Statistical Process Control Methods The Perfect toast

Statistical Process Control Methods The Perfect toast

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Introduction

On the following presentation we will provide an overview of the Statistical Process Control Methods on the process of how to make “The Perfect Toast”.

With the Use of SPC as graphical procedure we will determine is the process developed is operating properly. The SPC tool will help us preventing defects during the process implementation phase, avoiding detecting any defect before our products to get to the final customer.

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Process Flowchart – The Perfect Toast

Phase I –

Place toaster is a stable surface

Toaster plugged in?

No

Plug in toaster

Yes

Switch ON the toaster

Open Bread bag

More than one slice?

No

Yes

Place one slice into one toast slot

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Phase I – Process flow for the perfect toast

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Process Flowchart – The Perfect Toast Cont.’

Phase II –

Place two slices onto toast slot

Put into a level handle

Adjust level for tastiness’?

No

Yes

Leave the level at 1

Adjust the level dial between 1-5

Wait till toast pops up

Take the toast(s) out of the toast slot

Ready for eating

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Phase II – Process flow for the perfect toast

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Metric Definitions

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Process performance metrics enables the process to work more efficiently and less costly hence affordable.

The performance metrics employed in the process includes :

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Run Time

Operation Time

Combination of start-up time and the run time

Flow Time

Throughout Rate

Process Variation

Process Capability

Time it takes to make a batch of toasts. It is given as;

Run time = time to make unit toast * number of toast made

Operation time = start up time + run time

Mean time that the one toast takes to be processed fully

The output rate of production

Refers to the process that has failed to follow a specific pattern than is known to be the basic for the process. They can be either assignable or common variations.

Relates the productivity of an in-control process to the specification limits by using capability indices. The index employed to measure process capability are capability index, Cpk

Improved Process Flowchart – The perfect Toast

Toast Making process Flowchart

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Let’s overview again the Improved process to make The Perfect Toast

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Plug in the toaster

Switch ON the toaster

Push down the lever

Place one slice on the level

Place toaster on a stable surface( (Start-up time)

Open Bread bag

Adjust the level between 1-5

1-not toasty

5-very burnt toasty

(Flow time)

Wait till toast pops up (Operation time)

Ready to use (Throughout rate)

Remove toast out of toaster slot (Run time)

The Perfect Toast – Process Comparison

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Current Process Improved Process
The current toast baking process in place possesses many challenges. The primary purpose of this new improved process would be to first, reduce the time that it takes to bake and cook the toast.
The first being time, because of the all steps involved in baking through cooking to ensure the customer get quality food is tiresome. Second creating more efficiency around the customer satisfaction.
The second challenge stems from the fact the cutlery to be used in the baking process, they are expensive. The power is also a challenge. This increases the cost of baking and delivery. Finally help cut unnecessary cost as it relates to baking few toast at a time whereby a several toasts are baked at the same time.

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The Perfect Toast – Process Metrics

A sample of 50 toasts are tested on the daily for 15 days to test the quality of the baked toast.

The number of defective toasts, i.e. those that do not meet the minimum quality that is recommended are recorded are the number of defective toasts.

The fraction of the defective is determined and the sample standard deviation is calculated as shown in the excel workbook.

The Lower and Upper Control limits are determined using the formula:

LCL = p-hart – 3*σ

UCL = p-hart + 3*σ

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The Perfect Toast – Process Metrics

The control chart is constructed as shown:

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Image retrieved from :https://goo.gl/images/7gcFWX

Chart retrieved from excel file SPCMethod.xls

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Conclusion

In summary, the purpose of this Statistical Process Control Method was to allow detecting issues during the actual process. difficult where the process characteristic is continuously varying.

The control chart, shows that the process is under control. The defective rate is within the Lower Control Limit and the Upper Control Limit. Thus, from the sample of 50 toasts every day, the number that does not meet the expect quality standards are not rampant. This is indicated by the sample line which is within the limits.

On this case, the Control chart provides a better way to monitor a process, to estimate and control variation and to improve the process performance.

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Image retrieved from :https://goo.gl/images/dQcHbF

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References

Agarwal, S., Gallo, J. J., Parashar, A., Agarwal, K. K., Ellis, S. G., Khot, U. N., … & Kapadia, S. R. (2016). Impact of lean six sigma process improvement methodology on cardiac catheterization laboratory efficiency. Cardiovascular Revascularization Medicine, 17(2), 95-101.

Benneyan, J. C., Lloyd, R. C., & Plsek, P. E. (2003). Statistical process control as a tool for research and healthcare improvement. BMJ Quality & Safety, 12(6), 458-464.

Burr, I. W. (2018). Statistical quality control methods. Routledge.

MacGregor, J. F., & Kourti, T. (2015). Statistical process control of multivariate processes. Control Engineering Practice, 3(3), 403-414.

Montgomery, D. C., & Mastrangelo, C. M. (2009). Some statistical process control methods for autocorrelated data. Journal of Quality Technology, 23(3), 179-193.

Robert Jacobs, F., Richard Chase, B. (2014). Operations and Supply Chain Management (14th ed.). New York, NY: McGraw-Hill/Irwin.

Steinfeld, B., Scott, J., Vilander, G., Marx, L., Quirk, M., Lindberg, J., & Koerner, K. (2015). The role of lean process improvement in implementation of evidence-based practices in behavioral health care. The journal of behavioral health services & research, 42(4), 504-518.

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Below are the references utilized for this analysis

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