provides the ability to automatically derive labor standards based on the historical data of tasks or activities performed by warehouse users over a period of time. Labor standards are derived based on the following algorithm:
You can collect these metrics for a user for various samples as illustrated in the following table.
Sample | time | numTasks | distance | numLocs | Weight | creditedTime |
---|---|---|---|---|---|---|
User A - Sample 1 | T1 | N1 | D1 | NL1 | W1 | C1 |
User A - Sample 2 | T2 | N2 | D2 | NL2 | W2 | C2 |
User A - Sample 3 | T3 | N3 | D3 | NL3 | W3 | C3 |
Assuming that the labor standards for a user are constant over a period of time, the user is given full credit at the start time. Therefore, credited time for the user is the same as the time taken by the user to complete the task.
C1 = SN.N1 + SD.D1 + SNL.NL1 + SW.W1
C2 = SN.N2 + SD.D2 + SNL.NL2 + SW.W2
C3 = SN.N3 + SD.D3 + SNL.NL3 + SW.W3
where:
SN = Allowed minutes per task
SD = Allowed minutes per unit distance
SNL = Allowed minutes per location
SW = Allowed minutes per unit weight
C1 = Credited time for the first sample
C2 = Credited time for the second sample
C3 = Credited time for the third sample
The linear system of equations above is solved for
SN, SD, SNL, and SW in
such a way that the error (Ti – Ci)2 is minimum.
Labor standards are derived by setting standards for given set of users. When deriving labor standards, you can set a user to be X % efficient based on the data collated for a user. In this case, the credited time for each sample is equal to (X/100) *T, where 'T' is the actual time taken to complete a task.