Control of Manufacturing Process · 2019-09-12 · Control of Manufacturing Process Subject 2.830...
Transcript of Control of Manufacturing Process · 2019-09-12 · Control of Manufacturing Process Subject 2.830...
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Control of Manufacturing Control of Manufacturing
ProcessProcess
Subject 2.830
Spring 2004Spring 2004
Lecture #3 Lecture #3
“Sources of Variation”“Sources of Variation”
February 10, 2004February 10, 2004
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2/10/04 2.830 Lecture #3 © David E. Hardt all Rights Reserved 2
Topics for TodayTopics for Today
•• Causes of VariationCauses of Variation
–– Parameter UncertaintyParameter Uncertainty
•• Definition of Control Input to ProcessDefinition of Control Input to Process
–– Accessible, Deterministic ParametersAccessible, Deterministic Parameters
•• The Process Variation EquationThe Process Variation Equation
•• Process Control HierarchyProcess Control Hierarchy
–– Attacking the Variation EquationAttacking the Variation Equation
•• Control Loops in ManufacturingControl Loops in Manufacturing
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Delineation of Process Delineation of Process
ParametersParameters
Y ( )
(ep ,es ,mp ,ms )
ep equipment properties
es equpment states
m p material properties
ms material states
Equipment MaterialE(t )“controls” Geometry &
Properties
ep, es mp, ms
Y
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What Causes Variations?What Causes Variations?
If Y ( )
Any Change (or uncertainty) in
(ep ,es,m p ,ms)
•Which parameters are most certain and least variable?
(The good ones)
•Which parameters are least certain or most variable?
(The bad ones)
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A Rough Scale of “Goodness”A Rough Scale of “Goodness”
ep Machine Structure, Stiffness
e
Constant / known
Variable / unknown
s Positions Forces, temperatures
ms Stresses, Surface Temp., Flowrate,
Concentration
mp Stress-strain, Tg, Viscosity, Reactivity,
Resistance
Based on What???
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Now Consider a Typical Process:Now Consider a Typical Process:
e.g. Machininge.g. Machining
ep Structural Geometry
Structural stiffens, damping, and natural frequencies,
Tool Geometry
es Tool Velocity, Spindle Speed
Cutting Force
Tool Temperature and Heat Flux
ms Shear stress at tool interface
Bending Stresses in the workpiece
Temperature of chip area
mp Initial Geometry
Material hardness
Basic properties: Y, n, r, …
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We Lost the Controls!We Lost the Controls!
Process Y Process Ouputs
Y ( )
Equipment MaterialE(t )“controls” Geometry &
Properties
•• Where are the control inputs?Where are the control inputs?
–– A specific A specific subsetsubset of the parametersof the parameters
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Where are the Control Inputs to a Where are the Control Inputs to a
Process?Process?
E(t )
•• Example: the latheExample: the lathe
–– The tool positionThe tool position
–– The leadscrew positions?The leadscrew positions?
–– ??????
Equipment Material“controls” Geometry &
Properties
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Control Inputs to a ProcessControl Inputs to a Process
•• What are the “best” inputs?What are the “best” inputs?
’s that are’s that are::
•• deterministicdeterministic
•• accessibleaccessible
•• “fast”“fast”
•• “effective”“effective”
–– significant effect on outputsignificant effect on output
E(t )Equipment Material
“controls” Geometry &
Properties
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Back to the LatheBack to the Lathe
•• Tool PositionTool Position
–– Fast?Fast?
–– Accessible?Accessible?
–– Effective?Effective?
–– Deterministic?Deterministic?
•• What is accessible?What is accessible?
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Back to the LatheBack to the Lathe
•• Tool PositionTool Position
–– FastFast yesyes
–– AccessibleAccessible nono
–– EffectiveEffective yesyes
–– DeterministicDeterministic ??
•• What is accessible?:What is accessible?:
–– Lead Screw RotationLead Screw Rotation
–– FastFast yesyes
–– AccessibleAccessible yesyes
–– EffectiveEffective yesyes
–– DeterministicDeterministic yesyes
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BUT!BUT!
•• If the If the tool positiontool position is downstream of the is downstream of the leadscrewleadscrew
rotation it is no longer deterministic!rotation it is no longer deterministic!
WHY?
Uncertainties in:leadscrew pitch
bearing and nut backlash
machine deflectionsload
temperature
Other Examples?
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DefinitionsDefinitions
•• AnAn InputInput is a Process Parameter that is:is a Process Parameter that is:
–– FastFast
–– AccessibleAccessible
–– EffectiveEffective
–– DeterministicDeterministic
•• AA DisturbanceDisturbance is a Variation in a Process Parameter Caused is a Variation in a Process Parameter Caused
By:By:
–– uncertainty or randomnessuncertainty or randomness
–– inaccessibilityinaccessibility
–– forced variationforced variation
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Some QuestionsSome Questions
•• What parameters are the best candidates for Inputs?What parameters are the best candidates for Inputs?
•• What parameters have the greatest uncertainty?What parameters have the greatest uncertainty?
•• What process class has highest spatial resolution?What process class has highest spatial resolution?
•• What process class has What process class has highesthighest temporal resolution?temporal resolution?
•• What process class has the What process class has the lowestlowest spatial and temporal spatial and temporal
resolution?resolution?
•• Which has the highest precision?Which has the highest precision?
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Some Answers?Some Answers?
•• What parameters are the best candidates for Inputs?What parameters are the best candidates for Inputs?
–– Machine StatesMachine States
•• What parameters have the greatest uncertainty?What parameters have the greatest uncertainty?
–– Material PropertiesMaterial Properties
•• What process class has highest spatial resolution?What process class has highest spatial resolution?
–– Serial ProcessesSerial Processes
•• What process class has What process class has highesthighest temporal resolution?temporal resolution?
–– Mechanical ProcessesMechanical Processes
•• What process class has the What process class has the lowestlowest spatial and temporal spatial and temporal
resolution?resolution?
–– Thermal, Chemical and Electrical all are highly diffusiveThermal, Chemical and Electrical all are highly diffusive
•• Which has the highest precision?Which has the highest precision?
Equipment Material“controls” Geometry &
Properties
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A Model for Process VariationsA Model for Process Variations
Equipment Material
“controls”
Geometry &
Properties
•• Recall:Recall:
•• One or more One or more ’s’s “qualify” as inputs : “qualify” as inputs : uu
•• The first order Variation The first order Variation Y gives the “Variation Equation”Y gives the “Variation Equation”
Y ( )
Y ( ,u); u vector of inputs
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The Variation Equation
YY Y
uu
Disturbance
Sensitivity
Disturbances
Control
Sensitivity or
“Gain”
Control Inputs
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Primary Process Control Goal: Primary Process Control Goal:
MinimizeMinimize YYY 0How do we make ?
YY Y
uu
•• holdhold uu fixed (fixed ( uu = 0)= 0)
–– operator training (SOP’s)operator training (SOP’s)
–– good steadygood steady--state machine physicsstate machine physics
•• minimize disturbancesminimize disturbances
-->> minmin
This is the goal of Statistical Process Control (SPC) This is the goal of Statistical Process Control (SPC)
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OROR
YY Y
uu Y 0
•• hold u fixed (hold u fixed ( uu = 0)= 0)
•• minimize the term:minimize the term: the disturbance sensitivitythe disturbance sensitivity
This is the goal of Process Optimization This is the goal of Process Optimization
Y
••AssumingAssumingY
( ) = operating point= operating point
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OROR
YY Y
uu Y 0
•• manipulatemanipulate uu by measuring by measuring Y such thatY such that
uY
u
Y
This is the goal of Process Feedback Control This is the goal of Process Feedback Control
••Compensating for (not eliminating) disturbancesCompensating for (not eliminating) disturbances
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Statistical Process Control
YY Y
uu
Detect
and
Minimize
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Process Optimization
YY Y
uu
Empirically
Minimize
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Output Feedback Control
YY Y
uu
Manipulate
Actively
Such that
Y
uu
Y
Compensate for Disturbances
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Process Control HierarchyProcess Control Hierarchy
•• Reduce DisturbancesReduce Disturbances–– Good HousekeepingGood Housekeeping
–– Standard Operations (SOP’s)Standard Operations (SOP’s)
–– Statistical Analysis and Identification of Sources (SPC)Statistical Analysis and Identification of Sources (SPC)
–– Feedback Control of MachinesFeedback Control of Machines
•• Reduce Sensitivity (Reduce Sensitivity (increase “Robustnessincrease “Robustness”)”)–– Measure Sensitivities via Designed ExperimentsMeasure Sensitivities via Designed Experiments
–– Adjust “free” parameters to minimizeAdjust “free” parameters to minimize
•• Measure output and manipulate inputsMeasure output and manipulate inputs–– Feedback control of Output(s)Feedback control of Output(s)
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Limitations?Limitations?
•• SPC?SPC?
•• DOE/PO?DOE/PO?
•• FBC?FBC?
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SummarySummary
•• Process CausalityProcess Causality
–– Tracing Inputs to OutputsTracing Inputs to Outputs
•• Control Loops in the Process Control Control Loops in the Process Control
HierarchyHierarchy
–– Machine State Control to minimize Machine State Control to minimize
–– Material State Control to minimize Material State Control to minimize
–– Direct Output Feedback ControlDirect Output Feedback Control
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Process Causality PremisesProcess Causality Premises
Equipment MaterialE(t )controls Geometry &
Properties
•Process outputs are material geometryg yg y and propertiesp pp p•Changes in Geometry and Properties are caused by
changes in material state
•Changes in material state are caused by energy input aareep pp pppp pp pppfrom the equipment
•The energy distribution transferred from the equipmentyis
determined by the state and propertiesp p of the equipment
•The means to controluts arets areuts arets areuts arets areuts arets are the output is to manipulate the
distribution of energyp atatppmamamama ririrrtereereererefrom machine to material
eteteproperties of the e
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Process Causality PremisesProcess Causality Premises
•• Process outputs are material Process outputs are material geometrygeometry andand propertiesproperties
•• Changes in Geometry and Properties are caused by Changes in Geometry and Properties are caused by
changes in changes in material statematerial state
•• Changes in material state are caused by Changes in material state are caused by energy input energy input
from the equipmentfrom the equipment
•• The energy The energy distributiondistribution transferred from the transferred from the equipmentequipment isis
determined by the determined by the statestate andand propertiesproperties of the equipmentof the equipment
•• The means to The means to controlcontrol the output is to manipulate the the output is to manipulate the
distribution of distribution of energyenergy fromfrom machine to material machine to material
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Review of Theme/Lab Review of Theme/Lab
ProcessesProcesses
•• Lab: Produce parts using the followingLab: Produce parts using the following
–– CNC TurningCNC Turning Serial, Removal, MESerial, Removal, ME
–– Brake BendingBrake Bending Serial, Deformation, MESerial, Deformation, ME
–– Sheet ShearingSheet Shearing Parallel Removal, MEParallel Removal, ME
–– Injection MoldingInjection Molding Parallel, Formation, ThermalParallel, Formation, Thermal
–– ThermoThermo--formingforming Parallel, Deformation, ThermalParallel, Deformation, Thermal
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CNC TurningCNC Turning
D(x)
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Sources of Variation?Sources of Variation?
Initial
Geometry
Workpiece
Reference
Frame
Final Geometry
Machine
Reference
Frame
Tool Offset
Tool Position
vTool Reference
Frame
•• Geometry ErrorsGeometry Errors
–– Calibration, “Slop”Calibration, “Slop”
•• Machine DeflectionMachine Deflection
•• Material DeflectionMaterial Deflection
•• Tool Shape ChangesTool Shape Changes
–– WearWear
–– Built Up EdgeBuilt Up Edge
Key Process Variable is therefore the Cutting Force
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Uncut Chip
Thickness
t o
Chip
Width
b
Rake
Angle
Cutting
Speed v
Cutting Force ModelCutting Force Model
Orthogonal CuttingOrthogonal Cutting
Thus:
Fc = UTS d f u
UTS = material
property
f = equipment state
d = equipment state
What happened to v?
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Sheet Shearing ModelingSheet Shearing Modeling
•• Parallel Case:Parallel Case:
BACKGAUGE
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Serial ShearingSerial Shearing
b
Fc ~ UTS * h * b
UTS ~ 30,000 psi
b=20 in.
h = 0.06
Fc = 36,000 lb.!
Why:
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Injection Molding CycleInjection Molding Cycle
Reciprocating Screw
Hydraulic Unit
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Heat Transfer in the MoldHeat Transfer in the Mold
•• q = k A T/ xq = k A T/ x
–– Rate decreases as T/ x decreasesRate decreases as T/ x decreases
•• Mold heat & polymer coolsMold heat & polymer cools
•• dT/dtdT/dt == TT22/ x/ x22
–– = k / = k / CCpp
•• Polymers have low k and high Cp
q
q
Polymers have low k and high Cp
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Hydraulic Pressure ControlHydraulic Pressure Control
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ThermoformingThermoforming
Po
T1>Tg
T2
• Parallel
deformation
process
• Material
formed at
elevated
temperature
T2
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Key Material Properties:Key Material Properties:
E
Tm
Working
Region
TTg
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Brake Bending of SheetBrake Bending of Sheet
M M
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Simple Model : Pure Moment Simple Model : Pure Moment
BendingBending
Springback
Constant Radius Tool
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Simple Bending Mechanics: Simple Bending Mechanics:
Parameter EffectsParameter Effects
•• Tool Shape (Tool Shape (RRtooltool) determines the shape ) determines the shape under loadunder load
•• Elastic Springback determines the final Elastic Springback determines the final shapeshape
•• What determines the springback?What determines the springback?
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Simple Bending ModelSimple Bending Model
M
r = 1/K
y
=K y
M h
b
K = curvature of the toolingK = curvature of the tooling
h = thickness of the sheeth = thickness of the sheet
(y) = through thickness strain(y) = through thickness strain
What is M(K)
(or K(M)) ?
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Simple Beam TheorySimple Beam Theory
h
b
M
r = 1/K
y
=K y
M
(y) Ky
M (y)ybdyh/ 2
h / 2
dAmoment arm
d
y
dAb
h
dy
(y) = ?
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Material Model: Material Model:
Elastic Perfectly PlasticElastic Perfectly Plastic
E
Y
Y
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The MThe M--K CurveK Curve
M
MY
EI
KKY
3/2 MY
Loading
EIUnloading
Ktool
K
Kpart
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Final Shape: SpringbackFinal Shape: Springback
KMmax
EIKpart Ktool K
K = shape of tool
E= material property
I1
12bh
3cubic dependence on thickness
Mmax ?
Mmax = (KY, EI)
Strong Dependence on
yield properties
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Effect of Material Variations: Effect of Material Variations:
Increase in Yield StressIncrease in Yield Stress
M
K
EI
KY
MY
Ktool
K
Kpart
MY’
K
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See You in LabSee You in Lab