1 You manage a work center at amachining company and you\'re required to produce
ID: 3047138 • Letter: 1
Question
1 You manage a work center at amachining company and you're required to produce a metal dowl that is 575+007 inches in length 2 In Sample Number 1, you measured the dimensions of 25 parts and developed the data listed below 4 a. For sample 1, what is your capability for producing parts within the specified limits? 5 b. Based on your results from step a, you've made adjustments to your process and recorded the data 6 in sample number 2. Are you now capable of producing within the specified limits? 7 c For sample 2, what p ge of parts would you predict to babo the upper specification limit? 10 Sample Number 1 13 0.556 14 0.572 15 0.575 16 0.577 17 0.579 18 19 20 21 0.562 0.572 0.574 0.577 0.581 0.564 0.572 0.57 0.577 0. 0.564 0.573 5 0.575 0.577 583 0.586 0.572 0.575 0.577 0.580 0.575 Sample Number 2 23 0.5730.578 24 0.575 25 0.573 26 0.576 27 0.576 28 29 30 31 32 0.574 0.576 0.579 0.575 0.576 0.576 0.575 0.574 0.577 0.574 0.579 0.5730.577 0.575 0.574 0.575 0.576 0.577 0.5 75Explanation / Answer
(a) From the given data, we can find lower specification limit = 0.568 inch ( 0.575 - 0.007 ), and
upper specification limit = 0.582 inch ( 0.575 + 0.007 )
Now , in sample number 1, out of 25 parts, there total 6 parts are falling outside the range specified by above lower and upper limits. Therefore ,
the capability to produce parts within specified limits = (19 / 25 )*100 = 76%
(b) Observing the dimensions of parts in sample number 2, we can conclude that indeed, now all the parts are falling within the specified limits. Therefore , we say that now, we are capable of producing within specified limits.
(c) Since all the parts in sample number 2 are falling inside the specification limits, we would predict that 0.01 % of parts will be above the upper specification limit. (Note: We can't predict 0% because the sample is of finite size and we haven't observed all the possible part dimensions, therefore to be conservative in our prediction, we estimate the failure percentage to be 0.01 % )
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