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Work Sampling. INSY 3021 Auburn University Spring 2007. Work Sampling. A technique that discovers the proportions of total time that various activities contribute to the job by taking a relatively large # of observations at random intervals

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work sampling

Work Sampling

INSY 3021

Auburn University

Spring 2007

work sampling1
Work Sampling
  • A technique that discovers the proportions of total time that various activities contribute to the job by taking a relatively large # of observations at random intervals
  • Used to determine: production standards, machine and personnel utilization, and job allowances. Typically faster and cheaper than other techniques
  • Well suited for high cycle time and low repetition rate jobs & service industry
  • Does not require the analyst to continually observe the job
  • Reduced clerical time
  • A smaller # of hours are required to collect the data
  • Operator not subjected to long periods of observations
advantages con t
Advantages (con’t)
  • Single analyst can study a small crew (or # of subjects); GTT (Maynard Handbook)
  • Cost of the study may be cheaper (up to a certain # of samples)
  • Conducted over a long period of time (tends to be more objective)
  • Study can be postponed if something more urgent arises (no change in study criteria)
  • Will not produce as good a standard as direct time study
  • Cost maybe higher than suspected if sampling rates are frequent
  • Subjects need to be located close together to eliminate travel
  • Doesn’t provide the detailed data (C/I ideas) that direct study does
  • Theory of why it works is confusing for some people
little bit of theory
Little bit of theory
  • Based on an event being present or not.
  • Probability of x occurrences of an event in n observations: (p + q)n = 1
  • Expand IAW binomial theorem, with the 1st term giving the probability of x=0, the 2nd term x=1, etc…
  • This distribution of probabilities is known as the binomial distribution, with the Mean = np, and Variance = npq.
  • As n becomes large, the binomial distribution approaches the normal distribution
  • We’ll return to this later…
sample size
Sample Size
  • There are many sources of tabulated data for determining the # of samples required at various confidence levels and accuracy’s.
  • Formula for calculation purposes simplifies to: n = Z2(1-P)/(P)(A2)
study plans protocol
Study Plans (Protocol)
  • Start with preliminary estimate of the variable. This can be historical data, conducting pilot study, or an educated guess (least desirable)
  • Determine the desired accuracy of the results
  • What level of confidence do you desire
  • Estimate the # of observations
  • Develop a sampling schedule
  • Design the data collection form
determining randomness
Determining Randomness
  • Random number tables (text pg. 697)
  • Random number generators
    • C++ Program
    • Websites
  • Random Reminder
work sampling form instrument
Work Sampling Form (Instrument)
  • Forms should be custom designed to accommodate the specific data of interest to your study. Make the spaces large enough to easily record the data. Provide summary and calculations spaces right on the form.
  • Commercial software available for this application
  • Locate yourself at the same place each time prior to observing the operation
  • Try to intentionally distract yourself from the variable of observation as you approach the site (think safety)
  • Limit your time at the site to that actually needed for the observation
technique con t
Technique (con’t)
  • Try to record only the minimum data that you will need to successfully reconstruct the observation
  • Verify any discrepancy with the supervisor or foreman
  • Make notes on the form after the operator can no longer see you
  • Keep a pleasant attitude
computerized work sampling
Computerized Work Sampling
  • Computer and PDA programs
    • Quetech Ltd, TimerPalm, UMT-Palm
  • Advantages
    • IE time increased by a reduction in clerical time, results realized faster
    • More professional appearing report
    • $ of performing studies is cheaper
    • Improved accuracy
    • Reduced errors by analysts
    • Greater use made of work sampling, because it is less painful
  • “Sell” the work sampling method before using it
  • Use as large of a sample size as is practical
  • Take individual observations at random times, balance the study if necessary
  • Take the observations over two weeks or more