OEE and low Planning/Schedule adherence

Q:  It is theoretically possible to have high OEE and very low schedule adherence, as OEE has no component to measure ‘are we making the correct product today?’.

Arno Koch •    This is not just possible, it is most often the normal situation in OEE implementations. Why is that?

To understand why OEE implementations sometimes tend to be counterproductive to the strive for creating flow in the factory in order to follow customer demand, lets try to find the root cause for the phenomenon;

First of all: What does “Quality” in the Quality rate of OEE mean? It means the product has been produced according to its specifications.

Now what are the specifications that need to be met in a World Class environment? The products needs to be produced according to its:

  • technical specifications
  • specification of delivery
  • specification of costs…

… and all those specifications need to be leveled against customers needs and expectations.

If those specs are not known, wrongly defined, or not applied within the OEE, this is not a problem of the OEE as a measure, but a problem of the use and implementation of the measure.

How to prevent low schedule adherence?

Step 1

Step one to prevent a misalignment between what is produced (due to sub-optimization at the machine) and what is required, is to make sure On Time Delivery becomes a quality parameter on the machine.

So if the product is not produced On Time, it is not within spec, the quality rate in OEE goes down due to not meeting the specification of  delivery time.

Now the assumption often is this: “If the scheduler has the right scheduling tools and access to the status of the current schedule execution by operations, and access to ERP to ensure that raw material exists, then scenarios can be modelled to conveniently place orders into the existing schedule to deliver it, and all the other production orders, on time.”

In other words: “If we produce according to the right schedule, it is OK.”

Unfortunately, this is rarely true. Why? Because the ‘schedule’ is a construct, an opinion, about what is the best way to produce the required orders, based on a whole series of assumptions.

The schedule rarely fulfills customers real demand (it is even worst: since most B2B customers also ‘schedule’, they do not order according to their real demand…) so even if OEE would take ‘schedule fulfillment’ as a Q parameter, this does not guarantee real customer satisfaction.

Conclusion: Even if meeting the schedule would be a parameter of OEE, it is far from sure that customer demand would be met.

Now the question remains: Why is it so hard to meet a schedule, even if the schedule is planned with the best tools and planners?

This is because reality is rarely the same as the assumptions within the planning. In other words: Whatever you plan in advance; it will be probably differently in real life… So than why plan in advance?

Instead of running the optimal planning, you might consider to run your optimal real life!

One of the reasons why the planning is usually far from ‘practical’ and ‘real’ is the fact that the planner and its software are not -or not tight enough- connected to the real life, not being able to respond adequate to changes and deviations to the plannings assumptions.

Knowing this, it is not surprising to see how typically when an order portfolio is planned by the production-team, it will run much smoother than one planned by someone outside of the team.

Step 2

In order to have as much knowledge about the current actual situation around the equipment available, let the production team it selves plan the details of a certain order portfolio. “Those are the orders you have to produce, these are the deadlines, feel free to decide how you run them”

The problem that may arise next, is the supply of raw materials. If the production team plans its own routine of production, how do we know what raw materials are needed when?

Of course we might ask the team to also plan its raw materials, in other words, the team takes over the complete task of the current planner, yet only for the part it needs to run the machine.

We then would still be confronted with variances in real life situations. A typical ‘push planning’ (MRP/ERP systems try to push the planning through the value-chain)  can hardly cope with this, unless we grow buffers, security stocks etc. Which then again create new problems.

Step 3

Create ‘supermarkets’ using 2-bin and fifo buffers to guarantee the delivery of raw materials to the line. Planners and Buyers should be able to define bin-sizes and arrange bin swapping mechanisms with the suppliers. If not they have to learn this.

Step 4.

Give the line as direct as possible access to the real customer demand, show them directly what has been sold to the user, so they can respond adequate to fluctuations in demand.

Planners now take care of CAPACITY planning and not about DETAIL planning. Orders are assigned to machines (based on rules agreed with the teams) and keep track of the flow of bins, the lines of fifo’s etc.

At this point a high OEE can only be achieved if a high customer satisfaction has been achieved, this without complex IT systems, multi layered planning schedules, etc.

NEVER AUTOMATE A LOSS!

NEVER AUTOMATE UNNECESSARY COMPLEXITY !

 

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