The Dean Door Corporation (DDC) manufactures steel and aluminum exterior doors f
ID: 462905 • Letter: T
Question
The Dean Door Corporation (DDC) manufactures steel and aluminum exterior doors for commercial and residential applications. DDC landed a major contract as a supplier to Walker Homes, a builder of residential communities in several major cities. Because of the large volume of demand, DDC had to expand its manufacturing operations to three shifts and hire additional workers. Not long after DDC began shipping doors to Walker Homes, it began receiving some complaints about excessive gaps between the door and the frame. This problem was somewhat alarming to DDC, because its reputation as a high-quality manufacturer was the principal reason that it was selected as a supplier to Walker Homes. DDC placed a great deal of confidence in its manufacturing capability because of its well-trained and dedicated employees, and it never felt the need to consider formal process control approaches. In view of the recent complaints, Jim Dean, the company president, suspected that the expansion to a three-shift operation and the pressures to produce higher volumes and meet just-in-time delivery requests was affecting their quality. On the recommendation of the plant manager, DDC hired a quality consultant to train the shift supervisors and selected line workers in statistical process control methods. As a trial project, the plant manager wanted to evaluate the capability of a critical cutting operation that he suspected might be the source of the gap problems. The nominal specification for this cutting operation is 30.000 inches with a tolerance of 0.125 inches; therefore, the upper and lower specifications are LSL = 29.875 inches and USL = 30.125 inches. The consultant suggested inspecting five consecutive door panels in the middle of each shift over a ten-day period and recording the dimension of the cut. Table 1 shows 10 days data collected for each shift. Having seen the data (Table 1) in this initial study, Jim wants to know answers to the following questions: Is the process in a state of statistical control? Why or why not? If the process is out of control, what might be the likely cause(s)? What recommendations might you make to improve the situation i.e., reduce or eliminate the cause(s)? Finally, is the process capable of meeting the specifications given? Why or why not? The plant manager implemented the recommendations that resulted from the initial study. Because of the success in using control charts, DDC made a decision to continue using them on the cutting operation. After establishing control, additional samples were taken over the next 20 shifts, shown in Table 2. Jim now wants to know: Has the process changed? Explain Is the process capable? Explain TABLE 1 Observations Shift Operator Sample 1 2 3 4 5
29.968
30.01
(case study questions so please answers in case study format thank you)
Table 13.5 DDC Production Data First run Observation Sample Shift Operator 1 2 3 4 5 1 1 Terry 30.046 29.978 30.026 29.986 29.961 2 2 Jordan 29.972 29.966 29.964 29.942 30.025 3 3 Dana 30.046 30.004 30.028 29.986 30.027 4 1 Terry 29.997 29.997 29.980 30.000 30.034 5 2 Jordan 30.018 29.922 29.992 30.008 30.053 6 3 Dana 29.973 29.990 29.985 29.991 30.004 7 1 Terry 29.989 29.952 29.941 30.012 29.984 8 2 Jordan 29.969 30.000 29.968 29.976 29.973 9 3 Cameron 29.852 29.978 29.964 29.896 29.876 10 1 Terry 30.042 29.976 30.021 29.996 30.042 11 2 Jordan 30.028 29.999 30.022 29.942 29.998 12 3 Dana 29.955 29.984 29.977 30.008 30.033 13 1 Terry 30.040 29.965 30.001 29.975 29.970 14 2 Jordan 30.007 30.024 29.987 29.951 29.994 15 3 Dana 29.979 30.007 30.000 30.042 30.000 16 1 Terry 30.073 29.998 30.027 29.986 30.011 17 2 Jordan 29.995 29.966 29.996 30.039 29.976 18 3 Dana 29.994 29.982 29.998 30.040 30.017 19 1 Terry 29.977 30.013 30.042 30.001 29.962 20 2 Jordan 30.021 30.048 30.037 29.985 30.005 21 3 Cameron 29.879 29.882 29.990 29.971 29.953 22 1 Terry 30.043 30.021 29.963 29.993 30.006 23 2 Jordan 30.065 30.012 30.021 30.024 30.037 24 3 Cameron 29.899 29.875 29.980 29.878 29.877 25 1 Terry 30.029 30.011 30.017 30.000 30.000 26 2 Jordan 30.046 30.006 30.039 29.991 29.970 27 3 Dana 29.993 29.991 29.984 30.022 30.010 28 1 Terry 30.057 30.032 29.979 30.027 30.033 29 2 Jordan 30.004 30.049 29.980 30.000 29.986 30 3 Dana 29.995 30.000 29.922 29.98429.968
Explanation / Answer
1. LSL= 29.875
USL = 30.125
Mean of mean value of different observation = 899.7758/30
=29.993
UCL= 29.993 + 3*(0.125/sqrt(30))
= 30.061
LCL =29.993 - 3*(0.125/sqrt(30))
=29.925
few sample means falls outside the control limits which indicates that the process is outside the control limit.
The process seems out of control in shift 3 whose operator is Cameroon. Possible causes are:
i) Inability of operator to mange the specification limit
ii) Third shift causes too much pressure that operator starts ignoring control limit and violate lower limits
Recommendation is too change the operator and assign another operator in place of cameroon in third shift.
Author's Note: Please be specific to question that need to be answered
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