Chapter 3 Flashcards
Total quality management principles
- customer satisfaction
2.employee involvement
3.continuous improvement
IT’S ABOUT TEACHING
six sigma
involves setting very high standards
conformance to specifications
this is what operations managers have control over
value
quality measured with reference to price
fitness for use
a car that starts every morning
support
company’s reputation if there is a problem
psychological impressions
your initial impressions
continuous improvement
uses problem solving techniques within work teams
why are teams key?
kaizen-took american experts to teach them how to be better in quality
SPC
statistical process control
acceptance sampling
if things are ok then after sampling you can accept the entire lot of incoming materials
AQL
acceptance quality level
the quality level desired by the consumer as customer it’s what you will allow from your supplier
if it passes
it’s below aql
type 1 sample error
producers error
probability of rejecting a good lot (5% risk)
can lower this if you count more
type 2 sample error
customers
saying that a lot is good but it’s bad (3% risk)
SPC
statistical process control
using stat techniques to determine whether a process is delivering what the customer wants
variation of outputs
no two services of products are exactly alike because the processes used to produce them contain many sources of variation, even if the processes are working as intended
variables
variables-service or product characteristics that can be measured
can be single or many variables but measurements can be in or more than two states
attributes
service or product characteristics that can be quickly counted for acceptable performance
issues can be complex but you just need a yes/no,right/wrong
you can convert a variable into an attribute
true
the sample mean
is the sum of the observations divided by the total number of observations
range
the difference between the largest observation is sample and the smallest
standard deviation
square root of the variance of a distribution
common cause
purely random, unidentifiable sources of variation that are unavoidable with the current process
assignable cause
any variation-causing factors that can be identified and eliminated
control chart
time-based chart that is used to determine whether observed variations are abnormal (our of control or in control)
-they have a center, upper, and lower line
Steps for using a control chart
- take a random sample from the process and calc a variable or attribute performance measure
- if a statistic falls outside the chart’s control limits or exhibits unusual behavior, look for an assignable cause
- eliminate the cause
- repeat
r chart (variable)
measure the variability of a process
x bar chart (variable)
measures whether the process is generating output, on average, consistent with a target value
p chart (attribute)
proportion of defective services or products generated by the process
c-chart (attribute)
number of defects when more than one defect can be present in a service or product
m
number of samples
n
number within the (m) samples
steps to compute control charts
- collect data (20-25 samples)
- compute the range
- determine r-chart control limit (table)
- plot the sample ranges. if all are in control, proceed to step 5
- calc x-bar for each sample and determine the central line of the chart (x double bar)
if standard deviation of process if known
another form of the x-bar chart can be used
