[email protected] ENGR-25_Lec-29_MS_Excel-2.ppt 1 Bruce Mayer, PE Engineering/Math/Physics...

[email protected] • ENGR-25_Lec-29_MS_Excel-2.ppt1

Bruce Mayer, PE Engineering/Math/Physics 25: Computational Methods

Bruce Mayer, PELicensed Electrical & Mechanical Engineer

[email protected]

Engr/Math/Physics 25

MS ExcelTables/Plots



Learning Goals

Construct Formatted Tables in Excel• Use the Cell Formatting Commands

Construct Charts and Graphs• Comparison Charts → Bar, Col, Radar• Analysis Charts → Scatter, Surface

– Curve Fits → Linear Regression

Use tables and graphs as problem solving tools



Using Tables & Charts

Engineers record and present data in two primary formats: Tables and Graphs

Dist Parameter Final Initial

Sx = Xstretch= 1.00005 1.000

Sy = Ystretch = 0.99988 1.000 = Twist = 0.20326 0.000 °

h = Xoffset = -41.88402 0.000 µmk =Yoffset = 30.72551 0.000 µm

T & k Fields in Gap Between Chuck and Injector/Ceiling • Oct99

0.0

0.2

0.4

0.6

0.8

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

HOTTER = z/y COOLER

= (

T-T

1)/(

T2-

T1)

, =

(k

-k1)

/(k2

-k1

)

THETA = (T-T1)/(T2-T1)

lambda = (k-k1)/(k2-k1)

Constant k

ESTIMATE kavg WITH END POINTS• Est. = (k1 + k2)/2 = = 0.04180• Act. = -y•k(z)•(dT/dz)/(T2-T1) = 0.04276• = 2.25%

file = Chuck Heat_Xfer_Oct99.xls

PARAMETERS• Inj/Ceiling Temp, T1 = 65C• Chuck Temp, T2 = 550C• k1 = 0.02554 W/m-K• k2 = 0.05524 W/m-K• k[T(z)) for N2 by Reid, Prausnitz,. Poling



Tables in Reports When using Tables in Reports and

Presentations• Tables should always have:

– a Title– Column headings with brief descriptive names,

symbols and appropriate units.

• Numerical data in the table should be written to the proper number of significant digits.

• The decimal points in a column should be aligned. • Tables should always be referenced and

discussed/explained in the body of the text of the document containing the table



Table Examples

Table IIITypical In-Situ Cleaning Process Conditions

Cleaning Chemical

Chamber Pressure(Torr)

Clean Chemical Flow Rate (slpm)

Ar:NF3 Flow-Rate Ratio

Range Nom Range Nom Range Nom

aHF 50-200 100 1-2 2 n/a n/a

atomic-F 1-10 8 1-2 1.2 1-10 7.5

Unit Test Test V (fpm) At Measurement Position Vavg,90 Test Duct Area Q Test Condition • NotesTested Date No. P1 P2 P3 P4 P5 (fpm) (sq-in) (cfm) PS-fan Ctr-Fan DrvCg-Fan

AA007 22-May-03 1 60 65 65 75 70 60.3 49.5 20.7281 1 1 0BD013 22-May-03 2 160 115 165 150 140 131.4 49.5 45.1688 1 1 0PQ019 17-Jun-03 1 130 170 170 160 170 144 30.625 30.625 1 1 1



Budgeting Table2-MCM SYSTEM Cost

Sub-Assembly (Including outside Mfg. costs)

Prodution Cost

EstimateProduction

Budget

Proto Cost

EstimateProto

Budget

DeviceNet MFCs, 4 ea 8.0 12 8.8 20Pneumatic Valves, 8 ea 2.2 2.2Needle Valves, 4 ea 1.0 1.0Manual Valve, 2 ea; chk valves, 4 ea 1.0 1.0Weldments, 16 ea 4.8 4.8

a-F switching valves, 8 ea 1.8 6 1.8 10Pump Divert Valve Kit, 2 ea 4.0 4.0Weldments, 8 ea 2.4 2.4Upgrade downstream valves to ChemRaz 2.8 2.8

ASTeX Astron, 2 ea 82 80 98 100ASTeX qte SW031599

P-Xducer on Astron outlet, 4 ea 3.2 2 3.2 2Water Flow Sw, 4 ea (cf. 083931 0.9 0.912 ea TC (cf. 080144) 0.3 0.30Total 114.40 100.00 131.20 132.00



Table Construction Demo

Fall: Course TitleCourse No. Units Spring: Course TitleCourse No.UnitsVector Mechanics - DynamicsME 104 3 Technical Communication E 190 3ThermodynamicsME 105 3 Fluid MechanicsME 106 3

Year 3 Mechanics of MaterialsCE 130 3 Mechanical Behavior of Materials ME C124 3Computational MethodsE77 3 Orthopedic Biomechanics ME C176 3Electronic Techniques EE100 3 Game Theory ECON C110 3

Total Units 15 Total Units 15

Fall: Course Title Course No. Units Spring: Course Title Course No. Units

Vector Mechanics - Dynamics ME 104 3 Technical Communication E 190 3Thermodynamics ME 105 3 Fluid Mechanics ME 106 3Mechanics of Materials CE 130 3 Mechanical Behavior of Materials ME C124 3Computational Methods E77 3 Orthopedic Biomechanics ME C176 3Electronic Techniques EE100 3 Game Theory ECON C110 3


Year 3



Charts and Graphs

Carefully The Select the TYPE of Chart• Different Charts Convey Different Info

Make Clear and Easy to Read• Large Fonts• Good Contrast

– Light-on-Dark or Dark-on-Light

Include Legend Unless Info in Title Label All Axes, Including Units



Charts & Graphs cont

Where Appropriate Annotate or Mark points/regions of Interest with Arrows, Ovals, or Text

There are 11 different chart types in Microsoft Excel (and several variations of each type) • This Covers 99.9% of the Chart Types That

Most Engineers will need• Consider Next the Criteria for application



The 11 MS Excel Chart Types



MS Excel Charts

Area Chart• An area chart

emphasizes the magnitude of change over time. By displaying the sum of the plotted values, an area chart also shows the relationship of parts to a whole.

http://4.bp.blogspot.com/_mDaf3IQ-j-4/SvIl7aB-eLI/AAAAAAAACNQ/GpNCqtMI4ZA/s1600-h/stacked-area-chart.jpg



MS Excel Charts

Bar Chart• A bar chart

illustrates comparisons among individual items. Categories are organized vertically, values horizontally, to focus on comparing values and to place LESS emphasis on time. Stacked bar charts showthe relationship of individual items to the whole.

Alignment Effectiveness vs. No. of Calibration Points

27.05

25.00

23.11

21.08

0 5 10 15 20 25 30

65

43

Nu

mb

er

of

Alig

nm

en

t P

oin

ts

Aligned vs. Unaligned Effectiveness file = Align_CoOrd_Test_020320.xls

0 2 4 6 8 10 12 14

N

S

E

W

Production Volume (tons)Re

gion

Milk

IceCream

Chese



MS Excel Charts Column Chart

• A column chart shows data changes over a period of time or illustrates comparisons among items. Categories are organized horizontally, values vertically, to emphasize variation over time. Stacked column charts show the relationship of individual items to the whole.



MS Excel Charts

Line Chart• A line chart shows trends in data at equal

intervals. Although line charts are similar to area charts, line charts emphasize time flow and the rate of change, rather than the amount of change or the magnitude of values.



MS Excel Charts

Pie Chart• A pie chart shows the proportional size of

items that make up a data series to the sum of the items.

• It always shows only one data series and is useful when you want to emphasize a significant element



MS Excel Charts

XY (Scatter) Chart• An xy (scatter) chart

either shows the relationships among the numeric values in several data series or plots two groups of numbers as one series of xy coordinates. It shows uneven intervals, or clusters, of data and is commonly used for scientific data.

TEOS Liquid Source Vapor Bubble Saturation v. Liquid Height

0%

20%

40%

60%

80%

100%

0.0 0.2 0.4 0.6 0.8 1.0

Liquid Level Inside Bubbler, y (inch)

Inte

gra

ted

Bu

bb

le S

atu

rati

on

, Sv

0

30

60

90

120

150

Bu

bb

le R

ise

Tim

e,

r (m

s)

Integrated Saturation (%)

Rise Time (ms)

file = Sv(t)_01.xls

• Bubble Diameter = 1.999 mm

• Dv for TEOS in N2 = 0.0727 cm2/s

• Kinematic viscosity,, = 0.00511 cm2/s

99% Saturation after 67 ms, or 0.46"

Linear portion of r curve indicatesterminal velocity of ~0.23 m/s



MS Excel Charts

Doughnut Chart• Like a pie chart, a doughnut chart shows

the relationship of parts to a whole, but it can contain more than one data series. Each ring of the doughnut chart represents a data series

• Basically nestedPie-Charts



MS Excel Charts

Radar Chart• In a radar chart, each category has its own

value axis radiating from the center point. Lines connect all the values in the same series. A radar chart compares the aggregate values of a number of data series.



MS Excel Charts

Surface Chart• A 3D surface chart is useful when you want

to find optimum combinations between two sets of data. As in a topographic map, colors and patternsindicate areas thatare in the samerange of values.

5060

7080

90100

200250

300350

400450

500550

600650

700

4.4%

4.6%

4.8%

5.0%

5.2%

5.4%

5.6%

5.8%

6.0%

6.2%

6.4%

6.6%

6.8%

Cha

nge

in B

ubbl

er O

utpu

t (%

/°C

)

Bubbler Temperature (°C)

Chamber Pressure (Torr)

TEOS Bubbler Vapor Generator Temp Sensitivity

file =VapGen_T-P_Sens.xls



MS Excel Charts

Bubble Chart• A bubble chart is a type of xy (scatter)

chart. The size of the data marker indicates the value of a third variable.

4-Pt Aligned Error Mag vs. Position • KLARFF Wafer CZHA

-12

-8

-4

0

4

8

12

-4 -3 -2 -1 0 1 2 3 4

Xindex

Yin

de

x

NOTES• OTA-2100• 200mm IBM Wafer CZHA.001 • Test Date = 20Mar02• Aligned Avg Error Vector = 8.52 µm

file = Align_CoOrd_Test_020320.xls



MS Excel Charts

Stock Chart• The stock chart is often used to illustrate

stock prices. This chart can also be used for scientific data, for example, to indicate temperature changes



MS Excel Charts

Cone, Cylinder, and Pyramid Chart • The cone, cylinder, and pyramid data

markers can lend a dramatic effect to 3-D column and bar charts.

0

10

20

30

40

50

60

70

80

Ho

fste

de

Sco

re

Sociable Respecting Dif.Cultures

Building Skills Fairness Influential Considerate

Asia

U.S.



Graph Construction Demo

TABLE I: Vapor Pressure DataVapor pressures (mm Hg) of less than one atmosphere as a function of temperature. (All temperatures are in degrees Celsius)

Chemical 1 5 10 20 40 60 100 200 400 760 mmHg

Sodium, Na 439 511 549 589 633 662 701 758 823 892 oC

1,4-Dioxane C4H8O2-35.8 -12.8 -1.2 12.0 25.2 33.8 45.1 62.3 81.8 101.1 oC

Acetone (CH3)2CO -59.4 -40.5 -31.1 -20.8 -9.4 -2.0 7.7 22.7 39.5 56.5 oC

Butyric Acid, C4H8O225.5 49.8 61.5 74.0 88.0 96.5 108.0 125.5 144.5 163.5 oC

Stannic Chloride, SnCl4 -22.7 -1.0 10.0 22.0 35.2 43.5 54.7 72.0 92.1 113.0 oC

http://research.umbc.edu/~lkelly/DAExp.htm

Given Vapor Pressure Data

Construct a Scatter Chart to Find the Clapeyron Eqn Constants m & bfor Stannic Chloride

bT

mPv 1

ln



Chart Construction ResultSnCl4Vapor Pressure

ln(Pv) = -4.7201(1000/T) + 18.958

R2 = 0.9992

0

1

2

3

4

5

6

7

2.5 2.75 3 3.25 3.5 3.75 41000/T (1/Kelvin)

ln(P

v) (

ln[T

orr

])

-6%

-4%

-2%

0%

2%

4%

6%

8%

10%

12%

Fit E

rror =

(Fit-A

ctua

l)/Actu

al

ln(Pv)(ln[Torr])

Fit Error

Linear (ln(Pv)(ln[Torr]))

Demo_Excel_Table-n-Chart_Build_Fa06.xls



All Done for Today

ExcelPlotting HbH Metering Tube P • Orifice Characteristic • 25Jan00

P = 30.471q

R2 = 0.9996

0

1

2

3

4

5

6

7

8

9

0.00 0.03 0.06 0.09 0.12 0.15 0.18 0.21 0.24 0.27 0.30MFC Flow, q (slpm)

[1

-Ho

le B

ac

k P

res

su

re]

( [

Torr

])

0

10

20

30

40

50

60

70

80

90

1-H

ole

Ba

ck

Pre

ss

ure

, P ([To

rr)

1-Hole Back Pressure (SQRT{Torr})

1-Hole Back Pressure (Torr)

Bernoulli Square Law Behavior

file = Tube-Test_00.xls

PARAMETERS• Exhaust to Atmosphere• 0.312" O.D. Tube• 9.5 mil holes• Rough, 1st-cut Test• Re = 4q/(d) = 1400 @ q = 0.24 slpm



Bruce Mayer, PELicensed Electrical & Mechanical Engineer

[email protected]

Engr/Math/Physics 25

Appendix

6972 23 xxxxf tfyyy

735

masterjslave PxhPn

1



Table Construction Demo (1)

StartFall: Course TitleCourse No. Units Spring: Course TitleCourse No.UnitsVector Mechanics - DynamicsME 104 3 Technical Communication E 190 3ThermodynamicsME 105 3 Fluid MechanicsME 106 3

Year 3 Mechanics of MaterialsCE 130 3 Mechanical Behavior of Materials ME C124 3Computational MethodsE77 3 Orthopedic Biomechanics ME C176 3Electronic Techniques EE100 3 Game Theory ECON C110 3


Top & Bot Rows 20High

Middle Rows 16high

Merge Cells Vertically




Format Alignment of the “Year 3 Cell

Result so Far

Format Dialog Box

Fall: Course TitleCourse No. Units Spring: Course TitleCourse No.UnitsVector Mechanics - DynamicsME 104 3 Technical Communication E 190 3ThermodynamicsME 105 3 Fluid MechanicsME 106 3Mechanics of MaterialsCE 130 3 Mechanical Behavior of Materials ME C124 3Computational MethodsE77 3 Orthopedic Biomechanics ME C176 3Electronic Techniques EE100 3 Game Theory ECON C110 3


Year 3



Table Construction Demo (3) Set Column

Widths• 2, 30, 11, 5, 30,

11, 5

Format Fonts• All RED• Top, Bot, & Lt-End

Rows Bold

Format Top & Bot Cells for VERTICAL Centering



Table Construction Demo (4) Set Border Color

to Blue Grid INSIDE blue



Table Construction Demo (5) Double-Line Blue

Border Outside Double-Line Blue

Border Lt-Vert Cell




Double-Line Blue Border RemainderFall: Course Title Course No. Units Spring: Course Title Course No. Units



Year 3




Center Columns: Course No., Units

Fall: Course Title Course No. Units Spring: Course Title Course No. Units



Year 3



Chart Construction Demo (1)

Start • Open File

Demo_Excel_Table-n-Chart_Build_0511.xls

Copy from Table from Slide-22 → Paste into Demo Sheet • Need Vertical

Data

Horizontal table starting in Col-H

Copy Table Cells and EDIT → PASTE SPECIAL → transpose




Result after Transpose Paste




Archive Data• Make Scratch

WorkSheet; Xfer horizontal Table to to this sheet

Edit Worksheet• Adjust Headings• Delete Cols other

Than SnCl4• Move Remaining

to Right




Place in cols A & B• 1000/T; T in

Kelvins• Ln(Pv)

After Filling A & B

Formula for Col-B• =LN(E8)




Now need to Sort the Data with the indep var (1000/T) in ASCENDING ORDER• DATA → SORT




Highlight/Select Data to Plot

Invoke Chart Wizard




Continue with Chart Wizard




Add X-Grid Lines

Remove Legend

Insert As NEW Sheet• Give Descriptive

Name




Stannic Chloride (SnCl4) Vapor Pressure(ln[Torr])

0

1

2

3

4

5

6

7

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

1000/T (1/Kelvin)

ln(P

v) (

ln[T

orr

])

Chart Wizard Result

Change• X-axis Scale: 2.5-4• Shorten Title• Clear BackGround• Lager, Sq Data Markers• GridLine & Text Colors




Select Chart Area ThenRight-Clik

Select X-axis, Ther Right-Clik




Select Grid Lines, Rt-Clik, Chg Colors

Select Data Series, Rt-Clik, Chg Marker




Position Labels at Page Edges → Stretch-Out Plot Area




Chart Fine-Tuning ResultSnCl4Vapor Pressure

0

1

2

3

4

5

6

7

2.5 2.75 3 3.25 3.5 3.75 41000/T (1/Kelvin)

ln(P

v) (

ln[T

orr

])

Add TrendLine to find Clapeyron m &b Constants




Select Data Series, Rt-Clik, Add TrendLn

Select: Linear, Display Parameters




Fine Tune TrendLine Form & DisplaySnCl4Vapor Pressure

y = -4.7201x + 18.958

R2 = 0.99920

1

2

3

4

5

6

7

8

2.5 2.75 3 3.25 3.5 3.75 41000/T (1/Kelvin)

ln(P

v) (

ln[T

orr

])

SnCl4Vapor Pressure

ln(Pv) = -4.7201(1000/T) + 18.958

R2 = 0.9992

0

1

2

3

4

5

6

7

8

2.5 2.75 3 3.25 3.5 3.75 4

1000/T (1/Kelvin)

ln(P

v) (

ln[T

orr

])

Done with Plot; and have determined m & b by Trendline• Note that the Fit is Excellent;

R2 = 99.92%




Add Fitted Data to table

Copy & Paste from Chart

Calc Using m & b

Analysis of Fit Characteristics

Calc Error=(G4-E4)/E4



Put Fitted Data on Chart• On Table: Select & Copy

Data• On chart: EDIT → PASTE

SPECIAL → dialog Box above




Fine Tune Two-Variable DisplaySnCl4Vapor Pressure

ln(Pv) = -4.7201(1000/T) + 18.958

R2 = 0.9992

-1

0

1

2

3

4

5

6

7

8

2.5 2.75 3 3.25 3.5 3.75 4

1000/T (1/Kelvin)

ln(P

v) (

ln[T

orr

])

Error Data Series

To Make Error Data More Visible Show using SECONDARY Axis at Right



Chart Construction Demo (18)SnCl4Vapor Pressure

ln(Pv) = -4.7201(1000/T) + 18.958

R2 = 0.9992

0

1

2

3

4

5

6

7

8

2.5 2.75 3 3.25 3.5 3.75 4

1000/T (1/Kelvin)

ln(P

v) (

ln[T

orr

])

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%




Fine Tune Two-Axes Display



Chart Construction Demo (20)SnCl4Vapor Pressure

ln(Pv) = -4.7201(1000/T) + 18.958

R2 = 0.9992

0

1

2

3

4

5

6

7

2.5 2.75 3 3.25 3.5 3.75 41000/T (1/Kelvin)

ln(P

v) (

ln[T

orr

])

-6%

-4%

-2%

0%

2%

4%

6%

8%

10%

12%

Fit E

rror =

(Fit-A

ctua

l)/Actu

al

ln(Pv)(ln[Torr])

Fit Error

Linear (ln(Pv)(ln[Torr]))



Nice Chart



Coefficient of Correlation

The coefficient of correlation is an indication of how well the linear relationship determined by the method of least squares fits the data set.

The equation for the coefficient of correlation is:

2i

2i

2i

2i

iiii

)y()yn()x()xn(

)y)(x()yxn(R



Interpretation of R

If R is 0, the points are so scattered that the regression line does not help predict y for a given x.

If R is +1 (positive slope) or –1 (negative slope), the points actually lie on a straight line so almost perfect predictions of y for a given x can be made using the regression line.



Goodness of FitR Value Correlation

0.9 to 1.0 Very high positive

0.7 to 0.9 High positive

0.5 to 0.7 Moderate positive

0.3 to 0.5 Low positive

-0.3 to 0.3 Little, if any

-0.5 to -0.3 Low negative

-0.7 to -0.5 Moderate negative

-0.9 to -0.7 High negative

-1.0 to -0.9 Very high negative

[email protected] ENGR-25_Lec-29_MS_Excel-2.ppt 1 Bruce Mayer, PE Engineering/Math/Physics...

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Transcript of [email protected] ENGR-25_Lec-29_MS_Excel-2.ppt 1 Bruce Mayer, PE Engineering/Math/Physics...