Exploring Engineering

Chapter 15

Manufacturing Engineering

We Cover Three Shop Topics

Basic Metal Cutting Operations

Speeds and Feeds

Shop Safety

Applications of statistical methods

A statistical method of analyzing defective manufactured products will be introduced. Six Sigma methods will be touched upon.

To Be Safe - Think!

Basic Safety Rules

Wear eye protection at all times

No loose-fitting clothing or jewelry

Do not work alone

Ask Someone If You Are Have Questions

= ?

Traditional Machining Operations

Turning

Drilling

Milling

Typical Drill Press

On Lathes, Part Rotates

On Milling Machines The Cutter Rotates

Two Types Of Milling

Conventional Milling Climb Milling

PartPart

Cutter Cutter

Climb Milling

Both the cutter and the lead screw move the table in the same direction

Climb Milling

Part

Cutter

Speeds And Feeds Are Like Biting And Chewing

Speed: how fast the cutting tool (or part) spinsFeed Rate: how hast the part is advanced into the part

Manufacturers Have Recommended Cutting

Speeds

Calculating The Cutting RPM

Where RPM = revolutions per minute for the cutting tool (mill and drill) or work piece (lathe) CS = cutting speed in surface feet per minute Dia = diameter in inches for the cutting tool (mill and drill) or work piece (lathe)

Dia

CSRPM

*82.3

Same equation for drill press, mill, and lathe

The Feed Rate For Milling)___(#*)_(*)( teethcutterofloadchipRPMFEED

Chip load values are found in tables (check Machineries Handbook)

We will use 0.003 IPT for high speed steel cutting steel

The Feed Rate For Turning (Lathe)

Variability & Six SigmaNo manufacturedl

part is exactly like another. If everyone in this

class measured the length of new a pencil with a suitable ruler, the derived lengths would randomly vary by small amounts.

Histogram of measurements referred to mean

0

1

2

3

4

5

-1.6 -1.2 -0.8 -0.4 0 0.4 0.8 1.2

Mean - actual, mm

Fre

qu

ency

of

resu

lt

Variability & Six Sigma Extend to many points and in the limit of

large measurements the data become continuous: Plot ordinate as “frequency” (fraction of total

measurements) vs. Z

i

i

i

i

i

i

N

x

x

N

x

xZ

2

2

th

deviation, standard theis

t measuremen i theis

mean, theis in which

Variability & Six Sigma Plot with abscissa Z and ordinate

2)(

2zeZp

Z

p(Z

)

Variability & Six SigmaWhen plotted this way the area under

the curve from - to + is 1.00 (i.e., 100% of the samples) The area from -1 Z 1 contains 68% of

the data The area from -2 Z 2 contains 95% of

the data The area from -3 Z 3 contains 99.7%

of the data

Example 1:You make 1,000 rods of mean length

10.0 cm, standard deviation 0.1 cm.How many are within a specified range

of between 9.8 and 10.2 cm? Z = ±0.2/0.1 = ±2. Thus 95% of the rods, or

950 are within spec and 50 are not serviceable since out of spec.

Example 2: You make 1,000 rods of mean length 10.0

cm, standard deviation 0.1 cm. How many are within a specified range of

between 9.85 and 10.15 cm? Z = ±0.15/0.1 = ±1.5. In the general case get the area

under the normal curve using Normsdist(Z) in Excel. Normsdist(1.5) yields 0.933 and 67 rods will fail

Less failures than in Example 1 since the window of acceptance is wider.

Variability & Six SigmaVariability has deep

consequences For example: Are

these two noisy means equivalent?

0.0

20.0

40.0

60.0

80.0

100.0

120.0

-20 30 80

Expt. #

Wid

get

vari

able

o xAverage 107.2 95.6Std dev 0.4 4.1

• Hint: Add ±boundaries for 2 - if they overlap Then the data cannot be statistically distinguished with 95% confidence

Six Sigma

A quality control program introduced into the US by Motorola to reduce the number of rejects and thus improve the quality of their products. Z = 6 is the stated target; with some slight

of hand it translates to 3.4 defects per million samples)

Summary Manufacturing engineering is covered in

Chapter 15 Machining, cutting, welding, extrusion, pultrusion

are all ways of manufacturing different products Derivation of formulae relating to cutting rates for

drilling, milling, and lathe work, are derived. Statistical analysis leads to better process control

and lest rejected widgets being out of specifications.