Vi Vii 2498 0

V 2498

Best of best (target) OEE calculation

The best of best calculation uses the best scores in the period from each column. This gives us a theoretical achievable performance if all of these best scores were consistently achieved. It is our first target for improvement.

Best of best OEE = 1.000 x 0.877 x 1.000 x 100 = 87.7%

Question What is stopping us achieving the best of best consistently? Answer We are not in control of the six big losses!

The best of best calculation generates a high confidence level, as each value used of the three elements (availability, performance, quality) was achieved at least once during the measurement period. Therefore, if control of the six big losses can be achieved, our OEE will be at least the best of best level. We can now start putting a value to achieving the best of best performance.

TPM potential savings for achieving best of best

Cycle time A = 30s Number of men B = 2 Allowance in standard hours

(lunch breaks, technical allowance, etc.) C = 11%

Credit hours generated per piece v _ (A x B) + C _ (30 x 2) + 11% _nMoe X" 3600s " 3600s "0 0185

Variable cost per credit hour Y = £27.50 Direct labour cost per price X x Y = £0.5106 Current OEE D = 63.1% Number of pieces produced E = 2498 Best of best OEE F = 87.7%

Number of pieces produced at OEE = 87.7% G = ^xE = 3472

Difference in pieces produced G - E = 974 Potential weekly savings = £0.5106 x 974 = £497 Potential annual savings (45 working weeks) = £22 365

An alternative to increasing the output potential of 974 pieces per week at best of best is to achieve the same output of 2498 pieces in less time:

Loading time (total available time) was 1980 minutes (33 hours) to produce 2498 pieces at OEE of 63.1 per cent.

Loading time to produce 2498 pieces at best of best OEE of 87.7 per cent would be:

Time saving = 1980 - 1425 = 555 minutes = 9.25 hours Simple OEE calculation

If the foregoing 'live' example seemed a little complicated, let us take the following very simple example to illustrate the principles.

Data

• Loading time = 100 hours, unplanned downtime = 10 hours

• During remaining run time of 90 hours, output planned to be 1000 units. We actually processed 900 units

• Of these 900 units processed, only 800 were good or right first time

Interpretation

Availability: actual 90 hours out of expected 100 hours

Performance: actual 900 units out of expected 1000 units in the 90 hours

Quality: actual 800 units out of expected 900 units

Calculations

Planned run time a = 100 hours Actual run time b = 90 hours

(owing to breakdowns, set-ups)

Expected output in actual run time c = 1000 units in the 90 hours

• die changes averaging 4 hours each per set-up and changeover

• 15 500 units produced, plus 80 units scrapped, plus 150 units requiring

• Allowed time as planned and issued by production control for the five jobs was 52 hours, including 15 hours for set-up and changeover

Loading time = attendance - tea breaks = 120 - 6 = 114 hours Downtime = breakdowns + set-ups and changeovers

Actual press running time (uptime) = 120 - 6 - 43 - 20 = 51 hours

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