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Service Ops > Prelim 1 – Module 3 > Flashcards

Prelim 1 – Module 3 Flashcards

1
Q

Dimensions of Service Quality (5)

A
  1. Reliability: Perform promised service dependably and accurately (no defects!)
  2. Responsiveness: Willingness to help customers promptly
  3. Assurance: Ability to convey trust and confidence, e.g., being polite and showing respect for customer
  4. Empathy: Ability to be approachable, e.g., being a good listener
  5. Tangibles: Physical facilities and facilitating goods, e.g., cleanliness
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2
Q

What factors into expected service vs. perceived service?

A
  1. Word of mouth
  2. Personal needs
  3. Past experience
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3
Q

Service Quality Assessment

A
  1. Expectations exceed ES<PS (quality surprise)
  2. Expectations met ES ~ PS (satisfactory quality)
  3. Expectations not met ES>PS (unacceptable quality)
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4
Q

Service quality gap model

A

Gap 1: market research
Gap 2: design
Gap 3: conformance
Gap 4: communication
Gap 5: customer satisfaction

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5
Q

Lean service philosophy

A
  1. Satisfy the needs of the customer by performing only those activities that ADD VALUE in the eyes of the customer.
  2. Define the “VALUE STREAM” by flowcharting the process to identify both value-added and non-value-added activities. Scope out opportunities for improvement into Kaizen bursts, or small projects to make small incremental changes.
  3. Eliminate the waste. Waste in the value stream is any activity for which the customer is not willing to pay.
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6
Q

Lean ideas and illustrations

A
  • continuous flow
  • gemba walks (“real place”)
  • 5S to organize work area
  • automation
  • kanban (pull not push)
  • kaizen (continuous improvement)
  • poka-yoke (“error proof”)
  • value stream mapping
  • standardization
  • looking for mudas in services
  • visual factory
  • plan-do-check-act
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7
Q

Dig Inn

A
  • never put the bowl down: continuous flow; kanban
  • a manager going through employee training: gemba walk
  • designing scoops to automatically portion: poka-yoke; standardization
  • test squad: plan-do-check-act; kaizen
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8
Q

Lean’s 7 wastes

A
  1. transport
  2. inventory
  3. movement/motion
  4. waiting
  5. overproduction
  6. overprocessing
  7. defects
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9
Q

Transport waste

A

Moving inventory, people, or tools farther than necessary

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10
Q

Inventory waste

A

Storing products not needed at this time

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11
Q

Movement/motion waste

A

Unnecessary movement of people or items within a work centre

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12
Q

Waiting waste

A

When customers, patients, or parties sit idle

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13
Q

Overproduction waste

A

Producing more of a product than can be consumed at that time

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14
Q

Overprocessing waste

A

Doing more work than the customer values

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15
Q

Defects waste

A

Doing something of poor quality and then later fixing or scrapping

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16
Q

Example of waste: agents walk down jet bridge to confirm aircraft ready to board

A

Waiting, transportation

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17
Q

Example of waste: agents put “approved” takes on carry-ons

A

Overprocessing

18
Q

Example of waste: using the same aircraft-turnover process for on-time and delayed flights

A

Overprocessing, waiting

19
Q

Example of waste: flight attendants count passengers

A

Waiting, overprocessing

20
Q

Key detail of value stream map and efficiency formula

A

Value-added time and non-value added time
Efficiency = value added time/throughput time

21
Q

What is six sigma (6σ)?

A
  1. define
  2. measure
  3. analyze
  4. improve
  5. control
22
Q

Normal distribution: below x, above x, out of specifications

A

Below: norm.dist
Above: 1-norm.dist
Out of specification: the above added together

23
Q

Why is six sigma associated with 3.4 defects per million opportunities?

A

Consider a process with a mean μ, standard deviation σ, and lower/upper specification limits.
In stable processes, the mean naturally shifts by up to 1.5σ (let’s say μ=1.5σ)

24
Q

When mean is centred between specification limits

A

𝐶𝑝=(𝑈𝑆𝐿−𝐿𝑆𝐿)/6𝜎 𝐶𝑝=(+15−(−15))/(6(2.5))=2.0
𝐶𝑝 ≥ 2.0 is acceptable level of process capability for Six Sigma standards

25
Q

When mean μ is not centred between specification limits

A

𝐶𝑝𝑘=𝑚𝑖𝑛[(𝑈𝑆𝐿−𝜇)/3𝜎,(𝜇−𝐿𝑆𝐿)/3𝜎] 𝐶𝑝𝑘=𝑚𝑖𝑛[(15−1)/(3(2.5)),(1−(−15))/(3(2.5))]=𝑚𝑖𝑛[1.87,2.13]=1.87
𝐶𝑝𝑘≥2.0 will be more difficult to achieve

26
Q

Six sigma tools: defining goals

A

SMART: specific, measurable, action-oriented, reasonable, timely

27
Q

Six sigma tools: determining the cause of the problem

A

Flow charts, pareto diagrams, fishbone diagrams, the five whys, check sheets

28
Q

Six sigma tools: controlling the quality

A

Run charts, quality control charts, kanban, 5S, pokayoke

29
Q

5S technique

A
  1. sort
  2. set in order
  3. shine
  4. standardize
  5. sustain
30
Q

Sort

A

Eliminate obstacles and unnecessary items

31
Q

Set In Order

A

Arrange items for convenience, clarity, and smooth workflow

32
Q

Shine

A

Keep clean and safe; make problems easy to detect

33
Q

Standardize

A

Standardize best practices; make easy to find things

34
Q

Sustain

A

Ensure clarity of standards; audit; promote training and discipline

35
Q

Poka-yoke: can you ensure perfect quality?

A

Mistake proofing, inadvertent error prevention, idiot-proofing

36
Q

How can you poka-yoke a spreadsheet?

A
  1. drop-down boxes
  2. locking cells
  3. hiding worksheets
  4. setting the print area
  5. conditional formatting
37
Q

Control Charts (we study three types: 𝑋̅-chart, R-chart, p-chart)

A
  • Plot average values of a performance measure over time to determine if a process is in control
  • Conceptually similar to confidence intervals
  • Established using representative historical data
38
Q

Take action if

A
  • sample mean outside control limits
  • run of seven means above/below mean
39
Q

How do you determine the control limits? (R-charts)

A

R-charts depict the range (highest minus lowest observation)
Often used prior to 𝑋̅-chart in order to first see that variability is in control
Need to know sample size (n)
-> if range values are between UCL and LCL, our process is in control

40
Q

If observation is above UCL or lower than LCL

A

Take action

41
Q

What if the error measured is a frequency/percentage?

A

Use a p-chart
𝒑̅=𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒 𝑜𝑓 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑝𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒 (𝑤𝑒𝑖𝑔ℎ𝑡𝑒𝑑 𝑎𝑣𝑒𝑟𝑎𝑔𝑒)

Service Ops (8 decks)

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