The classical approach to time studies was developed by Frederick W. Taylor in 1911, and is the accepted procedure for production analysis. A time study, also termed a stopwatch time study, is an analysis of a worker`s performance against a time standard. Time studies are normally performed on short repetitive production types of tasks.
How is a time study performed?
There are several basic steps which must be followed in any time study:
1. Define the job to be analyzed.
2. Break the job into discrete tasks.
3. Measure the actual time required for each task.
4. Develop a statistically significant sample size of the task work cycles to be measured. Work measurement depends on sampling the work process. However, in order to counter inherent variability in the work samples, a sufficient representation of the sample universe must be selected. Therefore, it is essential to determine an adequate work cycle sample size. In order to do this, a preliminary analysis must be performed usually consisting of anywhere from 5 to 20 repetitive work cycles in order to determine variability.
The work sample size is dependent on three factors:
a. Observed variance in the work cycles.
b. How closely the sample will conform to the average work cycle (accuracy).
c. The desired statistical level of confidence.
The work cycle element having the greatest variability will determine the sample size needed to obtain an acceptable statistical level of confidence.
The typical statistical level of confidence expected is 95% with a reliability of t =5%. The following formula will determine required sample sizes:
N = (nZ2 [nΣX2 - (ΣX)2]) / ((n - 1)a2 (ΣX)2)
n = initial sample size
X = cycle time
a = accuracy
Z = confidence level (Z = 1 for 68.3% confidence level, Z = 2 for 95.5% confidence level, and Z = 3 for 99.7% confidence level)
5. Calculate the average time required for each job element using the following formula:
Average job element time = Sum of the time needed to perform each task / Number of job cycles
6. Rate the performance of each worker (performance rating).
7. Calculate the normal time required for each job element using the following formula:
Normal time = (average element time) x (Performance rating / 100)
The normal time for a particular employee is rated against the average job element time.
8. Determine allowances that may be permitted for a particular job task. This may take into consideration personal factors as well as unavoidable constraints encountered in the work situation. Allowances include all unavoidable delays, but rule out avoidable delays. An allowance factor represents time lost due to personal factors, shift adjustments, improper equipment, fatigue, and related issues. The performance rating is adjusted for any allowances.
9. Calculate the standard time. When calculating the standard time, three different types of time are actually utilized. Actual time is the time a particular employee actually takes to perform a particular job operation. Normal time is the time needed to complete an operation by an employee working at 100% efficiency having no delays. Standard time is the time needed to complete an operation by an employee working at 100% efficiency with unavoidable delays:
Standard time = normal time + allowance time
Standard time = normal time / (1 - allowance fraction)
A work operation consisting of three procedures is observed using a stopwatch time procedure. The allowance for the work operation is 15% of mean time. It is necessary to determine the standard time for the operation and what the standard should be in hours per 1,500 units. The observed data are contained in Table 1.1:
TABLE 1.1 STOPWATCH TIME STUDY
The standard time is 28.94 seconds/unit and the standard for 1500 units is 12.06 hr.
A manager wants to determine the required sample size for three different work cycle elements after having performed 12 sample observations. The manager is seeking a 95.5% statistical confidence level with an accuracy of ± 5%. Refer to Exhibit 1.6.
EXHIBIT 1.6 REQUIRED SAMPLE SIZE AT .005 LEVEL OF CONFIDENCE
N = (nZ2 [nΣX2 - Σ (X)2]) / ((n - 1 )a2 Σ (X)2) = (12(4)[ 12(850) - 10,000]) / (11(.0025) 10,000) = 34.91
N = (12(4)[12(2,732) - 32,400]) / (11(.0025) 32,400) = 20.69
N = (12(4)[12(748) - 8,836]) / (11(.0025) 8,836) = 27.66
Element I has the largest required sample size of 35. Therefore, the manager needs to make another 23 sample observations to complete the total sample size of 35.