6σ Note 1 6- σ Requi rement f or Green and Bl ack Belt The green belt must be familiar with and competent in th e following concepts: • The six σ approach. • Basic statistical process control. • Classical design of experiments. • Basic measurement system assessment. • Statistical analysis for process improvement. • Process !"#. • Team problem$solving. • Cost of %uality. &n addition to the re%uirements of the green belt' the blac( belt must have expertise in the following areas: • #dvanced statistical proc ess control. • T aguchi and classical design of experiments. • #dvanced measurement sy stem assessment. • Pro)ect management fundamentals. • Short run SPC. • !ista(e$proofing. • *ean manufacturing. • #dvanced product %uality planning +#P,P-. Customer Satisfaction . Cus tomer sat isfaction is cre ate d thr ough:
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
• One dimensional attributes Performance ( )inear*
"hese characteristics are directly correlated to customer satisfaction! +ncreased functionality or
quality of e&ecution ill result in increased customer satisfaction! onversely, decreasedfunctionality results in greater dissatisfaction! Product price is often related to these attributes!
• Attractive attributes -&citers ( Delighters*
ustomers get great satisfaction from a feature . and are illing to pay a price premium!
%oever, satisfaction ill not decrease belo neutral* if the product lacks the feature! "hese
features are often une&pected by customers and they can be difficult to establish as needs up
front so, sometimes the situation ill go conversely so that customer is not illing to pay
price premium for the attractive attributes*! /ometimes called unknon or latent needs!
Product differentiation can either be gained by a high level of e&ecution of the linear attributes or the
inclusion of one or more 'delighter' features! ut, it should be remembered that customer e&pectations
change over time and a cup holder in a car may be today's delighter, but tomorro it ill be e&pected!
/ome users of Kano also suggest that an additional set of attributes can be classified as 'enragers' .
features hich enrage either through their absence or inclusion!
ased upon the responses, the type of feature can be determined from a simple look.up table, as shon belo! Note, there are some additional attribute classifications#
• +ndifferent responses# these are attributes to hich the customer pays no attention 7+f they are
present, it is nice! +f they are not present, it does not matter7
• uestionable responses and reversals# responses hich contradict each other!
9! Plot features onto the Kano graph
+deally, the features should be mapped onto the graph to provide a visual guide to the relative
importance from a user perspective of different aspects of functionality!
Figure 2: The Kano charts: M te!ting is a Must "or a mobile phone
#otes
• an be difficult to grasp conceptually, but provides a useful additional dimension to specifying
features . in addition to 'ant', 'must have'
• Needs team involvement, as it links like 3D* product features ith user perceptions
"o put it in layman's terms, "s are hat the customer e&pects of a product!!! the spoken needs of the
customer! "he customer may often e&press this in plain -nglish, but it is up to us to convert them to
measurable terms using tools such as D3B-$, etc!
Map the process.
!apping of the process in this stage of the define phase of the six σ methodology is nothing
more than a high level visual representation of the current process steps leading up to
fulfillment of the identified CT, characteristics. This ?as is? process map will be useful
throughout the process as:
# method for segmenting complex processes into manageable portions.
# way to identify process inputs and outputs.
# techni%ue to identify areas of rewor(.
# way to identify bottlenec(s' brea(downs and non$value$added steps.
# benchmar( against which future improvements can be compared with the
original process.
Process mapping
A structured way of mapping and criti!uing the existing $%& '$ew %roduct &ntroduction( process, in
order to examine its effectiveness along a number of dimensions. )ncourages a multi*functional teamto identify critical elements in the process and locate potential areas for improvement.
Description
$ 'bron paper' e&ercise, is so called as it uses a large scale format to map an e&isting business process,
ith an emphasis on being 'rough and ready' rather than a precise, neat and tidy document! $pplied to
the product development process, it encourages a shared understanding of the implications of ne
product introduction on different parts of the business and helps to generate a shared onership of the
process! +t is likely that the process map ill illustrate the comple&ity of the NP+ process and
demonstrate critical flos of information, key check points and areas of over or under* bureaucracy!
"he output is intentionally physically large, hich can be daunting at first but aims to bring the process
+t is possible for a brainstorm to be dominated by one or to individuals, of for the facilitatorto be over 1ealous! "his can result in an atmosphere hich inhibits participation by some
members! +n addition, unless the team is good at e&pressing ideas visually, it is normally orally
and verbally driven!
@@@@so' the lines above indicates a very important principle of 9σ methodology: realistic. The
only way of ma(ing the process of continual improvement is to define' understand and scope
the existing problem within the realistic team4s ability of solving problem. #nd modern team
and pro)ect methodology is exactly to divide the problem into pieces that can be solved by
existing team and talent. That4s why western companies can gain great growth and
outstanding in engineering$ not only the pro)ect engineering' but the management.-
The greatest thing in the world is developing a methodology that can enable a lot of common
people to reali7e very difficult and complicated pro)ect of social' business' and engineering.AAAA
ltimately' the purpose of this stage is to set the foundations for the wor( ahead in solving a
problem. This means that an excellent understanding of the process must exist for all team
members' as well as complete understanding of the CT, characteristics. #fter CT, factors
are identified' everyone in the team must agree on developing an operational definition for
each CT, aspect.
"ffective operational definitions: OUTPUT
• 6escribe the critical to %uality characteristics accurately. $#ccuracy
• #re specific so that the customer expectation is captured correctly. 8Precise' specific
• 6etermine data type. &n this step the team must be able to answer the %uestion' ?<hat do we
want to (now>? Eeviewing materials developed during the previous stage' the team determines
what process or product characteristics they need to learn more about. # good start is the
definition of the data type. This is determined by what is measured. Two types of data can be
collected by measuring:
o #ttribute data. =ne way to collect data is to merely count the fre%uency of occurrence
for a given process characteristic +e.g. the number of times something happens orfails to happen-. 6ata collected in this manner is (nown as attribute data. #ttribute
data cannot be meaningfully subdivided into more precise increments and is discrete
by nature. ?FoDno go? and ?passDfail? data are examples of this category.
o 3ariable data. # different way to loo( at data is to describe the process characteristic
in terms of its weight' voltage or si7e. 6ata collected in this manner is (nown asvariable data. <ith this type of data' the measurement scale is continuous$it can be
meaningfully divided into finer and finer increments of precision.
• 6evelop a data collection plan. &n developing and documenting a data collection plan the team
should consider:
o <hat the team wants to (now about the process.
o The potential sources of variation in the process +Gs-.
o <hether there are cycles in the process and how long data must be collected to
obtain a true picture of the process.
o <ho will collect the data.
o How the measurement system will be tested.
o <hether operational definitions contain enough detail.
o How data will be displayed once collected.
o <hether data is currently available' and what data collection tools will be used if
current data does not provide enough information.
o <here errors in data collection might occur and how errors can be avoided or
corrected.
• Perform measurement system analysis. This step involves performing graphical analysis and
conducting baseline analysis. 6uring this step' the team verifies the data collection plan once it
is complete and before the actual data is collected. This type of analysis is called a
measurement system analysis +!S#-. # typical !S# indicates whether the variation measured
is from the process or the measurement tool. The !S# should begin with the data collection
plan and should end when a high level of confidence is reached that the data collected will
accurately depict the variation in the process. By way of a definition' !S# is a %uantitative
evaluation of the tools and processes used in ma(ing data observations. Perhaps the most
important concept in any !S# study is that if the measurement system fails to pass analysis
before collecting data' then further data should not be collected. Eather' the gauge should be
fixed' the measurement system should be fixed and the measurement ta(ers should be