Economics of Metal Cutting 1
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Transcript of Economics of Metal Cutting 1
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8/10/2019 Economics of Metal Cutting 1
1/11
Analysis: Machining Economics
How can we optimizethe machining of a part ?
Identify the objective, formulate a model, solve for optimality
Typical objectives: maximum production rate, and/or minimum cost
Are these objectives compatible (satisfied simultaneously) ?
Formulating model: observations hypothesis theory model
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Analysis: Machining Economics..
Formulating model: observations hypothesis theory model
Observation:
A given machine, tool, workpiece combination has finite max MRR
Hypothesis:
Total volume to cut is minimumMaximum production rate
Model objective:
Find minimum volume stockfor a given part
-- Near-net shape stocks (use casting, forging, )
-- Minimum enclosing volumes of 3D shapes
Models:
- minimum enclosing cylinder for a rotational part
- minimum enclosing rectangular box for a milled part
Solving:
-- requires some knowledge of computational geometry
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Analysis: Machining Economics..
Model objective:
Find optimum operations plan and toolsfor a given part
Model: Process Planning
- Machining volume, tool selection, operations sequencing
Solving:
- in general, difficult to optimize
Example:
or
or
??
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Analysis: process parameters optimization
Model objective:Find optimum feed, cutting speedto [maximize MRR]/[minimize cost]/
Feed:
Higher feedhigher MRR
Fin ish cutting:
surface roughness feed
Given surface finish, we can find maximum allowed feed rate
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Process parameters optimization: feed
Rough cutting:
MRR cutting speed, VMRR feed, f
cannot increase V and f arbitrarily
V MRR;
Tool temperature V, f;
For a given increase in MRR: Vlower tool life than f
Optimum feed: maximum allowed for tool [given machine power, tool strength]
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Process parameters optimization: Speed
provided upper limits, but not optimum
Need a relationbetween tool life and cutting speed(other parameters being constant)
Model objective:
Given optimum feed, what is the optimumcutti ng speed
Taylors model (empirically based): V tn = constant
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Process parameters optimization: Speed
One batch of large number,Nb, of identical parts
Replace tool by a new one whenever it is worn
Total non-productive time =Nbtltl= time to (load the stock + position the tool + unload the part)
Nbbe the total number of parts in the batch.
Total machining time =Nbtmtm= time to machine the part
Total tool change time =Nttctc= time to replace the worn tool with a new one
Nt= total number tools used to machine the entire batch.
Cost of each tool = Ct,
Cost per unit time for machine and operator =M.
Average cost per item:t
b
t
c
b
t
mlpr C
N
Nt
N
NMMtMtC
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Process parameters optimization: Speed
Average cost per item: tb
t
cb
t
mlpr CN
N
tN
N
MMtMtC
Let: total length of the tool path =L
VLtm
1 MLVVLM
t= tool life Nt= (Nbtm)/t Nt/ Nb = tm/ t
Taylors model Vtn= C t = C 1/n/ V1/n = C/V1/n
C
VL
C
V
V
L
t
t
N
N nnnm
b
t/)1(/1
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Process parameters optimization: Speed
Average cost per item: tb
t
cb
t
mlpr CN
N
tN
N
MMtMtC
1 MLVV
LM
C
VL
N
N nn
b
t
/)1(
nn
tclpr VCtMC
LMLVMtC /)1(1 )(
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Process parameters optimization: Speed
nn
tclpr VCtMC
L
MLVMtC /)1(1
)(
nn
tc
prV
n
nCtMC
LMLVdV
dC /)21(2 )1()(0
Optimum speed (to minimize costs)
n
tc n
n
CtM
MCV
)1()(
*
Optimum speed (to minimize time)
cb
t
mlpr tN
N
ttt
Average time to produce part:
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Process parameters optimization: Speed
Optimum speed (to minimize costs)n
tc nn
CtMMCV
)1()(*
Optimum speed (to minimize time)
c
b
t
mlpr tN
Nttt Average time to produce part:
load/unload time
machining timetool change time
V
L
tm
c
b
t
mlpr tN
Nttt
C
VL
N
N nn
b
t
/)1(
Substitute, differentiate, solve for V*