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1) Gear shaving 


Gear shaving is a finishing operation that
removes small amounts of metal from the flanks
of gear teeth. It is not intended to salvage gears
that have been carelessly cut, although it can
correct small errors in tooth spacing, helix
angle, tooth profile, and concentricity. Shaving
improves the finish on tooth surfaces and can
eliminate tooth-end load concentration, reduce
gear noise, and increase load-carrying capacity.
Shaving has been successfully used in finishing
gears of diametral pitches from 180 to 2. Stan-
dard machines and cutters are available for
shaving gears that range in size from 6.4 to 5590
mm (¼ to 220 in.) pitch diameter.
Leaving excessive stock for shaving will
impair the final quality of the shaved gear. For

maximum accuracy in the shaved gear and max-
imum cutter life, a minimum of stock should be
allowed for removal by shaving; the amount
depends largely on pitch. As little as 0.008 to
0.025 mm (0.0003 to 0.001 in.) of stock should
be left on gears having diametral pitch as fine as
48; 0.08 to 0.13 mm (0.003 to 0.005 in.) is
allowable for gears having diametral pitch of 2.
Operating Principles. The shaving opera-
tion is done with cutter and gear at crossed axes;
helical cutters are used for spur gears, and vice
versa. The action between gear and cutter is a
combination of rolling and sliding. Vertical ser-
rations in the cutter teeth take fine cuts from the
profiles of the gear teeth.
During operation, the tip of the shaving cutter
must not contact the root fillet, or uncontrolled,
inaccurate involute profiles will result. For
gears to be shaved, protuberance-type hobs that
provide a small undercut at the flank of the tooth
may be preferred. This type of hob avoids the
initial tip loading of the shaving cutter.

GEAR MATERIALS, PROPERTIES, AND MANUFACTURE, J.R. Davis
Davis & Associates, p:103


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2) Vapor Degreasing(manufacturing)(new)

uses  a hydro carbon vapor as a cleaning agent. The use of  vapor 

solves  the  problem  of  solvent  contamination 

because the solvent touching the workpiece is clean 

since.  when  it  boils  off  from  the  reservoir  of  the 

equipment,  it  leaves the contaminants  behind.  In  a 
typical  vapor  degreaser,  illustrated  in  Fig.  8A2a3, 
cooling  coils  in  the  vapor  chamber  walls  contain 
the vapors so that they do not escape. The part may 
be briefly immersed in the boiling or heated  liquid 
solvent,  or  both  in  sequence,  andor sprayed  with 
solvent before being raised to the part of the cham- 
ber  that  contains  the  vapor.  The  part,  if  not 
immersed,  is  normally  cooler  than  the  vapor;  the 
vapor  condenses  on  the  part  and  drips  into  the 
reservoir  below,  carrying  away  oils  and  contami- 
nants  from  the  workpiece.  As  the  workpiece 
warms,  the  condensation  stops  and  the  workpiece 
can be removed from the vapor, dry and very clean. 
The  cleaning  action  of  the  vapor  stage  of  the 
process for heavy soils is limited because the amount 
of  flushing  provided  by  the  condensing  vapor  is 
not  great.  That  is  the  reason  for  the  preliminary 
immersion and  spraying.  Some degreasers  include 
another tank (not  shown in  Fig.  8A2a3) of  cooled, 
clean,  distilled  solvent.  The  workpiece  is  power- 
sprayed  with  enough  of  this  solvent  to  cool  it  as 
well  as  further  clean  it.  Immersion  again  in  the 
vapor, until  the  workpiece  heats  up,  provides  fur- 
ther flushing and self-drying. 

Handbook of Manufacturing Processes, James G. Bralla, p:134


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3) Mean Time To Repair(new)(realiability)

Mean Time To Repair (MTTR) is the most commonly used term to describe the
maintainability of a system. It is the sum of the time required to fix all failures
divided by the total number of failures. The time required to fix the failure
typically includes troubleshooting, fault isolation, repair, and any testing that is
required to verify that the problem has been fixed. Simply stated, it is the time
from when the customer could not use the product to the time the customer
could use it.


Improving Product Reliability Strategies and Implementation, Mark A. Levin and Ted T. Kalal, p: 51


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4) Mean Time Between Failure(new)(reliability)

The most common term used to describe product reliability is the Mean Time
Between Failure (MTBF). This term measures the failure rate of the product
during its normal life. There are other ways to describe the failure rate of a
product, which are explained in the following sections.


1 Mean Time Between Repair
Mean Time Between Repair (MTBR) is another way of describing the basic
measure of reliability for a repairable system. It is a measure of the average
time between all repairs for the systems in the field.

2 Mean Time Between Maintenances (MTBM)
Mean Time Between Maintenances (MTBM) is a commonly used term to
describe the reliability of a repairable system. It is a measure of the average time
between maintenance (preventive maintenance and repair) for all the systems
in the field.

3 Mean Time To Failure (MTTF)
Mean Time To Failure (MTTF) is a commonly used term to describe the
reliability of a nonrepairable system. MTTF describes the average time a
collection of systems runs until the next system failure. This term is usually
used in cases where the product will not be repaired. Because it is not repaired,
it cannot have time ‘‘in between’’ failures in the normal operating sense.


4)Mean Time To Repair (MTTR)
Mean Time To Repair (MTTR) is the most commonly used term to describe the
maintainability of a system. It is the sum of the time required to fix all failures
divided by the total number of failures. The time required to fix the failure
typically includes troubleshooting, fault isolation, repair, and any testing that is
required to verify that the problem has been fixed. Simply stated, it is the time
from when the customer could not use the product to the time the customer
could use it.

5)Mean Time To Restore System (MTTRS)
Mean Time To Restore System (MTTRS) is similar to MTTR but i
additional time associated with obtaining parts to fix the problem.

Improving Product Reliability Strategies and Implementation, Mark A. Levin and Ted T. Kalal, p: 50


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