application of the toc fal, ie, seoul national university 1999. 11. 4 eoksu sim([email protected])

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Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim([email protected])

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Page 1: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

Application of the TOC

FAL, IE, Seoul National University

1999. 11. 4

Eoksu Sim([email protected])

Page 2: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

2/21

Contents

• General concepts and terms in TOC

• Recent domestic researches

• Formulation and solution of the drum-buffer-rope constraint scheduling problem(DBRCSP)

• Comment

• Reference list

Page 3: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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General concepts and terms in TOC(1/3)

• What is the TOC?– A production control methodology that maximizes profits in a

plant that has a demonstrated bottleneck.

– A management philosophy developed by Eliyahu M.Goldratt which is useful in identifying core problems of an organization

• The TOC provides 5 step – Identifying the constraints

– Deciding how to exploit the constraint

– Subordinating all other activities to the constraint

– Elevating the constraint

– Continuous improvement step of admonishing against managerial inertia

Page 4: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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General concepts and terms in TOC(2/3)

Theory of Constraints

LogisticsProblem solving/thinking process

Performance systemDBRBuffer

management

Throughputdollar daysInventory

dollar days

Productmix

ThroughputInventory

Operating expense

Five-Stepfocusingprocess

Schedulingprocess

V-A-Tanalysis

ECEdiagrams

ECEaudit

Clouddiagrams Five-Step

focusingprocess

Page 5: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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General concepts and terms in TOC(3/3)

• Performance Measure under TOC– Throughput : the rate at which the system generates money

through sales

– Inventory: All the money that the system invests in purchasing things the system intends to sell

– Operation expense : All the money the system spends in turning inventory into the throughput

• Several additional supporting measurement– Throughput = selling price - raw material

– Net profit from production line = total throughput - the additional operation expense

– ROI = net profit divided by the inventory

Page 6: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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Recent domestic researches

• In IE conference on 30th, Oct. 1999– Development of the TOC-based MPS component

• Using UML, COM like Mr. Yoon

– Present conditions of the TOC

Page 7: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

Formulation and solution of the drum-buffer-rope constraint scheduling

problem(DBRCSP)

Int. J. Prod. Res., 1996, Vol. 34, No. 9, 2405-2420

J. V. Simons, Jr., W. P. Simpson, III, B. J. Carlson, S. W. James, C. A. Lettiere and B. A. Mediate, Jr.

Graduate School of Logistics and Acquisition Management, Air Force Institute of Technology, Wright-Patterson AFB, OH 45433-7765, USA

Page 8: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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Constraint scheduling in DBR systems

• Constraints– Bottleneck, temporary(wandering) bottleneck

– In the TOC, a capacity constraint resource(CCR) is defined to be any resource which restricts throughput

• TOC’s five focusing steps and the idea of DBR production systems are typically focused on two primary problems– product mix : maximizes the overall system value

– product flow : a schedule for each constraint

• This paper will focus on product flow, as determined constraint scheduling

Page 9: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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• The multiple constraint schedules cannot be generated in isolation from each other. - interactive constraints

• Goldratt introduced the notion of rods to deal with both interactive constraints and multiple constraint operations for a single job– Rods - required time lags b/w constraint operations

• time rods : rods b/w operations on different constraints

• batch rods : rods b/w operations on same constraints

– The rod’s placement in the constraint schedule • function of two factors: transfer batch size and the relative magnitude

of the per unit processing time

– Fig. 1 and Fig. 2

Page 10: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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Page 11: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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Problem formulation - general job shop problem

number large very a H

scheduled is i job ofoperation last heat which t machine

otherwise 0or k, mahcineon )indirectlyor (directly

p job precedes i job if 1 of valueaon es which takvariableindicator

k machineon i job of timecompletion

k machineon p, job of qoperation for timeprocessing

k machineon i, job of joperation for timeprocessing

:where

(6) ,, 1 0

(5) , 0

(4) 1 ,,1

(3) 1 ,,1 )1(

),,(),1,( 0

(1)

i

ipk

ik

pqk

ijk

ipk

ik

ijkipkpkik

pqkipkikpk

ijkik

ik

k

y

x

t

t

kpiory

kix

mknpitHyxx

mknpityHxx

kjihjitx

xMinimizei

Page 12: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

12/21

• Process batch vs. transfer batch– The net effect is a partial relaxation of the general job shop

precedence constraint (2)

• The general job shop problem produces schedules for each machine. – DBR systems simplify the problem by requiring schedules only

for the constraint(s).

• In the DBRCSP, rods(time lags) may be placed b/w operations on either the first part in a batch or the last, depending on whether the first constraint operation is faster or slower that the second.

Page 13: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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Problem formulation -the general productionscheduling problem(GPSP)

}ftd-f|{it]1,-[t interval in time processin activities ofset

t]1,-[t period duringk typeresource renewable ofty availabili

iactivity by required K)1,2,...,(kk typeresource renewable ofamount

n1,2,...,i i,activity of date due

n1,2,...,i i,activity of ready time

n1,2,...,i i,activity ofduration

n1,2,...,i i,activity of efinish tim

FS of lag timea with relationsstart -finish with activities of pairs ofset

n1,2,...,i i,activity for unit per timeprocessing

n1,2,..., i i,activity for sizebatch

1,2,...ni i,activity for timesetupt independen-sequence

(13) } *;*)1(;*)1(max{

:where

(12) ,,2,1,

(11)

(10)

(9) 0

(8) ),(

(7)

iii

'ij

'

1

''

t

kt

ik

i

i

i

i

i

i

i

iiiiijjjj'ij

nktSi

ik

ii

iii

jjiji

n

S

a

r

h

g

d

f

H

p

n

s

pnspnspns FS

ftk ar

ihf

i gdf

f

HjidfFSf

fMinimize

t

Page 14: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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• Equation 13 addresses the advantage gained by the use of single unit transfer batches

• Consideration of all three relationships in equation 13 is necessary to ensure the improvement in the schedule is achievable

Page 15: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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Problem formulation - The drum-buffer-rope constraint scheduling problem(DBRCSP)

)length rod therepresents b*(0.5 j and i activitiesbetween sizebuffer

k machineon processing requiring activities all ofset

otherwise} 0or j,activity precedes iactivity if {1

number large very a

job ain operation final thengrepresenti activities ofset

n1,2,...,i i,activity of date due

n1,2,...,i i,activity ofduration

n1,2,...,i i,activity of efinish tim

FS of lag timea with relationsstart -finish with activities of pairs ofset

n1,2,...,i i,activity for unit per timeprocessing

n1,2,..., i i,activity for sizebatch

1,2,...ni i,activity for timesetupt independen-sequence

(19) } *5.0*)1(;*5.0*)1(max{

:where

(18)K 1,2,...,k ,),(

(17)K 1,2,...,k ,),( )1(

(16) 0

(15) ),(

(14) }})0),{max{(max(

ij

'ij

'

1

''

ij

k

ij

i

i

i

i

i

i

ijiijijjjj'ij

kiijji

kjijij

jjiji

iiCi

b

M

y

C

h

d

f

H

p

n

s

bpnsbpns FS

Mjidyff

Mjidyff

f

HjidfFSf

hfMin

Page 16: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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An evaluation of Goal System solutions

• Optimized Production Technology(OPT) - 1979, proprietary– 1990 AGI - DISASTER

– 1994 TOC Center - the Goal System

• The GS is heuristic in nature and is organized consistently with the five focusing steps– Essentially, GS begins by assuming that job order due dates are

the only constraints to be met

• Two aspects of the GS process are particularly noteworthy– whenever constraint schedules are produced, rods are inserted to

protect either previously developed constraint schedule or intervening non-constraint operations

– GS builds schedules for multiple constraints sequentially

Page 17: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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• Construct benchmark test problems(108 problems)– Resource criticality factor as a measure of the severity of the load

placed on a resource

– ten resources types, two resources(overloaded)

– A plant, V plant, T plant

• Obtain multiple GS solutions– Total days late(TDL) for both the best and worst GS solution

– Maximum tardy days(MTD) for both the best and worst GS solution

– %difference b/w best and worst GS solutions for both TDL and MTD

• Obtain optimal solutions– we sought to evaluate the quality of GS solutions compared to

solutions which optimally minimize maximum tardiness(B&B)

Page 18: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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Page 19: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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Conclusion

• The sequence in which multiple constraints are scheduled can make a substantial difference in the quality of GS solutions

• Following the GS recommendation concerning which constraint to schedule first usually produces the best solution

• GS solution appear to do a good job of minimizing maximum tardiness, especially when GS is run more than once(scheduling different constraints first)and the best solution used

Page 20: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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Comments

• TOC is not a really new concept.

• There are some areas that TOC can be applied.

• If you want to understand the Goldratt’s theory more easily, you can read the book “The Goal” which is located in our lab.

Page 21: Application of the TOC FAL, IE, Seoul National University 1999. 11. 4 Eoksu Sim(ses@ultra.snu.ac.kr)

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Reference Lists

• Demeulemeester, E. L. and Herroelen, W. S., 1992, A branch-and-bound procedure for the multiple resource-constrained project scheduling problem. Management Science, 38(12), 1803-1818

• Plenert, G., 1993, Optimizing theory of constraints when multiple constrained resources exist, EJOR, 70, 126-133

• www.goldratt.com

• www.tocc.com