Exam 2 Flashcards
Prevention cost
Cost associated with preventing defects before they happen
Appraisal cost
Costs incurred when the firm assesses the performance level of its processes
Internal failure costs
Costs resulting from defects that are discovered during the production of a service or product
External failure costs
Costs that arise when a defect is discovered after the customer recieves the service or product
Six sigma
Process on target with low variability
Process average ok with too much variation
Reduce spread
Process variability ok with process off target
Center process
Statistical process control: common cause
The purely random unidentifiable sources of variation that are unavoidable with the current process
Statistical process control: assignable cause
Any variation causing factors that can be identified and eliminated
Control charts
Two control limits, upper and lower, with an average for certain processes. What you make needs to be within the two limits
Control charts: run
Variation keeps getting lower, take action
Control charts: sudden change
Monitor
Control charts: exceeds control limits
Below or above control limits, take action
Type 1 error
An error that occurs when the employee concludes that the process is out of control based on a sample result that falls outside the control limits, when in fact it was due to pure randomness
Type 2 error
An error that 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
Process capability
The ability of the process to medt the deisgn soecification for a service or product
Nominal value
A target for design specifications
Tolerance
An allowance above or below the nominal value
Short range forcast
Up to a year. Purchasing, job scheduling, workforce levels, job assignments, production levels
Medium range forcast
3 months-3 years, sales and production planning, budgeting
Long range forecast
3+ years. New product planning, facility location, research and development
Forecasting approaches: qualitative methods
Used when situation is vague and little data exist (new products/technology) involves intutuion and experience (forecasting sales on internet)
Forecasting approaches: quanitative methods
Used when situation is stable and historical data exisit(existing products and current tech). Involves math
Quantitative approaches
Naive approach, moving average, expinential smoothing, trend projection, linear regression
Time series components
Trend, cyclical, seasonal, random
Exponential smoothing
Form of weighted moving average (most recent data weighted most) requires smoothing constant, involves record keeping of past data
Smoothing constant
ranges from 0-1 and subjectivly chosen
Effects of smoothing constants
Generally between .05-.50 and as alpha increases the older values become less significant
Trend
Gradual upward or downward movement of the data over time
Seasonality
Is a data patten that repeats itself after a period of days weeks months or quarters
Cylces
Are patterns in data that occur every several years
Random
Are blips in data caused by chance and unusual situations
Naive approach
Assumes demand in next period is the same as demand in most recent period
Moving averages
Uses an average of the n most recent periods of data to forecast the next period
Total quality management
A philosophy that stresses three principals for acheiving high levels of process performance and qaility: customer satisfaction, employee involvement, and continuous improvement in performance
Deckers video
Forecasting. Uses historical data. Bottom up-planning each individuallu
Carryover item-use past for future
Tops down-item by category to adjust dollars to each
