1. Chapter 30: Standard Data
Reusing previously determined times to predict standard times for new operations.
E.g., predict cost of automotive repairs
Can be specialized for a particular industry, company, or process …
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2. Advantages of Using Standard Data
Cost
Time study is expensive.
Standard data allows you to use a table or an equation.
Ahead of Production
The operation does not have to be observed.
Allows estimates to be made for bids, method decisions, and scheduling.
Consistency
Values come from a bigger database.
Random errors tend to cancel over many studies.
Consistency is more important than accuracy.
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3. Random and Constant Errors
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4. Disadvantages of Standard Data
Imagining the Task
The analyst must be very familiar with the task.
Analysts may forget rarely done elements.
Database Cost
Developing the database costs money.
There are training and maintenance costs.
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5. Motions vs. Elements Decision is about level of detail.
MTM times are at motion level.
An element system has a collection of individual motions.
Elements can come from an analysis, time studies, curve fitting, or a combination.
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6. Constant vs. Variable
Each element can be considered either constant or variable.
Constant elements either occur or don’t occur.
Constant elements tend to have large random error.
Variable elements depend on specifics of the situation.
Variable elements have smaller random error.
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7. Developing the Standard
Plan the work.
Classify the data.
Group the elements.
Analyze the job.
Develop the standard.
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8. Curve Fitting To analyze experimental data: Plot the data.
Guess several approximate curve shapes.
Use a computer to determine the constants for the shapes.
Select which equation you want to use.
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9. Statistical Concepts Least-squares equation Standard error
Coefficient of variation
Coefficient of determination
Coefficient of correlation
Residual
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10. Curve Shapes Y independent of X Y = A
Determine that Y is independent of X by looking at the SE.
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11. Y Independent of X
If Y is not related to X (is independent of X), then Y=A, where A is constant. 10 8 6 4 2
[x]
[y]
y=4
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12. Curve Shapes Y depends on X, 1 variable Y = A + BX Y = AXB Y = AeBX
Y = A + BXn
Y = X / (A + BX)
Y = A + BX + CX2
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13. Straight Lines
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14. Geometric Curves
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15. Exponential Curves
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16. Hyperbolas
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17. Parabolas or Hyperbolas with a Third Constant
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18. Curve Shapes Y depends on X, multiple variables Y = A + BX + CZ
Results in a family of curves
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19. Example Application: Walk Normal Times (min)
.0553
.1105
.1654
.2205
.0590
.1170
.1751
.0550
.1660
.2090
.0521
.1045
.1680
.2200
.0541
.1080
.1625
.2080
.0595
.1200
.1800
.1980
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20. First, plot the data
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21. Equations for Walking NOTE: see attached Excel sheet
intercept = ______ slope = _________
r2 = _______ σ = __________
Therefore, Walk time is computed as:
t = __________________
So, if a new task is added that requires walking 7.4 m, how long should be allowed in the standard?
r2 = .986 σ = .0073
t = d
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22. Equations for Walk Data Set
Walk time h = – (loge Distance, m)
r2 = .966 σ = .012 h
1/Walk time h = .24 – .96 (1/Distance, m)
r2 = .881 σ = .021 h-1
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