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Industrial Statistics with Minitab by Xavier Tort-Martorell Llabres, Lluis Marco Almagro, Pere Grima Cintas

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6.2 Copper

A manufacturer of copper tubes has detected, after collecting data and analyzing them with a Pareto diagram, that almost 70% of all process stops are due to breaks during the stretch of the tube.
After a brainstorming session attended by the heads of the stretching and casting sections, the three shift managers, and the person in charge of the laboratory, a list of all possible causes is compiled. These are shown in columns C1 to C6 of file COPPER.MTW.
Once the cause–effect diagram had been studied, it was decided to explore whether the alloy's contents of lead (Pb) or phosphorus (P) or the shift, which seemed to be the most probable causes, were really responsible for the breaks. In order to check that, data were collected throughout four weeks (60 shifts) on the following variables: the number of breaks, the contents (in ppm) of P and Pb in the alloy, and the shift within the breaks occurred.
Use Minitab to represent the cause–effect diagram and, analyzing the given data, to answer the following questions:
  • Do the data confirm the suspicions that the content of P, the content of Pb or the shift influence the breaks?
  • Has the process been stable during the four data collection weeks?

To construct the corresponding cause-and-effect diagram, proceed as follows.

Stat > Quality Tools > Cause-and-Effect

nc06uf009.eps
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