BAYFIELD MUD COMPANY

Bayfield Mud Company

Bayfield Mud Company

What is your analysis of the bag weight problem?

The Bayfield Mud Company has had some problems with their 50-pound bags of treating agents. They sent shipped some bags to Wet-Land Drilling, Inc. that were found to be short-weight by approximately 5%. Wet-Land first did their own study on how many bags were short and by how much. They randomly sampled 50 bags and found the average net weight to be 47.51 pounds. Wet-Land then contacted Bayfield Mud about the situation. Bayfield gave a 5% credit to Wet-Land for the mistakes. Wet-Land was not completely satisfied with the credit because the errors in the weight of the bags could have hurt their operations. Wet-Land informed Bayfield Mud that if something like this happened again, they would take their business elsewhere.

Bayfield's response to all this was to expand from a one-shift to a two-shift operation. Then, they had to expand to a three-shift operation. The additional night-shift bagging crew consisted of all new employees. The most emphasis was placed on increasing output. It was very likely that only occasionally were bags double checked on their weight. This is where the statistical control has come into place.

The company present the problem as an increased of demand, hiring new employees with a lack of training, new employees occupy the night shift, where old employees check the production, however the double checking of the bag still a problem to the company.

As Wet-Land Drilling, Inc. had filed a complaint that the bags it received from Bayfield were short-weight by about 5%, they had to determine the cause of the discrepancy. Bayfield's quality managers may consider using Statistical Process Control (SPC) (Hackman and Wageman, 2005). First of all, we need to analyze and find the errors the process could have, caused by the increased of demand and a lack of control due the old employees, for the analysis I will use the Statistical Process Control (SPC).

Statistical quality control, also called statistical process control, uses statistics to determine when processes or product quality deviate from specifications (Breaugh, 2006). The primary goal of statistical quality control is to maintain and improve processes through techniques such as sampling and process improvement projects, which reduce variations in product. Statistical process control uses control charts to monitor changes in processes, machinery, labor or the environment. Inspections and sampling determine when a process is outside of the control parameters, which can result in a reduction in quality.

Quality Consistency

Statistical quality control helps to maintain the consistency of a process, which will result in a consistency in the quality (Cummings & Worley, 2005). Process controls will not correct defects in the design of a product or in the process itself, but they do ensure each product is manufactured to the process parameters. Sampling and inspections used to collect data for statistical quality control can identify defective processes and flaws in product design.

Tools

The control chart is the tool most often used in statistical process ...