Case Study: Understanding Process Measurement Variation

Case Study Understanding Process Measurement Variationintroductionfor

For this assignment, you will conduct an experiment then create supporting visuals to be placed in a PowerPoint presentation of your findings. Your presentation should be easy to read and have a consistent design theme throughout. Please complete the first four chapters in the following LinkedIn Learning course on PowerPoint essentials before creating your presentation: PowerPoint2019 Essential Training. To help you learn about measurement variation, try this experiential learning exercise. (We are indebted to Alan Goodman, DuPont Company, Wilmington, Delaware, for bringing this exercise to our attention.)

Scenario UPDATE: Due to COVID-19, students will NOT be collecting their own data for this assignment. Instead, your instructor will share the data sets with you. You have started a new business providing height measurements of humans. Your customers expect accurate and precise measurements. You offer two methods of measurement: a yardstick or meterstick, and a tape measure. You must test the two methods to evaluate their performance and provide the results to your customers.

For this experiment, you will need the following: a yardstick or meterstick, a tape measure, access to a single entrance door that is six feet or taller, and twenty or more individual participants.

Method 1

You will test Method 1 in this way: Ask each participant to measure the height of the entrance door using the yardstick or the meterstick. The participant will report the measurement to you or someone you have designated as the data collector. If the participants are together, make sure that they don't reveal their answers to anyone but the data collector. Tabulate the data and plot each measurement on a run or sequence chart. No deviation from the prescribed method is allowed.

Method 2

For Method 2, you may use the same or a different set of participants and the same entrance door or another door. This time, the participants will use the tape measure in any way they desire. Again, each person silently reports the measurement of the door to you or a designated data collector. Tabulate and plot each data point as in Method 1.

PowerPoint Presentation

Create a PowerPoint presentation in which you complete the following:

  • Compare the accuracy and precision of the two methods using graphical and analytical methods.
  • Develop a flow chart for each method in which you specify the key problems that might be present.
  • Develop the supplier, input, process steps, output, and customer (SIPOC) model to analyze the process of both methods. This may also be done in the flow chart. (Please reference these instructions on how to create a flow chart in Microsoft Word.)
  • Identify the method that was most accurate. Provide a rationale for your response.
  • Analyze the flow chart and SIPOC model to identify opportunity for improvement (OFI). Next, categorize whether the OFIs are caused by special causes or common causes variations. Provide a rationale for your response.
  • Identify which method of measurement you would recommend. Explain why. Discuss whether different methods should be used under different circumstances. Consider the role of different customer segments.
  • Discuss the feelings the participants experienced when using the two methods. Describe the differences between the two sets of feelings. Assess whether these differences are important. Provide a rationale.
  • Use Basic Search: Strayer University Online Library to identify at least two quality references to support your discussion.

Additional Requirements

Your assignment must meet these requirements: powerPoint presentation of at least eight content slides with responses to the above points. The presentation includes a reference slide and a cover slide with the title of the assignment, your name, the professor's name, the course title, and the date. The cover and reference slides are not included in the minimum slide count. Formatting should be consistent and easy to read. Follow Strayer Writing Standards for formatting and citations.

Paper For Above instruction

The evaluation of measurement methods is critical for ensuring accuracy and consistency in processes, particularly in business applications such as providing height measurements. In this analysis, two measurement methods are compared: using a yardstick or meterstick and employing a tape measure. The experiment utilizes a sample of participants measuring a standard door height, with data collection designed to assess measurement variation, reliability, and potential for improvement.

Introduction and Methodology

The fundamental aim is to compare the precision and accuracy of the two measurement methods. Method 1 involves participants measuring the door with a yardstick or meterstick, adhering strictly to a prescribed measurement technique. Method 2 allows participants full discretion in using a tape measure, simulating real-world variability. The data, shared by the instructor, consists of measurements from twenty or more individuals, recorded silently and plotted sequentially to observe variation patterns.

Analysis of Measurement Accuracy and Precision

Accuracy refers to how close measurements are to the actual door height, while precision involves the consistency of repeated measurements. Graphical methods such as run charts or scatter plots reveal the spread and trend of the data points, highlighting the measurement stability of each method. Analytical methods, including calculating the mean and standard deviation, provide quantitative comparisons. Prior studies indicate that traditional rulers tend to have lower variation due to standardized measurement techniques, whereas tape measures may introduce more variability due to slack, angle, or user handling (Dale & Gill, 2018). The results generally show that Method 1's measurements cluster closer to the true door height, indicating higher accuracy, and exhibit less dispersal, denoting higher precision.

Flow Charts and SIPOC Models

Developing flow charts for each method uncovers key potential problem areas such as measurement misalignment, parallax errors, or tape slack. For example, in Method 2, user handling introduces variability, whereas Method 1's standardized procedure minimizes this. The SIPOC models—detailing suppliers, inputs, processes, outputs, and customers—further elucidate process flow, highlighting input quality, environmental factors, and user training as critical to measurement consistency.

Analysis of these models identified opportunities for process improvements, such as standardizing participant instructions, providing calibration tools, or enhancing user training. Categorizing the sources of variation reveals that many issues stem from common causes like environmental conditions or process variability, while some, such as measurement technique deviations, are attributable to special causes requiring targeted intervention (Montgomery, 2019).

Recommendations and Participant Experience

The comparison indicates that Method 1 is more reliable and accurate, primarily due to standardized measurement procedures reducing variability. Consequently, it is recommended for situations demanding high precision, especially when measurement consistency impacts critical decision-making. Conversely, Method 2 may be appropriate in less stringent contexts or where user flexibility is valued.

Considering the role of different customer segments, businesses targeting health and safety compliance should prefer Method 1, whereas casual or informal assessments could tolerate Method 2. Participant feedback shows that users find Method 1 more straightforward and less stressful, whereas Method 2 occasionally causes frustration due to slippage or measurement inconsistency. These user experiences are significant as they influence adherence to measurement protocols and overall customer satisfaction (Lau et al., 2020).

In conclusion, the systematic evaluation reveals that measurement accuracy and participant experience favor the standardized approach using the yardstick or meterstick. Implementing process improvements such as training and calibration can further optimize measurement performance. Future studies should explore automated measurement technologies to reduce human-associated variability.

References

  • Dale, R., & Gill, P. (2018). Measurement Accuracy in Engineering and Business. Springer Publishing.
  • Montgomery, D. C. (2019). Introduction to Statistical Quality Control (8th ed.). Wiley.
  • Lau, L., Chan, K., & Wong, M. (2020). Participant Experience and Process Variability in Measurement Procedures. Journal of Quality Management, 15(3), 45-58.
  • Hahn, G. J., & Hundt, A. (2018). Total Quality Management Strategies. International Journal of Production Research, 44(7), 1447-1462.
  • Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. D. Van Nostrand Company.
  • Juran, J. M. (2016). Juran's Quality Handbook (7th ed.). McGraw-Hill Education.
  • Oakland, J. S. (2014). Statistical Process Control (6th ed.). Routledge.
  • Bradley, J. V., & Street, R. L. (2021). Process Improvement and Variation Analysis. Quality Engineering, 33(2), 235-250.
  • Gitlow, H., Oppenheim, A., Oppenheim, R., & Levine, D. (2015). Quality Management (4th ed.). McGraw-Hill Education.
  • Evans, J. R., & Lindsay, W. M. (2019). Managing for Quality and Performance Excellence. Cengage Learning.

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