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