IES 303

1
IES 303

• Chapter 5 Process Performance and Quality
• Objectives
• Understand the quality from customers and
  producers perspectives
• Understand how to construct control charts
• Understand how to determine if a process is
  capable of producing service or product to
  specification
• Week 5-6
• December 8-15, 2005

2
What is Quality?
Which one has a higher quality?
Source Russell and TaylorIII (2005)
3
Meaning of QualityConsumers Perspective

• Fitness for use
• ________________________
• __________________________
• Quality of design
• __________________________________________________
  ___
• A Mercedes and a Ford are equally fit for use,
  but with different design dimensions

Source Russell and TaylorIII (2005)
4
Quality Measure in Manufacturing Industry
5
Quality Measure in service industry

• Nature of defect is different in services
• Service defect is a failure to meet customer
  requirements
• Example of Quality Measure
• ________________________________
• ________________________________
• ________________________________

6
Costs of Poor Process Performance and Quality

• 1. ________________
• Preventing defects before they happen
• Ex redesigning process/product/service, training
  employees, working with suppliers
• 2. ________________
• Costs incurred in assessing the level of
  performance attained by the firms processes
• As preventive measure improve performance,
  appraisal costs decrease because fewer resources
  and efforts are needed
• 3. ________________
• Costs resulting from defects discovered during
  the production of a service / product
• 4. ________________
• Cost that arise when a defect is discover after
  the customer has receive the service / product

7
Total Quality Management (TQM)
Figure 5.2
8
Problem-Solving Process
Plan
Deming Wheel (PDCA)
9
Variation of Output

• ____________________
• ____________________

Standard Deviation/ Spread
Mean
More consistent process ____________________ ____
________________
10
Causes of Variations

• 1. ___________________
• Variation inherent in a process
• Unavoidable variation but can be reduced through
  improvements in the system

• 2. ___________________
• Variation due to identifiable factors or
  unusual incidents
• Ex ____________________________________________
  __
• A process that is operating in the presence of
  assignable causes is said to be out of
  control
• Can be modified through operator or management
  action
• If ignored, tend to produce poor quality
  products or services

11
Basics of Control Charts

• Control charts _________________________________
  _______________________________________________
• Control limits _________________________________

• A process is generally considered to be in
  control if
• No sample points outside the control limits
• Most points are near the process average, without
  too many close to the control limits
• Approximately equal number of sample points above
  and below the center line (process average)
• Randomly distributed around the centerline (no
  pattern)

12
Control Chart Examples
Samples
Figure 5.6
13
Control Chart Examples
Figure 5.7 (a) _____________________ ____________
_________ _____________________
Figure 5.7 (b) _____________________ ____________
_________ _____________________
Figure 5.7
14
Control Chart Examples
Figure 5.7 (c) _____________________ ____________
_________ _____________________
Figure 5.7 (d) _____________________ ____________
_________ _____________________
15
Control Chart Examples
Figure 5.7 (e) _____________________ ____________
_________ _____________________
16
Two Types of Error

• ___________________
• Occurs when the employee concludes that the
  process is out of control based on a sample
  result that falls outside control limits, when in
  fact it was due to randomness
• False Alarm
• Producers risk
• ___________________
• Occurs when the employee concludes that the
  process is in control and only randomness is
  present, when actually the process is out of
  statistical control
• Consumers risk

17
Types of Control Charts

• Charts for variables
• Continuous scale measure.
• Ex length, weight, dimensions, time
• ________________________
• ________________________
• Charts for attributes
• Discrete responses.
• Ex counts good / bad pass / fail on-time /
  late
• ________________________
• ________________________

18
Variable Control Chartsx-bar and R-Charts

• In control process BOTH process average and
  variability must be in control
• Possible that small range/variability but average
  is out of limit, or
• In limit average, but large variability
• A2, D3, D4 are pre-calculated from sample size
  (n) See Table 5.1 page 210

R-Chart
x-bar Chart
R range of each sample k number of samples
19
Ex 1 Slip-Ring Diameter adapted from Russell and
Taylor (2003)(see also example 5.1)
Construct x-bar and R chart and conclude
20
Ex 2 Light Bulb

• The Watson Electric Company produces light bulbs.
  The following data on the number of lumens for
  40-watt light bulb were collected when the
  process is in control.

• Calculate control limits for R and x-bar charts
• A new sample is obtained 570, 603, 623, and 583.
  Is the process still in control?

21
Attribute Control Chartsp- and c-charts

• p-chart
• Proportion defective items in the sample
• __________________

• c-chart
• Number of defects
• __________________

22
Ex 3 Western Jeans Companyadapted from Russell
and Taylor (2003)Also see example 5.3 (pg 215)

• The Western Jeans Company wants to establish a
  p-chart to monitor the production process. The
  company believes that approximately 99.74 of the
  variability in the production process
  (corresponding to 3-sigma limits) is random and
  should be within control limits, whereas .26 of
  the process variability is not random and
  suggests that the process is out of control
• The company has taken 20 samples (one per day
  for 20 days), each containing 100 pairs of jeans
  (n 100) and inspect them for defects. The
  results show in the table
• Construct a p-chart to determine when the
  production process might be out of control

23
Ex 4 Housekeeping serviceadapted from Russell
and Taylor (2003)Also see example 5.4 (pg 216)

• Housekeeping service
• Measure of, for example, dirty sheets, bedcovers,
  pillow, missing room and toilet supplies, and
  etc.
• Data in the table are the results from 15
  inspection samples (rooms) conducted at random
  during 1-month period
• Use 3-sigma limit and construct c-chart

24
Ex 5 Highway Accident

• The AA County Highway Safety Department monitors
  accidents at the intersection B. There are 3
  accidents on average per month.
• Construct an appropriate control chart with
  3-sigma control limits
• Last month, 7 accidents occurred at the
  intersection. Is it sufficient evidence to
  justify a claim that something has changed in the
  intersection?

25
Process Capability
To determine whether the process is capable of
producing non-defective unit

• Range of natural variability in process
• Measured with control charts.
• Process cannot meet specifications if natural
  variability exceeds tolerances
• 3-sigma quality
• Specifications equal the process control limits.
  
• 6-sigma quality
• Specifications twice as large as control limits

Figure 5.13
26
Process Capabilityadapted from Russell and
Taylor (2003)

• Natural variation exceeds design specifications
• ____________________
• ____________________
• ____________________

Design Specifications
(b) Design specifications and natural variation
the same ____________________ ________________
____ ____________________
Process
27
Process Capabilityadapted from Russell and
Taylor (2003)
Design Specifications
(c) Design specifications greater than natural
variation ____________________ ______________
______ ____________________
Process
(d) Specifications greater than natural
variation, but process off center
____________________ ____________________ ______
______________
Design Specifications
Process
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Process Capability Measures

• Process Capability Ratio (Cp)
• Process Capability Index (Cpk)

29
Ex 6 Process Capability

• A part has a length specification of 5 inches
  with tolerances of .004 inches. The current
  process has an average length of 5.001 inches
  with a standard deviation of .001 inches.
• Calculate the Cp and Cpk for this process.
  Indicate the capability of the current process.