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Wet-Land Drilling, Inc. recently raised concerns about the bags it received from Bayfield, citing a deviation in weight from the standard 50 pounds to 47.5 pounds per bag. This has emerged as a significant issue for the company, attributing it to increased demand, the influx of untrained employees, and a shift in employee schedules. In order to address this bag weight problem comprehensively, a thorough analysis utilizing Statistical Process Control (SPC) is crucial.
Statistical Process Control (SPC) employs statistical techniques to measure and analyze process variation.
Primarily utilized in manufacturing, SPC aims to monitor product quality and maintain processes within predetermined targets. Given the bag weight discrepancy, it is imperative to examine the potential errors in the process, particularly those arising from increased demand and the lack of control by experienced employees during the night shift.
The historical bag weight data reveals an average of 50 pounds per bag with a standard deviation of 1.2, denoted as X=50 and σ=1.2. Applying SPC principles, the upper control limit (UCL) and lower control limit (LCL) can be determined.
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The UCL is calculated as 50 + 3σ, resulting in 51.4697, while the LCL is calculated as 50 - 3σ, resulting in 48.5303. This establishes a 99.73% confidence interval for the bags' average weight within these limits.
The percentage of bags with an average weight within control limits across different shifts is as follows:
- Day Shift: 96%
- Afternoon/Evening Shift: 50%
- Night Shift: 50%
To ensure proper quality control and rectify the bag weight problem, several proactive measures are recommended.
Implementing constant monitoring with double checks on bag weights is crucial. Additionally, creating mean and range charts as a guide for employees will enhance control measures. Bag packers should be equipped with scales accompanied by these charts to minimize errors in weight.
Investing in scales for both the production and bag packing areas, integrated with mean and range charts, will substantially reduce weight discrepancies. Furthermore, the incorporation of surveillance cameras in these areas will add an extra layer of oversight. Training programs for new employees focusing on dosage and understanding mean and range parameters for each bag type are essential to mitigate potential errors.
In conclusion, addressing the bag weight problem at Wet-Land Drilling, Inc. requires a multifaceted approach. Statistical Process Control analysis has provided insights into the current situation, emphasizing the need for stringent quality control measures. The recommendations put forth aim to create a robust system that ensures consistency in bag weights and safeguards against future discrepancies.
Quality Control in Bag Weight Management at Wet-Land Drilling, Inc. (2016, Jun 06). Retrieved from https://studymoose.com/case-study-bayfield-mud-company-essay
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