Manufacturing and Service Enterprise with Risks: A Stochastic Management Approach

279 Pages·2009·9.527 MB·English

by  Masayuki Matsui (auth.)

Manufacturing and Service
Enterprise with Risks
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∗Alistoftheearlypublicationsintheseriesisfoundattheendofthebook∗
Manufacturing and Service
Enterprise with Risks
A Stochastic Management Approach
MasayukiMatsui
ProfessorofUEC,Tokyo
123
MasayukiMatsui
TheUniversityofElectro-Communications
Tokyo,Japan
[email protected]
ISSN:0884-82897
ISBN:978-0-387-84803-7 e-ISBN:978-0-387-84804-4
DOI10.1007/978-0-387-84804-4
LibraryofCongressControlNumber:2008932169
(cid:2)c SpringerScience+BusinessMedia,LLC2009
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permissionofthepublisher(SpringerScience+BusinessMedia,LLC,233SpringStreet,NewYork,
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Preface
Thesubjectforthisbookismylifeworkontheenterprisemodelingandintegration
byastochastic/queuingform,andthebookplanwasconceivedbeforemystayinthe
USA in 1996–97 as a visiting scholar. The first title was “Stochastic Management
and Design of Manufacturing Systems.” The first version was attempted in 2001;
however,thisversionwasinappropriateandwasnotrevisedtillnow.
It is 40 years since I attempted a stochastic approach to manufacturing and
management due to the limitations of statisticalapproaches. The century in which
industrial engineering and management rose to the forefront was one in which a
static/statistical approach was applied to the development of classical models and
general/averagetheory.
Thisbookpresentsastochasticmanagementapproachtothemanufacturingand
serviceenterprisewithrisksbyagame/strategicview,andisbasedonmanypapers
in production/queueing studies that have appeared in famous journals. The book’s
objective is to discuss and show the goals and constraints on manufacturing and
serviceenterprises,andtoprovideastrategic/collaborativesolutionformanagement
withrisksinheterogeneity.
Thisbookmainlyfocusesonthethreemanufacturingclasses:continuous,point-
wise, and flexible stream types under risks. These manufacturing streams are first
studied using the respective stochastic processes, and are characterized and devel-
opedasaqueueing/strategiccontrolproblemoflook-ahead/buffer,selection/switch-
over, and arrangement/routings. Moreover, the behaviors of some design/control
variablesareshownandusefultheoriesfordesignareestablished.
Underthesetypes,theMGM(managementgamemodel),consistingofsales(ser-
vice) and production centers, is developed for the problem of profit maximization
subject to risky lead time (speed). The concept of gaming in sales and production
isintroduced;thetwo-stagedesignmethodisappliedtothethreeenterprisetypes,
andthemanagement/designstrategies(ellipticalinshape)arepresentedatthebase
oftheproposedpair-matrixtable(map).
Generally, the theory of constraints (TOC) is a noncooperative improvement
approach; however, the MGM is a cooperative design approach and superior to a
collaborative approach with the TOC. Moreover, its strategic map coincidentally
correspondstotheBSC(balancedscorecard).Finally,agamingapproachisapplied
toachainoftwoMGMsinanSCM(supplychainmanagement),andthewin-win
v
vi Preface
strategyisdiscussedandfoundedonthecaseofToyotaversusDell.Further,thetwo
parallelSCMsaretreatedinasimilarmannerastheseriesSCM.
Basedontheabovementionedideasandobjectives,thisvolumecontainsthefol-
lowing7Partswith25subchapters.
Part I, Introduction. There are many risks involved in globalization and hetero-
geneity. This part is an introduction to the strategic enterprise system and man-
agement under risks. Moreover, it introduces and distinguishes the environmental
andinternalrisksforreaders.Themainfocusismanufacturingandservice(sales)
enterprises,andthesechainsarefoundintheso-calledSCMs.
Part II, Stochastic Management Model. From a system view, enterprises are
regardedasa3M&IsystemthatconsistsofhuMan,Machine/material,Money,and
Information.Furthermore,managementisdefinedastheartoforganizinga3M&I
system, and its structure is distinguished into the following two types: cycle and
game models. The respective stochastic models are prepared, developed, and later
applied.
PartIII,StreamRiskProcesses.ThisParttreatsthestochastic/queueingcontrol
(strategy)ofstreamriskprocesses.Therearetwotypicalstreams:continuousversus
point-wisetypes.Therespectiveconfigurationsforstreamsarecalledassemblyline
andjobshop.Theconfigurationrisksmainlyoccuratthetimeofdemand/processing
fluctuations,andtheserisksshouldbetreatedadvantageously inthecaseofenter-
prises.
PartIV,FlexibleRiskProcesses.ThisParttreatsthestochastic/queueingcontrol
(strategy)ofparallelriskprocesses.Intheconfigurationofflexiblenetworks,there
is a flexible machining/assembly system (FMS/FAS) of the central server type. In
this system, the superiority of hybrid ordered-entry (HE) routing is pointed out in
paralleling.
Part V, Ellipse Management with Risk. This Part considers a few applications
of MGM theory to the basic manufacturing systems. The ellipse theory on the
pair-matrix table is found to be applicable to the management/design strategies of
major manufacturing systems. The strategy maps (elliptical in shape) are shown
for the four configurations, and the respective forms of strategic management are
distinguished.
Part VI, Demand and Supply Risk Chain. This Part treats a few supply chains
consisting of unit-enterprise modules—namely MGMs—under chain risks. Both
the series and the parallel types of MGM chains are found. The respective coop-
eration/collaborationstrategieswouldprovideadifferentmaximizationpropertyat
total profit in an SCM. In such a case, the existence of a maximum is found on a
balancematrixasawin-winconditioninbalancing.
PartVII,EmergingChallenge.ThisPartprovidestheconclusionstowardfurther
management and strategy development under risks. A theory of pair-matrix strat-
egy is presented and discussed in this part; a two-stage design is summarized and
concludingremarksareprovided.
Throughout this book, manufacturing and service management with risks are
treatedbyadoptingastochastic/queueingview.Itisimportantforreaderstoknow
Preface vii
howtoformularizethemanagementstrategyaccordingtorisksandthisbookwould
beusefulforthispurpose.
This work is the fruit of much guidance and cooperation from many people to
whomIamverygrateful.Firstofall,IamgratefultomanymembersoftheMatsui
LaboratoryatTheUniversityofElectro-Communications,Tokyo.Aboveall,Isin-
cerely thank Drs. Tetsuo Yamada and Jing Sun, my research colleagues, for their
kindhelp.
Next, I acknowledge the contribution of the many researchers who reviewed
the first version. Special appreciation is expressed to Dr. Shimon Y. Nof, Profes-
sor at Purdue University, Dr. J.George Shanthikumar, Professor at the University
ofCaliforniainBerkeley;H.C.Tijms,ProfessoratVrijeUniversiteit,Amsterdam;
TakehisaFujisawa,EmeritusProfessorattheUniversityofElectro-Communications,
Tokyo;andToshinaoNakatsuka,ProfessoratTokyoMetropolitanUniversity.
I also wish to thank Dr. Jiro Fukuta, old Emeritus Professor at Gifu Univer-
sity, Japan, and Dr. Hajime Makabe, Emeritus Professor at the Tokyo Institute of
Technology.Moreover,IamindebtedtooldProfessorsShoichiIsotaniandTetsuro
Shingu of Hiroshima University, Japan, and Emeritus Professor Youtaro Ogiwara,
TheUniversityofElectro-Communications,Tokyo,forintroducingmetoalifeof
scholarship.
Finally, for their contributions to the English review, thanks are due to
Dr. T. Fujisawa, Ms. Kyoko Hasegawa, Associate Professor at Ishinomaki Senshu
University, Japan, Mr. Ron Belisle, Excellence-English Editing, Japan, and Mrs.
AkikoIrick,USA.Ialsowishtothankmywife,Kazuko,whohasbeensupporting
myresearchendeavorsforalongtime.
Tokyo,Japan MasayukiMatsui
Contents
PartI Introduction
1 ManagementintheAgeofRisk ................................. 3
2 StochasticManagementApproach............................... 11
2.1 3M&IandStochasticApproach ............................. 11
2.2 RiskChainsandBalancing ................................. 19
PartII StochasticManagementModel
3 ManagementCycleModel ...................................... 29
3.1 ProcessCycleModel ...................................... 29
3.2 Limit-CycleModel........................................ 37
4 ManagementwithSalesRisk.................................... 49
4.1 ManagementGame/StrategicView........................... 49
4.2 ServiceVersusManufacturingModel......................... 63
PartIII StreamRiskProcesses
5 ContinuousRiskStream........................................ 75
5.1 LineDesignWithoutStoppers .............................. 75
5.2 LineDesignwithStoppers.................................. 87
6 Point-WiseRiskProcesses ...................................... 95
6.1 PeriodicTypeStrategy ..................................... 95
6.2 DynamicTypeStrategy ....................................109
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x Contents
PartIV FlexibleRiskProcesses
7 FlexibleCellSystem............................................121
7.1 FlexibleAssemblySystem(FAS)............................121
7.2 FASwithGeneralizedCSPSs ...............................129
8 Job/CustomersRouting ........................................139
8.1 FlexibleMachiningSystem(FMS)...........................139
8.2 FMS/FASandOptimalRouting .............................151
PartV EllipseManagementwithRisks
9 AssemblyEnterprise ...........................................163
9.1 EfficientAssemblyandReconfiguration ......................163
9.2 MixedLineDesignwithLook-Ahead ........................173
10 NonAssemblyType ............................................183
10.1 Job-ShopEnterpriseandEllipseStrategy .....................183
10.2 FlexibleEnterpriseandEllipseStrategy.......................193
PartVI DemandandSupplyRiskChain
11 2MGMChainsandBalancing...................................209
11.1 SerialSCMandBalancing..................................209
11.2 Make-or-BuyandRetailSCMs..............................219
12 ManufacturingSCM...........................................231
12.1 PushVersusPullSystem ...................................231
12.2 ToyotaVersusDellStrategy.................................243
PartVII EmergingChallenge
13 Pair-StrategicMapIssues.......................................255
14 SummaryandRemarks ........................................263
AppendixA:ATheoryofDemanded-to-SupplyEconomics.............269
Index.............................................................273
About the Author
Dr. Masayuki Matsui is a professor in the Department of Systems Engineering
at The University of Electro-Communications, Japan. He received a BS and MS
in Industrial Engineering from Hiroshima University, and a DEng in research on
conveyor-serviced production systems from the Tokyo Institute of Technology,
Japan.HewasavisitingscholaratUCBerkeleyandPurdueUniversityin1996–97.
His recent research interests are industrial engineering, production and operations
management, management theory, operations research, quality management, and
artificial intelligence. He is the author of over 300 technical papers and 10 books.
Currently,heisPresidentoftheJapanIndustrialManagementAssociation(JIMA)
and is a board member of the International Foundation of Production Research
(IFPR). He served as the editor/director of the JIMA journal (2000–05), was hon-
oredwiththeJIMAPrizeandAwardin2005,andiscurrentlyaSeniorMemberof
IIE.HeislistedinNihon-Shinshiroku(Who’sWhoinJapan),MarquisWho’sWho
inScienceandEngineering,andMarquisWho’sWhointheWorld(USA).
xi