SPC - Cause/Effect Diagrams and Run Charts

by Oliver Yu

The next two tools were used constantly for large-scale manufacturing sciences support of cell culture: Cause Effect Diagram and the Run Chart.

Cause/Effect (Ishikawa) Diagram

The cause/effect diagram (aka) Ishikawa diagram is essentially taxonomy for failure modes. You break down failures (effects) into 4 categories:

1. Man
2. Machine
3. Method
4. Materials

It's used as a brainstorming tool to put it all out there and to help visualize how an event can cause the effect. This was particularly helpful contamination investigations. In fact, there's a "politically correct" Ishikawa diagram in my FREE case study on large-scale bioreactor contamination.

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The cause/effect diagram helps clarify thinking and keeps the team on-task.

Run Chart

The Run Chart is basically what a chart-recorder spits out. In this day and age, it's what we call OSIsoft PI. You plot a parameter against time (called a trend), and when you do this, you get to see what's happening in sequential order. When you plot a lot of parameters on top of one another, you begin to understand sequence. Things that happen later cannot cause events that happened earlier. Say your online dissolved oxygen readings spiked below 5% for 10 seconds, yet your pO2 remains steady and the following viability measurement shows no drop off in cell viability, you can basically say that the dO2 spike was measurement error.

Here's an example of the modern-day run chart, it's called, "PI":


Run charts (i.e. PI) are crucial for solving immediate problems. A drifting pH probe can dump excess CO2 into a media-batched fermentor. Being able to see real-time data from your instruments and have the experience to figure out what is going on is key to troubleshooting large-scale cell culture and fixing the problem real-time so that the defect is not sent downstream.

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As you can see, SPC concepts are timelessly applied today to cell culture and fermentation... albeit with new technology.