Why Daily Plans Fail

At 6:00 Monday morning I create a plan for my day starting at 7:00. That doesn’t seem to be such a difficult task. Why is it that by 7:30 my plan already shows signs of being hopeless?

I’ve done the obvious things. First I upgraded from a magnetic Gantt chart based on hand-written information to Advanced Planning and Scheduling (APS) software. That was much easier to use, but frankly the results didn’t dramatically improve. Feeding it with live data from my Manufacturing Execution System (MES) got me a good starting point, with a lot less effort than the paper approach, but my plan still didn’t hold up to the test of time.

I then realized that my software was based on standard lead times and it assumed infinite capacity — it was constantly overestimating my production capability. So I updated to Finite Capacity Scheduling (FCS) software. That helped a lot. But I still had a lot of problems because the FCS tool was based on a “standard” data model for my industry. I guess we do things a bit different than most people in our industry, but the schedule it generates doesn’t recognize those differences.

So I updated to a general purpose simulation product with the flexibility to model my system as it really is AND generate the Gantt charts and other reports I need for scheduling. So now I can account for that problem aisle where my lift trucks get so congested. And I can account for that machine cluster that shares access to a single crane. As a bonus I also got an animation that lets me “play out” the day and visually see what I can expect.

Now I have a much better plan that is realistic and accurate as long as everything goes well. But it is always optimistic. While I can put in preventative maintenance, there is no way to factor in that my Cobalt 120 machine is 30 years old and breaks down almost every day. Or that my supplier for Jenkins 257 material is often way behind their promised delivery. I can pad the schedule to allow extra time, but that just guarantees that I will waste valuable production time when things go well.

In my simulation tool I can run my model with all that variability accounted for (stochastic analysis) and it gives me good long-term capacity analysis. But since there is no way to predict a specific “random” problem, like an equipment failure, I can’t use that knowledge in generating my plan for today — I am limited to a deterministic schedule … or am I?

Actually there is a new technique available called Risk-based Planning and Scheduling (RPS) that first generates a deterministic plan, then applies a stochastic analysis to that plan. It actually tells me how likely it is that I will meet the plan. For example, orders that require the Cobalt 120 machine or Jenkins 257 material may show a high risk of not completing on time. Since I know this before the shift starts, I have more options on how to deal with it – like adjusting labor assignments, rerouting a process, or expediting a material. I can even evaluate the various alternatives to determine which one performs best, and then base my plan on the alternative that generates an acceptable risk at the lowest cost.

Now that’s a plan I can live with!

Happy Modeling!
Dave Sturrock, VP Operations, Simio LLC

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