Work measurement ppt @ bec doms
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Work measurement ppt @ bec doms
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Work measurement ppt @ bec doms
- 14. Time Studies - Sample Size h = accuracy level desired as percent of job element, expressed as a decimal (5% = 0.05) z = number of standard deviations required for the desired level of confidence s = standard deviation of the initial sample x = mean of the initial sample
- 16. Common z values Desired Confidence Level (%) Z Value 90.11 1.65 95.00 1.96 95.45 2.00 99.11 2.58 99.73 3.00 99.0
- 17. Time Study Equations Allowance factor Nonwork time Total time Average element time Element times Number of cycles Normal time Average element time * Perf. Rating Standard time Total normal time 1 - Allowance factor = = = =
- 19. MTM Table for Reach Motion Time TMU Hand in Motion Distance Moved (in) A B C A B 3/4 or less 2.0 2.0 2.0 1.6 1.6 1 2.5 2.5 3.6 2.3 2.3 2 4.0 4.0 5.9 3.5 2.7 A Reach to object in fixed location. B Reach to object in variable locations. C Reach to object jumbled with others. 1 TMU = .0006 minutes
- 20. Sample MTM Table for GET and PLACE Motions
- 21. MTM-HC Analysis: Pouring Tube Specimen Element Description Element Time Get tube from rack AA2 35 Get stopper, place on counter AA2 35 Get centrifuge tube, place at sample tube AD2 45 Pour (3 sec.) PT 83 Place tubes in rack (simo) PC2 40 0.0006*238=Total standard minutes = 0.14 Total TMU 238
- 25. Work Sampling - Sample Size p = estimated value of sample proportion (of time worker is observed busy or idle) h = accuracy level desired in percent, expressed as a decimal
- 26. Work Sampling Equations Normal Time = (Total Time) (% of time working) (Rating) Number of units Produced Standard Time = Normal Time 1 - Allowance
- 27. Work Sampling Time Studies
Editor's Notes
- You might note here that labor standards are of use both before production (planning, bidding, etc.) and during producing (wage-incentive, determining efficiency, etc.)
- Most of these methodologies rely on the job actually being performed..
- Here it may be helpful to discuss why something, which often looks to students to be so simple, is really not. What problems does one encounter in doing a time study? Why factors make it more complex than it appears?
- It is sometimes helpful to actually walk students through a time study in the classroom. The task does not have to be complex - perhaps as simple as sharpening a pencil. Ask them to consider sources of variance as the task is performed on different pencils by different people. Students should also be asked how one determines the appropriate adjustments for unusual influences.
- At this point in the process, students should be asked to determine the appropriate waiting factor and allowances. How does one determine the rating factor for a particular worker? What allowances are appropriate in a given situation, and how long should they be?
- Some thoughts on allowances.
- The need for calculation of the appropriate sample size was probably covered earlier. If not, one should at least introduce the equation and its use.
- Explain to students that sample size is computable.
- If you have actually conducted a time study in the classroom, you should demonstrate the use of these equations.
- A useful exercise in applying predetermined time standards can be to have teams of three or four students each develop the time standard for a particular task as a homework assignment. Have them bring the completed standards to the next class and discuss the results.
- Discussion of this methodology should emphasize its use in service organizations.
- It would be helpful at this point to note the use of Work Sampling as a diagnostic tool.
- One point to bring out here is that observations should be conducted at random intervals. Students could be asked to conduct a study of one of their classmates or a worker in the college or university community. One issue this might raise is that of the impact of the observer on the worker being observed.
- The issue to be raised here is that this calculation gives an estimate of sample size. If the sample proportion turns out to differ significantly from the estimate, the sample size must be recalculated.