Replicate	Furnace	%Si	%Ca	Cooling	Hardness
1	A	-1	-1	Process 2	17
1	A	-1	1	Process 1	26
1	A	1	1	Process 1	34
1	A	1	-1	Process 2	27
1	B	1	1	Process 2	35
1	B	-1	-1	Process 1	22
1	B	1	-1	Process 1	32
1	B	-1	1	Process 2	25
2	C	-1	1	Process 1	29
2	C	1	-1	Process 2	28
2	C	1	1	Process 2	37
2	C	-1	-1	Process 1	24
2	D	1	1	Process 1	29
2	D	-1	1	Process 2	19
2	D	-1	-1	Process 2	18
2	D	1	-1	Process 1	30
3	E	-1	1	Process 2	22
3	E	1	-1	Process 2	31
3	E	1	1	Process 1	39
3	E	-1	-1	Process 1	21
3	F	1	-1	Process 1	28
3	F	-1	1	Process 1	24
3	F	1	1	Process 2	41
3	F	-1	-1	Process 2	14

2. Material scientists are studying a process to make ceramic parts. They are independently varying 3 factors at two levels each: %Silicon in the ceramic, %Calcium in the ceramic, and two Cooling Processes. The scientists elected to perform three replicates of the experiment which requires 24 total runs. The firing furnaces available to the scientists can only accommodate a set of 4 parts in a single cycle. So, in order to perform all of the runs simultaneously a set of 6 furnaces were required (4 parts per furnace); the furnaces are the same type, but scientists are concerned that some differences could exist among the furnaces. Use the data set Ceramic Sintering.JMP to answer the following questions a.What is the blocking factor? b. What interaction is used to create blocks 1 and 2; blocks 3 and 4; blocks 5 and 6? c. What is the effect of the blocking scheme on the standard errors of the different effect estimates in the full model? d. Find the best model for hardness, using the Fit Model platform in JMP. Be certain to include a screenshot of the Parameter Estimates table for your final model c. Does the blocking factor appear to be needed in the model? Explain. f. Based upon your model, use Desirability Functions in the Prediction Profiler to determine the settings of the experimental factors that would you recommend to the Engineer in order to achieve maximum hardness? Again, be certain to include a screenshot of your Profiler showing the optimized settings. 2. Material scientists are studying a process to make ceramic parts. They are independently varying 3 factors at two levels each: %Silicon in the ceramic, %Calcium in the ceramic, and two Cooling Processes. The scientists elected to perform three replicates of the experiment which requires 24 total runs. The firing furnaces available to the scientists can only accommodate a set of 4 parts in a single cycle. So, in order to perform all of the runs simultaneously a set of 6 furnaces were required (4 parts per furnace); the furnaces are the same type, but scientists are concerned that some differences could exist among the furnaces. Use the data set Ceramic Sintering.JMP to answer the following questions a.What is the blocking factor? b. What interaction is used to create blocks 1 and 2; blocks 3 and 4; blocks 5 and 6? c. What is the effect of the blocking scheme on the standard errors of the different effect estimates in the full model? d. Find the best model for hardness, using the Fit Model platform in JMP. Be certain to include a screenshot of the Parameter Estimates table for your final model c. Does the blocking factor appear to be needed in the model? Explain. f. Based upon your model, use Desirability Functions in the Prediction Profiler to determine the settings of the experimental factors that would you recommend to the Engineer in order to achieve maximum hardness? Again, be certain to include a screenshot of your Profiler showing the optimized settings