ) . I n a d d i t i o n i t i s assumed t h a t e a c h a c t i v i t y r e q u i r e s o n l y one u n i t of one t y p e r e s o u r c e and t h a t a l l r e q u i r e m e n t s and a v a i l a b i l i t i e s a r e c o n s t a n t .

F i g u r e 1.

N e v e r t h e l e s s , t h e a s s e m b l y l i n e b a l a n c i n g problem i s c l o s e l y r e l a t e d t o t h e p r o j e c t s c h e d u l i n g problem, s i n c e i t c a n be r e p r e s e n t e d on a s i m i l a r network, a l t h o u g h t h e form of t h e r e s o u r c e s c o n s t r a i n t s may b e q u i t e d i f f e r e n t .

I n t h i s p a p e r w e p r o p o s e a method f o r s o l v i n g t h e prob- lem. I t i s based on t h e e x t e n d i n g of t h e p r o c e d u r e s o r i g i - n a l l y proposed f o r t h e p r o j e c t s c h e d u l i n g problem (Zi.min [ 2 1 )

.

Note t h a t o u r method i s b a s e d on t h e c o n t r o l t h e o r y a p p r o a c h and d i f f e r s v e r y much from h e u r i s t i c methods t r e a t e d i n Levy 1 1 1 and o t h e r a p p r o a c h e s i n which t h e problem i s s t a t e d a s a s e t of l i n e a r ( i n t e g e r ) i n e q u a l i t i e s and a p p r o a c h e s which d e a l w i t h t h e c o m b i n a t o r i a l problem d i r e c t l y .

We c o n s i d e r t h e problem d e s c r i b e d by t h e f o l l o w i n g con- d i t i o n s :

(5)

A ) A s e t of S j o b s must b e performed. The j - t h j o b c o n s i s t s of n t a s k s numbered from 1 t o n

.

The

j j

maximal t i m e t o p e r f o r m e a c h t a s k i s a known i n t e g e r r e p r e s e n t e d by T i j f o r t h e i - t h t a s k of t h e j - t h j o b .

B) A s e t of K d i f f e r e n t r e s o u r c e s i s a v a i l a b l e . Rk i s t h e amount of t h e k - t h r e s o u r c e a v a i l a b l e i n any t i m e . The amount of t h e k-th r e s o u r c e r e q u i r e d by t h e t a s k i j d u r i n g i t s p r o c e s s i n g i s r F o r example, t h e

i j *

r e s o u r c e s c o r r e s p o n d t o t h e machines of a j o b shop, and e a c h t a s k r e q u i r e s o n l y a s i n g l e machine d u r i n g t h e i n t e r v a l of i t s p r o c e s s i n g .

C) No p r e e m p t i o n of t a s k performance i s a l l o w e d . Once t h e t a s k i j i s s t a r t e d , it must b e p r o c e s s e d u n t i l completed i n no l o n g e r t h a n T i j t i m e u n i t s and no less t h a n T . t i m e u n i t s .

-1 j

D) The s t a r t t i m e s of t h e t a s k s on a g i v e n j o b a r e c o n s t r a i n e d by a c y c l e - f r e e network of t h e CPM-PERT t y p e (see F i g u r e 1)

.

E) We a r e r e q u i r e d t o f i n d t h e v a l u e s f o r

t p j

( s t a r t t i m e ) , j = 1,

...,

n i t i = 1,

...,

S which s a t i s f y con- d i t i o n s A-E and f o r which t h e t o t a l number of j o b s

( o r t a s k s ) completed d u r i n g a g i v e n p e r i o d of p l a n n i n g T i s maximal.

The " d u a l " problem of minimizing t h e c o m p l e t i o n t i m e of a g i v e n s e t of j o b s c a n b e s t a t e d . Here we use t h e f i n i t e - d i f f e r e n c e e q u a t i o n t o d e s c r i b e t h e model w i t h :

t h e dynamic e q u a t i o n :

i j i j

x ( t

+

1) = x ( t )

+

u i j ( t ) 8 (1

-

x i - l r ~ ( t ) 1

,

(1)

where

i j

x ( t ) 3 p o r t i o n of t h e i j - t h t a s k performed t o t h e moment t . I t c o u l d b e i n t e r p r e t e d a s a p o r t i o n of t h e t o t a l t i m e ( T i j ) t h e t a s k r e q u i r e d f o r i t s performance u n t i l t h e moment t ;

(6)

i j

u ( t ) Z p e r f o r m a n c e i n t e n s i t y o r p o r t i o n of t h e i j - t h t a s k h a s b e e n c o m p l e t e d w i t h i n

[ t

-

1,

t l

p e r i o d ;

By i n t r o d u c i n g t h e m u l t i p l i e r 0 t o t h e r i g h t - h a n d s i d e s of t h e e q u a t i o n s , w e t a k e i n t o a c c o u n t t h e p r e c e d e n c e r e l a - t i o n s (see p o i n t D) w i t h :

. t h e i n i t i a l c o n d i t i o n s :

W e assume t h a t t h e i j - t h t a s k b e c o m p l e t e d i f xi' ( t ) = 1.

Thus, w e h a v e t h e f o l l o w i n g c o n s t r a i n t s f o r e v e r y t :

i j a n d n a t u r a l c o n s t r a i n t s f o r u ( t )

A l l r e l a t i o n s f o r m u l a t e d a r e h e l d f o r :

(5) I n a d d i t i o n , f o r t h e f i n a l (dummy) t a s k OS

+

1 w e have:

(7)

R e s o u r c e c o n s t r a i n t s (see p o i n t B ) a r e :

.There a r e n o p r e e m ~ t i o n c o n s t r a i n t s (see p o i n t C) :

W e d e f i n e (see p o i n t E) t y j a s t h e f i r s t moment when t h e f o l l o w i n g c o n d i t i o n i s h e l d :

Some l i m i t a t i o n s t o t h e maximum p e r f o r m a n c e i n t e n s i t y h a v e t o be p r e s e n t (see p o i n t C1:

A c c o r d i n g t o p o i n t E , t h e o b j e c t i v e f u n c t i o n c o u l d be w r i t t e n i n t h e f o r m o f :

S n . j

~ ( u ) =

I

X ] ( T )

,

( 1 2 )

j = l

where T i s a g i v e n i n t e g e r .

~ h u s , t h e p r o b l e m c o u l d be s t a t e d a s

Max I ( u )

,

s. t. (1)

-

(11)

.

To s o l v e t h i s p r o b l e m w e u s e d a m o d i f i c a t i o n of t h e method described i n [ 2 ]

.

Note t h a t t h e model c o u l d i n c o r p o r a t e some a d d i t i o n a l f a c t o r s , f o r e x a m p l e , t h a t t h e j o b s h o u l d p e r f o r m w i t h o u t i n t e r r u p t i o n . Once j o b j i s s t a r t e d , a l l i t s t a s k s m u s t be

(8)

p r o c e s s e d w i t h o u t a t i m e l a g b e t w e e n t h e f i n i s h t i m e o f t h e p r e d e c e s s o r a n d s t a r t t i m e o f t h e s u c c e s s o r . The re-

s o u r c e c o n s u m p t i o n and s u p p l y d e p e n d e n c e o f t i m e a l s o c o u l d be c o n s i d e r e d , e t c .

3 . Complex Oxygen P r o c e s s e s - - C o n t i n u o u s C a s t i n g Model ( p a r t i c u l a r case)

A s a n e x a m p l e , a n i n d u s t r i a l s y s t e m c o n s i s t i n g o f two c o m p l e x e s , o x y g e n - c o n v e r t e r s a n d c o n t i n u o u s c a s t i n g m a c h i n e s f o r s t e e l p r o d u c t i o n , i s c o n s i d e r e d i n t h i s work. Such s y s - t e m s a r e c o n s i d e r e d t o b e e f f e c t i v e a n d a r e b e i n g i n s t a l l e d a l l o v e r t h e w o r l d . A c c o r d i n g t o a number o f f o r e c a s t s , s t e e l p r o d u c t i o n w i l l be b a s e d m a i n l y on t h e s e p r o c e s s e s i n t h e n e a r f u t u r e .

The t a s k o f t h e o x y g e n - c o n v e r t e r complex i s t h e p r o d u c - t i o n of s t e e l o f a g i v e n c o m p o s i t i o n a n d t e m p e r a t u r e . C y c l i c p r o d u c t i o n i s c h a r a c t e r i s t i c o f t h e s e c o m p l e x e s . T h e r e are some p r o c e s s a n d p r o d u c t i o n c o n t r o l s y s t e m s b e i n g d e v e l o p e d f o r i m p l e m e n t a t i o n i n t h i s t v p e o f complex. I n 1 9 7 3 , a b o u t e i g h t y o f t h e s e s y s t e m s , u s i n g m i n i - and a v e r a g e c o m p u t e r s , w e r e

f u n c t i o n i n g a r o u n d t h e w o r l d .

The t a s k s o f s u c h s y s t e m s i n c l u d e :

-

p r o c e s s c o n t r o l ,

-

p r o d u c t i o n c o n t r o l ,

-

d a t a c o l l e c t i o n f o r s t a t i s t i c a l r e s e a r c h , c a l c u l a t i o n , e t c .

The p r o d u c t i o n c o n t r o l s y s t e m s a r e n o t i n c l u d e d i n t h e i n t e - g r a t e d c o n t r o l s y s t e m o f t h e e n t e r p r i s e as a r u l e .

The t a s k of t h e c o n t i n u o u s c a s t i n g m a c h i n e complex i s t h e c o n t i n u o u s c a s t i n g of s t e e l i n s l a b s of g i v e n d i m e n s i o n s . C o n t r o l s y s t e m s f o r c o n t i n u o u s c a s t i n g m i l l s h a v e b e e n d e v e l - oped l e s s c o n s i d e r a b l y .

When s c h e d u l i n g t h e m u t u a l work o f BOP

-

C C , t h e r e i s t h e p r o b l e m o f c h o o s i n g t h e rhythm f o r a l l t h e work i n w h i c h p r o d u c t i v i t y i s maximal. I n o t h e r w o r d s , t h e f r e q u e n c y of t h e h e a t p r e p a r a t i o n i n t h e o x y g e n - c o n v e r t e r complex s h o u l d c o r r e s p o n d t o t h e p r o d u c t i v i t y o f t h e c o n t i n u o u s c a s t i n g m a c h i n e complex.

I n a c c o r d a n c e w i t h t h e g i v e n s t e e l g r a d e , p r o d u c t i v i t y p o s s i b i l i t i e s of e a c h complex, e n e r g y e x p e n d i t u r e s and o t h e r d i s t r i b u t i o n s a r e c h a n g e d . I n t h i s case t h e p r o b l e m o f

o p e r a t i o n - s t a t e s c h e d u l i n g a r i s e s .

(9)

I n a m e l t i n g a n d c o n t i n u o u s c a s t i n g p r o c e s s , e v e r y j o b c o n s i s t s o f three t a s k s : m e l t i n g , p r e p a r i n g f o r c a s t i n g and c a s t i n g i t s e l f . T h i s n e t w o r k d i a g r a m i s shown i n F i g u r e 2.

I -1

- I

PREPARATION

I - I -

S

... ... . . . ... ...

F i g u r e 2.

C o n v e r t e r s f o r t h e m e l t i n g a n d c a s t s f o r t h e c a s t i n g a r e c o n s i d e r e d h e r e a s r e s o u r c e s . W e f o r m u l a t e t h e model by u s i n g a s i n g l e i n d e x :

dynamic e q u a t i o n s :

X 3k- 2 ( t

+

1) = x 3 k - 2 ( t )

+

u 3k-2 ( t ) ( m e l t i n g )

,

x 3k-1(t

+

1) = x 3k-1(t)

+

u 3k-1 ( t ) 0 (x 3k-2

-

1) ( p r e p a r a t i o n ) x3k ( t + 1) = x 3 k ( t )

+

~ ~ 0 ~( x 3k-1- ( t 1) ) ( c a s t i n g )

,

k = 1 , 2 ,

...

, S and

r e s o u r c e c o n s t r a i n t s :

w h e r e

ak E t i m e r e q u i r e d t o c o m p l e t e t h e (3k

-

2 ) - t h m e l t i n g ;

bk t i m e r e q u i r e d t o c o m p l e t e t h e 3k

-

t h c a s t i n g ; ck z t i m e r e q u i r e d t o c o m p l e t e t h e (3k

-

1 ) - t h

p r e p a r a t i o n f o r t h e 3 k - t h c a s t i n g ;

(10)

m

-

t h e number o f c o n v e r t e r s ; n

-

t h e number o f c a s t s .

W e assumed t h a t a p r e p a r a t i o n f o r c a s t i n g s does n o t r e q u i r e any r e s o u r c e s .

W e have no preemption c o n s t r a i n t s :

u 3k-2 ( t )

2 -

1

e

(X 3 k - 2 ( t ) )

e c i -

x 3 k - 2 ( t ) 1

,

=k

C o n s t r a i n t s t o t h e maximum performance i n t e n s i t y a r e :

Eqs. (15) and ( 1 6 ) i n d i c a t e t h a t f o r a l l t a s k s i n t e n s i t y c o u l d b e e q u a l t o 0 o r c o r r e s p o n d i n g l y

-

a 1

' -

1 and - 1

.

i 'i bi

The o b j e c t i v e f u n c t i o n ' i s :

where T i s t h e t i m e of c o m p l e t i o n of a l l t h e j o b s .

(11)

4 . A N u m e r i c a l Example

W e h a v e d o n e some c o m p u t a t i o n a l e x p e r i m e n t s w i t h t h e model p r e s e n t e d . An a d d i t i o n a l a s s u m p t i o n i s t h a t n o p r e - e m p t i o n o f t h e j o b p e r f o r m a n c e i s a l l o w e d . The r e s u l t s a r e shown below. The n e t w o r k d i a g r a m i s g i v e n i n F i g u r e 3.

F i g u r e 3 .

Thus, S = 5 , t h e t a s k s 1, 4 , 7 , 1 0 , 1 3 c o r r e s p o n d t o t h e m e l t i n g s ; t h e t a s k s 2 , 5 , 8 , 11, 1 4 a r e p r e p a r a t i o n s f o r

t h e c a s t i n g s ; a n d t h e t a s k s 3 , 6 , 9 , 1 5 c o r r e s p o n d t o t h e c a s t i n g s (see F i g u r e s 4 and 5 ) . T a b l e 1 shows t h e t i m e d u r a - t i o n s f o r e v e r y t a s k .

T a b l e 1. I n p u t d a t a ( d u r a t i o n s o f t h e t a s k s i n m i n u t e s ) .

J o b Task Task Task

number number number number

i i i i

The t a s k numbers ( i n b r a c k e t s ) c o r r e s p o n d t o F i g u r e 3 .

(12)

V A R I A N T i ( m = 2 , n = 3 ) TB

=I70

0 10 20 30 40 50 60 70 80 90 100 1W 120 130 140 150 160 170

F I G U R E 4 TIME [MINUTES]

t

C O N V E R T E R L O A D I N G 2

( A V A I L A B L E 1

C A S T S

t

L O A D I N G

T " = 170 F I G U R E

5

3 2 1

1; 0 10 i 0 50

; & &

90 I& 1i0 120

la *a 1k 1b

170

--- -- --- - -

( A V A I L A B L E 1 --

--- - -

- -

-

- - - - -

--

-

TIM

(13)

The following variants have been computerized and examined (Table 2).

Table 2. Input data (resource supplies).

Variant Converters Casts number

iii 4 4

iv 5 2

Ghant diagrams which correspond to the optimal solution of the problem and resource loadings are shown in Figures 4-13.

The construction of the surface T* (m, n) would help the management of a plant or a job shop to select the appropriate amount of facilities from the available set and to deal with

the input-payoff analysis very effectively.

The surface (or table) T* (m, n) could be easily constructed on the basis of the problem solution for all the m and n. In our case the total number of these calculations is equal to twelve. Each calculation required about 0.1 sec of the CP time on the CDC-6600 computer.

Note that the solution of the problem (T') with the constraints (15) removed gives us the low boundary to the length of the

optimal schedule for the initial problem (T*). That is

In this variant the low boundary has been achieved. The solution with the constraints (15) removed is shown in Figures 6 and 7. This solution (Figure 6) is not acceptable for our initial problem due to the violation of the constraints men- tioned in point C (see Figure 8 and Figure 9).

In this case we could conclude that three casts will be

enough to complete the whole job within the same time: that is, the

(14)

T A S K N U M B E R

. I l l l l l l ////////// -

D X) M 30 40 50 60 70 80 90 100 110 120 130 140190 180 170

F I G U R E

6

t

CONVERTER LOADING

2

- - - - - - - - - - -

( A V A I L A B L E ) 1 --

TI ME 0 .

FIGURE

7

3 - 2 - -

1 0

10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170

. - - -

- --- --- - - - - -

( A V A I L A B L E )

- - -

-

--

L TIME

r I b

(15)

FIGURE

8

t

CONVERTER LOA Dl N G

3

( AVAILABLE I

. -

10 20

30

40 50 60

70

80 90 160 1K) 120 130 1 4 0 I& 160 T I M E

i CAST LOAD1 N G

.--- --- - - - - -

( AVAILABLE 1

F I G U R E

9

L

I

L

-

(16)

optimal number of casts for the given number of converters is equal to three (see Figure 10 and Figure 11).

In this case the increase in the number of casts will not lead to a time decrease. An increase in the number of converters (to five) will decrease the time to T* = 135.

The simultaneous increase of the number of converters and casts to five will lead to the time decrease T* = 125. The latter is the minimum possible time in which the given number of jobs can be completed. It corresponds to the case in which all the resources are unlimited (see Figure 12 and Figure 13).

Conclusion

The examples of the tasks we have considered do not

cover all the numerous problems which arise in operation pro- duction processes planning. We propose to continue our job of trying to find the general principles of control of the integrated production complexes of the same kind.

Acknowledgment

We are grateful to Prof. T. Koopmans and Prof. A.

Cheliustkin for their discussions and useful advice.

(17)

V A R I A N T i i i ( m

= 4 , n = 4 )

F I G U R E 10

f

LOADING CONVERTER

F I G U R E 11 A CAST

4 3 2 1

I

*

10 20 30 40 50 60 7 0 80 90 100 110 120 130 140 150 160 T I M E LOAD ING

- . - - - .

( AVAIL A B L E )

- -

--- - - -

-

.- --

- - I

(18)

VARIANT iv (

m = 5 , n = 2

)

I l l l l l l l

/ / / / / / A I

T I M E b

10 20 30 40 50 60 70 60 90 100 110 120 130 160 150 160 1'10 160

F I G U R E 12

1 ---

I AVAILABLE )

---- -

C O N V E R T E R LOAD1 NG

1 I

!

'

TIME

10 20 30 40 50 60 70 80 90 100 110 120 130 140 150

CAST LOAD1 N G

--- - - -

( A V A I L A B L E

10 20 30 40 50 60 70 80 90 100 1lO 120 130 140 150 T I M E

F I G U R E 13

(19)

R e f e r e n c e s

Dl

Levy, F . K . , G.L. Thompson, a n d J . D . Wiest. " M u l t i - S h i p , Multi-Shop Workload Smoothing P r o g r a m . "

N a v a l R e s e a r c h L o g i s t i c s Q u a r t e r l y ,

9

( 1 9 6 2 )

,

37-44.

c21

Zimin, I . " L a r g e - S c a l e S c h e d u l i n g P r o b l e m s i n Long- Range P l a n n i n g .

''

I n t e r n a l p a p e r , J a n u a r y 19 75.

Referenzen

ÄHNLICHE DOKUMENTE

b The verification of the tri-lineage differentiation ability of adipogenesis, osteogenesis, as well as chondrogenesis of hBM-MSC by Oli Red O staining, Alizarin Red Staining and

Figure S5 Manhattan plots of GWAS for primary branch number in a–c 2015 and d–f 2017 for a, d all accessions; b, e japonica accessions; and c, f indica accessions... Figure S6

(a-d) MiR-100 mice showed no altered glucose tolerance in the GTT (a+b) and insulin sensitivity in the ITT (c+d) compared to wildtype animals fed normal chow diet before the

MACCE: Major adverse cardiac and cerebrovascular events MI: Myocardial infarction, Revasc: repeat revascularization.. Supplementary Table S2: Event rate in CABG and PCI according

The numbers with unit below each AFM image represent the thickness of

Peritoneal fluid (PF) and serum was processed before and after operation from n = 12 patients operated with CRS-HIPEC and receiving the MOC31PE immunotoxin IP and from n = 26

Multimodal assessment of results achieved after proximal optimization technique (POT) in provisional. A,B) View of well apposed stent proximal to the bifurcation by direct

B Representative confocal image showing targeted ChR2 expression (green) co-stained with GABAergic neurons (red) in the NAc in these double-transgenic mice (scale bar, 250 μm;