Manufacturing performance: OEE, takt time and the six big losses

Cue 1 Three bars for availability, performance and quality, then the multiplied result

AMARA 00:00 Every plant quotes an OEE. Why do you distrust the number?

NADIA 00:04 Because the formula is trivial and the definitions are not. Three fractions multiplied together. Anyone can do the arithmetic. What decides the answer is what you put in loading time, and that is a judgement somebody made once and rarely wrote down.

AMARA 00:21 Start with the arithmetic anyway.

NADIA 00:23 Availability, performance, quality, multiplied. Ninety per cent on each looks respectable and gives you seventy three. That multiplication is why plants that feel busy find a quarter of their intended production time produced nothing they could sell.

AMARA 00:38 Loading time. What is the argument?

NADIA 00:40 What did you intend to run. Nobody counts Christmas Day. After that it is contested. Planned maintenance, changeovers, trials, a shift with no orders. Argue any of those out of loading time and the number rises without one thing changing on the floor.

AMARA 00:57 So which convention is right?

NADIA 00:59 Either. Neither is wrong. Excluding planned maintenance answers how well the equipment ran while you meant it to run. Including it answers how much of the calendar became product. Pick one, write it down, and never move it because a month looks poor.

Cue 2 A timeline of a shift, colour coded into loading time, run time and each loss

AMARA 01:16 How often does that happen?

NADIA 01:18 Often enough that it is the first thing to check when OEE improves sharply with no corresponding change in output. If the tonnage did not move and the number did, somebody edited a definition.

AMARA 01:32 Performance. You called two of its losses invisible.

NADIA 01:35 Reduced speed and small stops. Reduced speed is a line running below its demonstrated best because it jams at full rate, and that decision is usually so old that nobody remembers taking it. Small stops are the ten second clearances.

AMARA 01:51 Ten seconds. Does that matter?

NADIA 01:53 Two hundred times a shift it matters enormously. It is frequently the largest single loss in the plant, and it is almost never in the downtime log, because filling in the log takes longer than the stop took. That is not laziness. It is a measurement system asking for something impossible.

AMARA 02:14 How do you catch them, then?

NADIA 02:16 You stop relying on people to type them. Count from the line itself. Any gap between units beyond the cycle time is a stop, whether or not anyone declared it. The machine is a more reliable witness than a clipboard at the end of a twelve hour shift.

Cue 3 The six big losses table with each loss animating into its factor

AMARA 02:35 Ideal cycle time. People set that generously.

NADIA 02:38 Constantly, and it destroys the factor. If ideal cycle time is the rate you usually achieve, performance is ninety eight per cent by construction and tells you nothing. It has to be the demonstrated best the equipment has ever sustained.

AMARA 02:54 Quality. Where does that one go wrong?

NADIA 02:57 Rework. Quality means right first time. A unit that went to a rework bench and came back consumed capacity twice, and the whole point of the factor is to make that visible.

AMARA 03:10 But it sold in the end.

NADIA 03:12 It did, and the plant paid twice for it. Where rework rejoins the good count you get quality above ninety nine per cent in a plant that is running a permanent rework cell. The number is denying the existence of a room you can walk into.

AMARA 03:30 The six big losses. Are they more than a poster?

NADIA 03:34 They are useful for one specific reason. Each loss lands in exactly one factor. So an improvement makes a falsifiable claim: fix changeover and availability must move. If you cut changeover time in half and availability is unchanged, the saving went somewhere else and you should find out where before you celebrate.

Cue 4 Two failure timelines side by side: frequent and quick against rare and slow

AMARA 03:55 Give me an example of that going wrong.

NADIA 03:58 A team halves changeover and availability does not move, because the line now sits idle waiting for materials that were never the constraint before. The improvement was real. The benefit was absorbed by the next problem, which is normal and worth knowing.

AMARA 04:15 Mean time between failures and mean time to repair. Why both?

NADIA 04:20 Because they are different diseases with the same symptom. Both dent availability. A short time between failures with a fast repair means the machine fails constantly and your team has become superb at fixing it. That is not a compliment, it is a warning.

AMARA 04:37 And the reverse?

NADIA 04:38 Long time between failures, slow repair. Rare events, no spare on the shelf, nobody on shift who has done the job before. Completely different project. One is engineering out a fault, the other is stores and training.

AMARA 04:53 If somebody has one hour a week, where do they spend it?

NADIA 04:58 On the downtime Pareto, and on making the counting automatic. Most plants improve fastest not by fixing anything but by finding out what is actually stopping them, because the thing everyone assumes is the problem is usually third on the list.

Cue 1 A demand clock ticking down against a line producing, showing takt met and missed

AMARA 05:14 Takt time. Give me the definition without the jargon.

NADIA 05:18 Available time divided by demand. Four hundred and fifty minutes of real production time, nine hundred units wanted, takt is thirty seconds. One unit off the end every thirty seconds.

AMARA 05:30 And that is different from cycle time how?

NADIA 05:33 Cycle time is what the line does. Takt is what the customer needs. Takt is the only rate in the building that comes from outside the building. Everything worth knowing here is in the comparison between the two.

AMARA 05:48 Say the line is faster than takt. That is good news.

NADIA 05:53 It is the case that needs the most discipline. The instinct is to keep running, and running ahead of demand turns cash into stock. It takes space, it ages, and worst of all it hides problems. A line at takt shows you a fault within one cycle. A line building a mountain shows you nothing for three days.

AMARA 06:16 So you deliberately slow down.

NADIA 06:18 You run to takt and you use the freed time for something else. Maintenance, training, a changeover done properly rather than at a sprint. That is a management decision people find genuinely difficult, because a stationary machine looks like waste and a warehouse full of unsold stock looks like achievement.

Cue 2 A five station line with work in progress stacking in front of the slowest station

AMARA 06:38 And when the line is slower than takt?

NADIA 06:41 Then you cannot meet demand as configured, and overtime is a postponement rather than an answer. You go to the constraint.

AMARA 06:50 Define the constraint.

NADIA 06:51 The slowest station in the chain. It sets the output of the whole line, and it is the only place where an improvement changes what you ship.

AMARA 07:02 That sounds too absolute.

NADIA 07:03 It survives the challenge. An hour lost at the constraint is lost by the entire plant and cannot be made up anywhere. An hour saved anywhere else is worth nothing, because the extra units just queue in front of the constraint. That is why plants that improve every station equally see no change in output and a large rise in work in progress.

AMARA 07:28 How do you find it if the cycle times are not written down?

NADIA 07:34 Walk the line and look at the floor. The constraint has work piled in front of it and clear space behind it. You can find it in four minutes without a stopwatch.

Cue 3 The same line after work is moved off the constraint, queues clearing

AMARA 07:46 Then what?

NADIA 07:47 Never starve it and never let it work on something that is already scrap. That second one is the one people miss. Inspect before the constraint, not after. Time spent by your slowest station on a unit that gets rejected later is the most expensive time in the building.

AMARA 08:07 What about buying another machine?

NADIA 08:09 Last, not first. Ask what work could be moved off the constraint onto a station that is standing waiting. It usually costs nothing and it is usually resisted, because it means deliberately loading a fast station and that feels like going backwards.

AMARA 08:26 And once the constraint is relieved?

NADIA 08:28 It moves. There is always a slowest station. Teams that fix one and stop looking are surprised six weeks later when output has not risen a second time. Go and find the new one.

AMARA 08:42 Downtime Paretos. Everyone has one on a wall.

NADIA 08:45 And most of them are ranked by how memorable the cause was. Rank by total time lost. A single four hour breakdown is unforgettable. Two hundred and forty two minute stops cost you exactly the same four hours and not one person can recall a single one.

Cue 4 A downtime Pareto rebuilding itself when ranked by total time rather than frequency

AMARA 09:04 Which of those two gets the attention?

NADIA 09:06 The breakdown, every time, and it is often third on the list. The top of a properly built Pareto is usually something nobody nominated.

AMARA 09:16 You said the largest category eventually becomes other.

NADIA 09:19 It is a reliable end state. The board is filled in at the end of a twelve hour shift from memory, the gaps get the vaguest label available, and within a quarter your biggest loss is called other. At that point you are measuring the reporting process rather than the plant.

AMARA 09:40 How do you stop that?

NADIA 09:42 Capture from the equipment. Review it at handover while the people who were there are still standing in the room. And put a name against each of the top causes, because a cause owned by everybody is owned by nobody.

AMARA 09:58 Handover gets cancelled when the plant is behind.

NADIA 10:01 Which is exactly when the incoming shift most needs it. Ten minutes is the highest value part of the day and it is the first thing sacrificed. If you protect one practice out of this whole course, protect that one.