Transcript Total Quality Management TQM

Total Quality Management
(TQM)
Dr. Gene Fliedner
Decision and Information Sciences
School of Business Administration
Oakland University
7/3/2015
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TQM
• Quality: a powerful competitive weapon
• Importance evidenced by variety of industrial awards
(e.g., Baldrige Award, Deming Prize)
• Complex and multifaceted concept
• TQM is a continuous, organization-wide effort to total
customer satisfaction and continuous process
improvement
• Is the customer always right?
• The underlying principle of TQM programs is to
produce products of high quality in the first place,
rather than depend on detecting defective products
later through inspection.
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Alternative Quality Definitions?
• Product-based definition - quality is a precise and
measurable variable where differences in quality reflect
differences in the quantity of some ingredient or attribute
possessed by a product. Example: content of multivitamins
• User-based definition - in terms of satisfying the
consumers’ wants, needs and preferences. Example: brand
name manufacturer versus generic drugs
• Manufacturing-based definition - conformance to
requirements, meeting specifications. Example: interior
diameter of pipe
• Value-based definition - in terms of costs and prices.
Quality is value for the dollar spent
• Elimination of variability.
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Garvin’s “Dimensions of Quality”
1. Performance – product/service primary
characteristics
2. Reliability – consistency of performance
3. Durability – length of useful life
4. Conformance to specifications
5. Aesthetics – appearance, feel, smell, taste
6. Special features - extras
7. Safety
8. After sale service
9. Perceptions – indirect evaluation of quality
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Costs of Quality
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Internal failure costs
External failure costs
Appraisal costs
Prevention costs
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5 TQM “Gurus”
1.Shewhart: “grandfather of SPC,” Shewhart cycle
2.Deming: 14 points; “father of quality control,” known
for: appreciation of a system, knowledge of variation,
theory of knowledge, knowledge of psychology
3.Juran: Pareto principle; trilogy or cross-functional
management approach comprised of quality planning,
quality control, and quality improvement
4.Crosby: Quality is Free; “do it right the first time”
5.Feigenbaum: total quality control (systems view)
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6 TQM Programs Elements
1. Top Management Leadership and Commitment
• Mission statement: is quality a corporate objective?
• Leadership: Remember 3 points
a. Definition: “interpersonal influence, exercised in situations and directed through the
communication process, toward the attainment of a specified goal or goals.”
b. Influence = the numerous “leadership theories” and various leadership styles
c. Leadership includes setting the direction the organization through a thorough, longterm vision of the organization’s value-producing processes.
• Long-term commitment to continuous improvement (kaizen)
2. Product design: Manufacturability and conformance to specifications
• Idea: design and build in quality rather than inspect it in; nonconformance is $$$
• Practices: product standardization; simplicity or fewer parts, where for n independent
components, system reliability Rs = (R1)(R2)(Rn); robotics; vertical insertion; redundancies,
where for a system with a back-up, Rs = R1+{R2*(1-R1)}; improved supplier relations;
preventative maintenance
• Cpk: ratio of allowable process variability to actual variability (versus Cp ratio)
3. Process design
• Practices: ISO 9000/TS 16949 (standardized thinking); recognizing value of employees
(education and training programs, participative management, quality circles, “quality at the
source,” Plan-Do-Study-Act ); organizational structure (teams based matrix approach,
fewer management levels, increased span of control); technology and tools; and through
the customer focus (see next slide)
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6 TQM Programs Elements
4. Customer Focus: Internal and External Customers
a. Internal: Engaged employees (an understanding of their importance and a demonstration of
this through practices such as participative management and teamwork)
(1) Quality at the Source (empowered employees)
• Authority is the power granted to individuals so that they can make final decisions
to complete their assignments
• Responsibility is the obligation incurred by individuals in their roles in the formal
organization in order to effectively perform assignments.
• Accountability is the state of being totally answerable for the satisfactory
completion of a specific assignment.
• Accountability = Authority + Responsibility
(2) Employee skills: education, training (tool kits), standardized thinking
(3) Technology and tools
(4) Quality Circles
• A decentralization of management responsibility; a group of 3 to 10 employees
doing related work; meets at regular intervals; objectives of increased productivity
and quality; direct employee involvement; provide for substantial individual
motivation; improve managerial decision-making
b. External customers: consumers, customers, vendors
(1) Quality Function Deployment (QFD)
(2) Conformance to specifications
(3) Engaging suppliers and managing the supply chain quality
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6 TQM Programs Elements
5. After-the-sale service quality: distribution, installation, after-the-sale support
6. Use of Quality Tools; 2 categories
a. Process Improvement Tools: attempt to reduce the causes of variation before it happens
b. Statistical Process Control (SPC) Tools or Techniques: attempt to identify assignable causes
of variation so that it eventually may be eliminated
c. Variation caused by chance causes (random variation) and assignable (attributable)
causes
d. Process Improvement Tool examples
(1) Benchmarking
(2) Brainstorming
(3) Process Mapping (flow charting); example follows
(4) Pareto Analysis and Histograms; example follows
(5) Cause-and-Effect Diagrams (a.k.a., Ishikawa diagram, 4M diagram, fishbone diagram) ;
example follows
(6) Check Sheets (checklists); example follows
(7) Scatter Diagrams ; example follows
e. Statistical Process Control (SPC) Tools or Techniques: 2 subcategories
(1) Control charts: used for higher volume, repetitive processes
(2) Acceptance plans: used for lower volume, batch processes
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Process Improvement Tool: Process Mapping (Flowcharting)
Different shapes represent different types
of process flow tasks, e.g., rectangle
represents a task while triangle represents
assessment.
Diagram to left is an example of an
“engineering” process map.
There is also a “flow” process map that
depicts items in 1 of 5 states during flow:
(1) in process, (2) being moved, (3) being
stored or in inventory, (4) waiting to be
moved, or (5) in inspection.
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Process Improvement Tool: Histogram
• Along the x-axis you find the categories of concern, e.g., repair
times for various failures
• If you read over to the y-axis you find the frequency (or the
probability) of the category occurring
• The idea is to help direct improvement efforts
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Process Improvement Tool: Pareto Chart
• A variant of an histogram
• Categories are arranged
from greatest frequency of
occurrence to least
frequent
• The cumulative frequency
is 1 or 100%
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Process Improvement Tool: Cause and Effect Diagram
• Also called Ishikawa diagram, 4M diagram, and fishbone diagram
• Process: work back from the effect to attempt to identify the cause
• Common to find more than 4 categories; e.g., 5th M may be “metrics”; 6th
M may be “mother nature”
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Process Improvement Tool: Check sheet
• You’re keeping a running tally of the issue or defect type, typically by date,
time, and location, so that the frequencies can be ultimately determined
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Process Improvement Tool: Scatter Diagram
• Diagram makes relationships (correlation) clearer
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SPC Tool: Control Charts
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A graphical tool for describing the state of control of a process
Basic control charts consists of UCL, LCL and centerline (process mean)
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X-axis is time while the Y-axis is generally the mean of the quality characteristic being measured
It is used to monitor the output of high volume (repetitive) production processes
Sample values are used to monitor process performance
It’s a confidence interval designed to achieve desired level of producer (type I error) and consumer
risk (type II error)
Construction varies with data type Variable (continuous) or Attribute (0-1)
Variable Data: Means chart and Range chart
Attribute Data: P-chart, nP-chart, c-chart and u-chart
Because it’s a confidence interval, the UCL and LCL are typically process mean + some number of
standard deviations (z-scores).
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Statistical Process Control (SPC) Techniques
• Remember: The underlying principle of the quality
management process is to produce products of high quality in
the first place, rather than depend on detecting defective
products later through inspection.
• Note: A process is in statistical control if the variation in the
process is due to common causes (random causes) alone.
When special causes (assignable causes) are present, the
process is deemed to be out of control.
• Process Control attempts to identify assignable causes of
variation so that it eventually may be eliminated. Control
charts and acceptance plans are used for this purpose.
• The limits of SPC Control charts are determined from the
output of the production process itself.
• SPC depends upon sampling.
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Sampling
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The timing, location and amount of sampling is governed by the cost of
sampling versus the expected cost of passing on defective items.
Strategic locations of sampling?
The costs of undetected defects and sampling are inversely related.
Two data types
a. Variable (continuous)
b. Attribute (0-1)
Type I and Type II Errors - sampling leads to incorrect decisions
a. Type I Error - a decision that the production process is out of control
when in reality it is in control (producer’s risk). Cost of a Type I error: lost
production time, cost of testing for an absent (ghost) problem
b. Type II Error - a decision that the production process is in control when in
reality it is out of control (consumer’s risk). Cost of a Type II error: scrap,
rework, after-the-sale service costs (difficult to measure)
Controlling for Type I and II Errors
a. Increase amount of inspection – frequency or sample size
b. Reduce size of control limits
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2 Causes of Variation
• Random versus Assignable Variation
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Interpretation and Use of Control Charts
1.Observations should fall within the limits
2.Data points should not reflect any trends
3.Low degree of variability should be observed in the
data points
4.No evidence of “runs” in the data
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Control Charts for Variable (Continuous) Data
• Means Chart: used to monitor the average value of the
variable being measured
a. Center line, x (mean of sample means)
b. UCL = x + Z(x)
where, x = /n and it is the
standard deviation of the distribution of sample means
c. LCL = x - Z(x)
d. Alternatively: UCL = x + A2(R) and LCL = x - A2(R)
• Range Chart: measures variability within a sample
a. Center line, R
b. UCL = D4R
c. LCL = D3R
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Control Charts for Attribute (0-1) Data
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Control chart for proportion (fraction) defective, 1 defect per unit of output, p-Chart
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Center line is process mean, p
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b. UCL and LCL = p + Z  p(1-p)/n
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(where n is sample size)
Control chart for number defective, 1 defect per unit of output, np-Chart
a. Center line is process mean, np
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b. UCL and LCL = np + Z  np(1-p)
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Control chart for total number of defects in a sample, multiple defects per unit of output, c-Chart
a. Center line is process mean, c
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b. UCL and LCL = c + Z√c
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Control chart for the avg number of defects in a sample, multiple defects per unit of output, u-Chart
a. Center line is process mean, u
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b. UCL and LCL = u + Z√u/N
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(where u is x/n and x is number of defects in sample)
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Control Chart Construction Guidelines
• If cost of investigating cause of “out-of-control” decision is high, a
Type I error is important and should be avoided. Use wider control
limits.
• If cost of passing on defectives is high, Type II error is important and
should be avoided. Use narrower limits.
• If costs of Type I and Type II errors are high, wide control limits
should be used and consideration should be given to increasing
sample size and increasing frequency of taking samples.
• Based upon actual experience, if out-of-control conditions arise
frequently, narrower control limits should be favored.
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Acceptance Sampling
• Acceptance Sampling: process of randomly inspecting a certain number of items
(sample size of n) from a batch of items (N) to determine acceptance/rejection of
the lot based upon observed number of defects versus acceptance/rejection
criteria.
1. Sampling Plans: identify N, n, accept/reject criteria, single, double, multiplesampling
2. Operating Characteristic Curve: demonstrates the discriminating power of the
sampling plan; x-axis is proportion of defective items in lot, y-axis is probability
of lot acceptance
3. Acceptable Quality Level (AQL): the percentage of defects consumers are willing
to accept
4. Lot Tolerance Percent Defective (LTPD): threshold (maximum) level of defective
items consumers tolerate
5. Average Outgoing Quality (AOQ): assuming all lots have same proportion
defective (p), the overall average outgoing quality where Pac is probability of
acceptance is:
AOQ = (Pac)p(N-n/N)
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