© C.Hicks, University of Newcastle Manufacturing Systems Research Chris Hicks
Jan 05, 2016
© C.Hicks, University of Newcastle
Manufacturing Systems Research
Chris Hicks
© C.Hicks, University of Newcastle
Computer Aided Production Management Systems in
Engineer to Order Companies
• ACME grant in collaboration with NEI
Objectives• Identify the characteristics of
companies in ETO/MTO sector• Evaluate the status of CAPM• Identify common CAPM problems• Develop methods for modelling CAPM
systems in ETO/MTO environments• Apply modelling methods to identify
solutions to CAPM problems
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Identification of Company Characteristics and CAPM
problems
• Nine one day visits• Three long visits (3 days - 1 month)• Developed semi-structured “audit”
methodology• Developed methods for company
classification
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Audit
• Markets• Products• Processes• Manufacturing Systems• CAPM Systems
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Company Classification
Shallow Deep
Product Structure
Jobbing
Batch
FlowMan
ufac
turin
g P
roce
ss
Main product
Spares
Subcontract
Company Type “A”
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Company Type “B”
Shallow Deep
Product Structure
Jobbing
Batch
FlowMan
ufac
turin
g P
roce
ss
Valves & PumpsMotorsCabs
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Control Approaches
Shallow Deep
Product Structure
Jobbing
Batch
FlowMan
ufac
turin
g P
roce
ss ProjectManagement
MRP
MRP+ JIT
JIT
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Audit Conclusions
• Markets - demand highly variable and lumpy
• Products - complex, highly customised, mix of products
• Processes - wide range yet all areas tend to be controlled in same way
• Manufacturing systems - mainly functional layouts, high capital employed
• CAPM systems - poor integration, wide variety of subsystems, incorrect data structures, poor operational procedures, generally unsuccessful
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Systems Modelling
• Functional models decompose complex systems using a hierarchical top-down approach. They provide a means of understanding activities and interrelationships
• Information models enable structure of information to be described
• Dynamic models show changing behaviour over time.
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Company X - Context Diagram
Company X
ITT
Tender
ContractAwarded
aCustomer
aCustomer
ProgressReport
bSupplier
bSupplier
QuoteITT Order
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D ata F low D iagram - H igh Leve l
Tendering1
P repareTender
ITT
C ustom er
Tender
D1 ITT & Tender
ITT (copy)
Engineering2
D es ign fo rTende r
ITT (copy)
D2 Supplier Deta ils
Suppliers& Costing
Q uote
Q uality3
P repareC Q A R
ITT (copy)
CQ AR
Designs, TPS, PPRecom m end Suppliers
Projects5
Plan & CoordinateProject
ContractF ile
Engineering6
Conceptual &Detailed Design
ContractF ile (copy)
7 Purchasing
Supplier Selection,O rdering &Expediting
ContractF ile (copy)
ContractF ile (copy)
ProgressReport
ProjectPlan
ProgressReport
ProgressReport
ProgressReport
Drawings,M anuals
DrawingsDrawings
M3 Contract F ile
D/M4 Client Corresp
Approv eP.O .
8 Q uality
ITP & SupplierApproval
ITP
Update
S upplie r
S upp lie r
Q uote
SupplierApprov al
PurchaseO rder Expedite
Inspectionreport
SupplierApprov al
M5 Pref. Suppliers
Supplier
M6 Historic Designs
Designs
M5 Pref. Suppliers
M6 Historic Designs
Supplier
Designs
M/D7 Suppliers
Supplier
D8 Prev ious Suppliers
ContractAwarded
G en. M anager4
A pprova l O fTende r Tender
G.M
B R R
9ProjectReport
Action
Q uote
New DesignsSupplier
PurchaseO rder(copy)
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D ata F low D iagram - Low Leve l :Supp lie r Se lection , O rdering & Exped iting
Purchasing7.1
G enera te B illo f M a te ria ls
D8 Prev ious Suppliers
P ro jects7 . Supplier Selection,Ordering & Expediting
Drawings
Purchasing7.2
S e lec tS upp lie r(s )
Purchasing7.3
O rderC om ponen t
Purchasing7.4
E xped ite
ContractF ile (Copy)
Com ponents(grouped)
Possible Supplier
S upplie r
Q uote
P ro jects
Project P lan(Deliv ery Date)
PurchaseO rder
Project ProgressCheck
E ngineeringApprov eSupplier
Approv eO rder
M/D7 Supplier Literature
NewSupplier
Supplier Selected
PurchaseO rder(Copy)
S upplie rProgress
SupplierDetails
Agreed Deliv eryDate, Location
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Method Limitations• Audit, systems analysis and data
modelling provide static “snapshot” views. Longitudinal studies are a series of snapshots. No model of system dynamics.
• At best enable “best practice” or potential solutions to be described and documented.
• Not possible to perform experiments to examine alternative configurations and evaluate them in terms of specified performance criteria
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Simulation
• Allows modelling of system dynamics• Very expensive in terms of model
building and computational resources• Validation often a problem• Predominantly used for either small
scale models or rough-cut high level models
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Simulation Model CAPM Modules
PP
BOMP
P/A P
MPS
MRP
SFC
FIN
CP
INV
POC
S IM U LA TIO N
C A P M M odu les
E xis ting
D eve lop ing
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PRODUCT DATA
PRODUCT STRUCTURECurrent operationCurrent operation typeCurrent valueActual operation start timesQueue times before each operationActual set up timesActual processing timesQueue times after each operationActual transfer time
PRODUCT STRUCTURE
Product structure codesProduct instance codes
PRODUCT DATA
PART CODEPart codeNameComponent codesComponent quantities
RESOURCE DATAShift patternAudit periodData update periodAvailabilityDispatching ruleOptional resource ruleBatch splitting ruleBatch sizesTransfer deviceMinimum set up timeMinimum processing timeMinimum transfer timeStochastic distributionEfficiencyOverhead cost per hourCost per hour
MINOR RESOURCE DATAMinor resource codeLocationQuantityCost per hourMinimum use time
SHIFT DATAShift numberDaily work pattern
PRODUCT STRUCTURE
Product familyOriginal due timePlanned due timePlanned operation start times
PART CODERoutingOperation typesMinor resources usedMinor resource quantitiesWhen minor resources usedPlanned set up timesPlanned operation timesPlanned transfer timesLead timeLot sizeLot sizing ruleSafety stockSafety lead timePlanned product structure
PRODUCT DATA
MASTER PRODUCTION SCHEDULEMPS Item NumberPart codeQuantity
DEFAULT DATAMinimum set up timeMinimum processing timeMinimum transfer timeMinimum queue before operationMinimum queue after operation
STATIC DATA
RESOURCE DATAResource codeNameOptional resourceLocation (x,y)Rectangular size (w,h)CoordinatesCompany reference
OPERATIONAL DATA
RESOURCE DATAResource statusWork in progress (non added value)Work in progress (added value)Queue lengthMaximum queue lengthOperations per familySum set up timeSum processing timeLast partBatch counter
CONDITIONAL DATA
Refers to
Static data - time invarientOperational data - specified configurationConditional data - dynamic stochastic data
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Key Features
• Large scale model allows whole manufacturing facilities to be represented
• Models facilities, products, processes and planning and control systems
• Many product families can be represented with shallow, medium or deep product structure
• Data structures match ETO/MTO requirements
• Allows variety of planning and control methods to meet local requirements
• May be used as a research tool or for planning and simulation.
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Simulation Case Study
• Heavy Machine Shop used for case study
• Static configuration used layout and other resource constraint information
• BOM information obtained for products• Process data and planning data
obtained for 18 month period.
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Experimental Design
• Series of full factorial experiments
Factors• Process - assembly lead time,
minimum set-up, machining and transfer
• CAPM, scheduling methods, BOMs, dispatching rules, capacity planning
• Product mix / load • Operational - data update period
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Conclusions• Assembly planning and capacity
planning important CAPM subsystems• “Dispatching” rules not very significant• Manufacturing performance sensitive
to transfer times.• Significant advantages gained through
having close control of key resources• Real time data recording led to
improved manufacturing performance
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Consequent research topics
• Manufacturing Layout (Hinrichs, Wall)• Capacity planning (Tay, Holmes,
Hines, Pongcharoen) • Assembly planning (Sullivan ..)• Planning of product development
activities• Planning under uncertainty (Wall,
Brand, Song)• Integration of project planning methods
with MRP type approaches (EPSRC proposal)
• Plan Optimisation through Genetic Algorithms
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Manufacturing Layout
• All data required for layout analysis, clustering and generation in simulation data structures
• Work started with Chris Lee who was interested in improving the layout of Vickers’ Scotswood Road factory
• Much work in layout has focused on moving from functional layout to cellular layouts
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Methods
• Clustering– Matrix based methods– Similarity coefficient methods
• Layout generation– Starting with some candidate
solution generate new layout that minimises (maximises) some objective function
– Simulated annealing– Genetic algorithms
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Capacity Planning
• Finite / infinite loading• Re-planning rules (Tay)• Finite loading rules (Holmes)• Interactive tools (Hines, Poncharoen)• Schedule “optimisation” (Poncharoen)
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Supply Chain Management
• ETO companies moving towards buy rather than make
• Business process analysis approach (McGovern, Earl, Harrison, Hamilton)
• Agent based modelling of supply chains (Harvey, McLeay, Hines)
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IT Implementation
• Embodies audit, business process analysis and requirements definition
• Transfer of computing expertise• 3 Teaching Company Schemes
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Layout design & effect on benchmarks
• Tony Wells Siemens Semiconductors• Data from North Tyneside, US,
Germany, Taiwan.• Pareto analysis of costs• Identification of cost drivers• Relating cost drivers to plant design
configurations• Results so far: potential cost reduction
of 50% on £30m/annum -pity the plant has closed!
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Management of Knowledge
• Data modelling / systems analysis based upon thematic knowledge that is formal, explicit and easily shared
• Knowledge management requires knowledge of product and process structure
• “Tacit” or embedded knowledge that is disorganised, informal, context dependent and relatively inaccessible often important.
• Interested in developing methodologies for systems integration that include both thematic and tacit knowledge
• LABS Proposal with Paul Braiden
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Other Activities
• £180k EDF grant with ISRU to develop distance learning material (Dave Stewardson & Mark Gary)
• TCS with House of Hardy aimed at improving manufacturing efficiency (Rob Davidson & Paul Braiden)
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Summary• Wide portfolio of manufacturing
systems research• Various types of research undertaken
from the theoretical through to applied.• “Market led” rather than “product led”