Doe design of experiments

Doe design of experiments

Doe design of experiments

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In this chapter, you investigate two factors that could reduce the time it takes to prepare an order for shipment: the order processing system and the packing procedure.

You can use both the Session window output and the two effects graphs to determine the effects that are important to your process. First, look at the Session window output.Factorial Regression: Hours vs. Order System, Package

You fit the full model, which includes the two main effects and the 2-factor interaction. Effects are statistically significant when their p-values in the Coded Coefficients table are less than the significance level (α). At the default α level of 0.05, the following effects are significant:

Factor plots include the main effects plot and the interaction plot. A main effect is the difference in the mean response between two levels of a factor. The main effects plot shows the means of Hours using both order processing systems and the means of Hours using both packaging procedures. The interaction plot shows the impact of both factors, order processing system and packing procedure, on the response. Since an interaction means that the effect of one factor depends on the level of the other factor, it is important to evaluate the interactions.

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design of experiments pdf

In this chapter, you investigate two factors that could reduce the time it takes to prepare an order for shipment: the order processing system and the packing procedure.

The Western facility has a new order processing system. You want to determine whether the new system reduces the time it takes to prepare an order. The plant also uses two different packing procedures. You want to determine which procedure is more efficient. You decide to conduct a factorial experiment to test which combination of factors provides the least time required to prepare an order for shipment.

Minitab uses the factor names as the labels for the factors in the analysis output and the graphs. If you do not enter factor levels, Minitab sets the low level to -1 and the high level to 1.

In this example, because you did not add center points or place the runs in blocks, Minitab sets all values for C3 and C4 to 1. The factors you entered are stored in columns C5 (Order System) and C6 (Package).

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But in many cases when we face the study of a particular process we do not know where to start. For this reason it is necessary to know the steps to follow so that the DOE is as simple as possible and gives us the answer to what we want to know.

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One of the great advantages of DOE, which makes its use so popular, is the possibility of studying a wide range of processes and obtaining answers to different types of questions. But we should always ask ourselves the question we hope to answer before we start.

For example, we can use DOE to choose between different alternatives (which raw material is most optimal, which packaging works best, which supplier is most suitable for our needs). In other cases we want to know what is critical in the study process. Obviously there are many variables that affect the final result of our activity (manufacturing, analysis, calibration, etc.), but not all of them have the same weight. That is why one objective of DOE can be to know how changes affect the process and therefore what margin of variability we can afford.

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Since I like to use premade chocolate cake mixes, I decided to use two of my favorite cake mix brands for the experiment. In this publication, I will call the brands A and B. Thinking about the factors that could affect moisture loss, baking time and oven temperature are likely to affect the results. Therefore, the factors or inputs I decided to use for the experiment are:

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Next, I needed a way to measure moisture loss. For this experiment, I used an electronic food scale to weigh each cake (in the same baking pan) before and after baking, and then used those weights along with the formula below to calculate the percentage of moisture lost for each cake:

After spending an entire weekend baking cakes and calculating the moisture loss for each, I entered the data into Minitab for analysis. I also brought back plenty of cake to share with my Minitab colleagues!

Doe design of experiments
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