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I never recommend wikipedia but in this case it has a good comparison:
The question doesn't make much sense to me.
- A flow chart could show process differences between mfg and test environments. I'm not sure how it could be used to show the effects of climate change other than "temp affects this step".
- A histogram shows how data falls into certain ranges. Perhaps they could be compared for the two environments. I don't know how it could be effectively be used to show that differences involve climate patterns.
- A scatter diagram shows relationships between 2 variables. That could be applied to output vs. temp showing effects of climate, but not very well when one of your variables is binary (lab vs. mfg).
- Control charts could be compared between the 2 environments, but unless there is an assumption that the difference is caused by climate, I don't see it addressing the climate aspect either.
It seems like the author has something in mind, but having used all of those tools in practice, I'm at a loss to what one tool would address both the stakeholder's concerns.
A scatter diagram may be an adequate tool. Scatter diagrams use the values of two variables to look for a relationship between them. If the variables are correlated, the points will fall along a line or curve. In this case, the variables are the data of climate and the results of manufacturing.
I have been thinking of a scatter diagram too - for instance,
• the effects of climate change on the environment: rainy days, high/low temperatures, floods versus the final project costs/timeline, etc.
Regarding the control charts: for example, we can compare current-day variations with the standard-variation capacity for change in air temperature -however, it doesn't make sense to me (in the context of the question).
A scatter plot may have been what the author intended, but I have issues with that as a valid answer, much of which involves the term climate.
1) There are far more than 2 variables involved. At a minimum you have 3: Some proxy measurement for climate, and 2 separate environments. You could choose temperature for the climate variable and compare 2 separate scatter plots, however climate isn't temperature. Humidity, precipitation, wind speed, barometric pressure, etc. are also variables of weather, can all affect manufacturing processes, and could all be different between the test and mfg environments. Temperature drives weather but it isn't how weather is defined, let alone climate.
2) Climate is statistical weather patterns over long periods of time. When you consider seasonal weather pattern changes, you'd need many years of data measuring manufacturing processes and the weather variable of choice for statistical validity.
All the choices are tools commonly used in 6 Sigma, which has a problem solving model of Define, Measure, Analyze, Improve, and Control. When I read the problem statement and compare it to the possible answers, I'm still struck with the problem being poorly defined.
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