Case Study - Statistical Process Control Background: On a daily basis, Mobley Concrete Company loads and average of 40 to 50 loads of concrete into mixer trucks that deliver the material to the job site. Prior to loading each truck, the front-end loader adds the raw ingredients of the concrete mix into the plant bins and bulk hauling trucks load cement powder into the silos. Upon the command of the batch man, the proper amounts of raw materials are weighed up into the scales on the plant. Once the batch computer system is satisfied that all of the raw materials are in the scales, the material is dropped into the truck where it begins mixing. Once the material has dropped into the truck completely, the driver is notified to pull out from under the plant and the driver proceeds to the wash stand. The particular plant we are discussing has two wash stands so that two trucks may be washing at the same time. The driver exits the truck and goes into the batch room to collect their delivery ticket. The driver is responsible for washing down the mixer truck both for the sake of prolonging the life of the mechanical components and for the image of the company. During the wash-down process, the driver also has the responsibility to check the wetness of the concrete to make sure it matches the consistency desired by the specification on their delivery ticket. Once the load is the proper consistency and the truck has been washed down, they can then travel to the job and deliver the concrete to the customer. Problem: Upon observation on a particular day, it appeared that the two wash stands were insufficient for the plant as trucks seemed to be stacking up at the plant prior to leaving and slowing the delivery to the customers. Data: The Operations Manager, having observed this problem, decided to randomly choose four trucks operating from the plant on one day and time their flow through the plant from the time they began pulling into position, to the time they left plant. A spread sheet has been provided to show the statistical data collected from that day.

Questions:

1. Based on the statistical data, what part of the process can you determine may be the bottleneck? Explain your analysis and your answer.

2. Now look closer at the data for the process or processes you determined may be the bottleneck. Is there any noticeable trend within the data that may help you determine a course of action going forward?

3. What are some possible recommendations to help the process become more streamlined and consistent?

Load Number Driver 1 A Load Size (CY) 10 11 B 2 3 4 D A 5 8 9 5 6 B 11 7 C 10 7 Total load time (minutes) 5.45 6.02 3.05 4.23 4.82 6.08 5.40 3.55 4.00 6.10 4.32 2.95 3.20 4.77 4.90 4.75 4.88 8 9 10 11 12 D 9 11 B C 8 2 13 A D 6 14 15 Total time to retrieve ticket Total Wash down (minutes) time (minutes) 1.50 10.48 1.25 13.53 1.60 11.25 1.70 10.67 2.10 9.98 1.15 13.42 1.32 11.36 1.60 10.08 1.50 10.28 1.80 14.25 1.40 11.20 1.30 11.57 1.60 10.67 1.40 10.98 1.20 11.27 1.75 15.20 1.60 10.92 1.70 10.33 1.27 10.17 1.23 14.98 1.36 9.97 1.80 10.32 1.40 10.20 1.20 11.25 14.75 1.73 10.90 1.151 14.32 1.25 11.27 1.65 10.92 1.70 10.27 9 9 9 16 B 17 D 9 10 5.38 18 19 A D 20 B 7 4 6 21 A D 9 A 10 C B 10 11 3.67 2.23 3.13 4.63 5.25 5.32 6.17 5.15 3.15 3.98 3.15 4.15 22 23 24 25 26 27 28 29 30 1.60 D 10 B 3 C 6 D 5 7