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Delta Plastics, Inc. (B)

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Delta Plastics, Inc. (B)
Running header: Delta Plastic, Inc. (B)

Delta Plastics, Inc. (B)

Delta Plastics, Inc. (B)
Introduction
Have you taken the time to look at your plastic containers? Well, if you do there is a chance that your containers have flaws and defects that are noticeable to the human eye. There are defects that do not get in the way of using the containers but for quality purposes, it still is a defect. This paper will show a 3-sigma control chart for the production process for using the new and standard material. The control chart will show if the processes are in control and if the materials are equally subject to defects. Based on the finding, Jose will be advised on the action to take.
3-Sigma control chart

Prepare a 3-sigma control chart for both production processes, using the new and standard material (use of quality report in “Delta Plastics, Inc. Case A,” Chapter 5).
The control prepare is showing the type and number of defect using a sampling of 20. The average number of defects for the new material is 2.44 and the range is 4.55. The control limit
L) is 2.41, upper control limit (UCL) is 4.14 and the lower control limit (LCL) is -1.73.

The average number of defects for the standard material is 1.93 and the range is 2.6. The control limit (CL) is 2.41, upper control limit (UCL) is 3.28 and the lower control limit (LCL) is .571.

Control

Discuss whether or not both materials are in control and what conclusion may be drawn.
To determine whether both material are in control it will be based on the number of defects and the quality tool used to determine if the product will perform as intended. It was previously determined that the Pareto analysis determined the reliability (Reid & Sanders, 2010). According to Reid & Sanders (2010), the Pareto analysis is a technique that identifies quality problems based on the degree of importance. The defects that will decrease the reliability would be uneven edges and cracks.



References: Reid, R.D, & Sanders, N. R. (2010). Operations management: An integrated approach (4th ed.). Hoboken, NJ: John Wiley & Sons. pp. 165. Wienclaw, R. (2008). Statistical Quality Control. (p. 1). Great Neck Publishing. Retrieved from Research Starters - Business database.

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