GUIDE TO TOTAL QUALITY MANAGEMENT (IE673-852)

Assignment 3: Process Improvement and Process Control Analysis

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Total Quality Management: IE 673, Spring 2008
Assignment #3
Author: William V. Nordling
March 30, 2008
eLearning Pack ID: 673-Spring 2008-61-12

CONTENTS:

  • INTRODUCTION AND OBJECTIVES
  • APPLIED METHODOLOGIES
  • MAIN BODY OF THE PROJECT
  • SUMMARY
  • FURTHER WORK NEEDED/PROPOSED
  • REFERENCES

INTRODUCTION AND OBJECTIVES:

As part of understanding process variability, control charts will be utilized in this assignment to evaluate and improve upon the quality aspects of the process.  Virtual TQM will illustrate the variability within a hypothetical process and will take the necessary measures for correcting them.  Reduction in process variability is an important aspect within a manufacturing environment and needs special attention.  Minimizing variability will reduce costs associated with process downtime and manufacturing defects.  Complete understanding and utilization of these tools will ensure product reproducibility, ultimately ensuring that the customer receives a quality product.

 

APPLIED METHODOLOGIES:

 

Control Charts in the form of X-bar and R charts will be used.  Corrected control charts will show how a process can be corrected by analyzing data feedback.  The utilization of such charts will lead to a controlled process that will result in a mistake free product.  They can be utilized to monitor the processes and generate real time data that can be used to make necessary corrections.   By identifying components of the process that are resulting in process malfunctions or defective product, corrections can be made to avoid future mishaps.  The potential for reworked materials will ensure that waste is minimized.  Similar manufacturing concepts and equipment will also minimize line changeover and cost.  This will result in lower production costs while maintaining a quality operation and product.  The performance of the process will be monitored for a variety of control variables at various inspection stations.  Virtual TQM in collaboration will the other four companies will use similar processes for production and packaging purposes. By analyzing the data generated during process operation Virtual TQM will ultimately provide more efficient processing.  The analysis will incorporate the GE Fanuc automated software system to monitor the process and identify defects while manufacturing each of the products of the three companies. 

For the purposes of this assignment and to illustrate the benefits of process monitoring the graphics displayed on the packaged product will be visually inspected for orientation and flaws.

 

MAIN BODY OF THE PROJECT:

The manufacturing process for each of the products requires that it be packaged in an attractive box with graphics that are appealing to the consumer.  An attractive package should be able to convey a message to the consumer that the contents inside is fun and exciting.  Each company prides itself on quality and needs to display not only the brand name but to entice the consumer to by their product.  The packaged product will be examined for defects and will be monitored using control charts.   Orientation of text and images will be focused upon.  By utilizing the programmable software each of the respective products packaging can be visually inspected for flaws.  The packaging materials can be inspected and rejected if they do not meet the acceptance criteria.  Contents within the package can be repacked if necessary, assuming that the defect is isolated to the packaging carton.  Periodic inspection of the processing line will be the area of focus.  The data contained herein will illustrate the non-conformances on a continuous operation of a packing line for over a span of an eight hour shift.  The inspection is performed on five samples every twenty minutes for a total of one hundred and twenty samples inspected.  The inspection will consist of centering of the company logo from the edge of the packaging.  The control variable is 6 inches from the edge of the box.

 

Histogram

 

The histogram below shows that the data is normally distributed with the exception of a few points on the lower end.  This may indicate that there is something abnormal occurring.  The histogram does not correlate the abnormality to a specific point in time.  Further analysis is needed to identify what is causing the abnormality.  These abnormal occurences can be outliers.  In the case of Virtual TQMs packaging lines these may be attributed to defective parts that were caught by inspection.

 

HISTOGRAM:

https://wnordling.tripod.com/sitebuildercontent/Assignment%203/Histogram.xls

X-Bar and R Charts

 

The data is better analyzed by utilizing the X-Bar chart to observed the average of the centering measurement and the R-Chart that correlates the range of the measurements at each time point.  Looking at the data we can see immediately that the process seems to be in control until the very end of the shift.  Measurements 23 and 24 are outside the control limits falling below the lower control limit.  This shows that something has interrupted the control of the process and further analysis is needed.

 

X-Bar and R Charts

https://wnordling.tripod.com/sitebuildercontent/Assignment%203/X-Bar_and_R_Chart.xls

Reworked X-Bar and R Charts

 
By taking into account that there was an occurrence toward the end of the shift at sampling points 23 and 24, we see that those particular packaged components need reworking (repackaging).  By omitting the product data point that required reworking the data now meets the control limits.  Both the X-Bar and R charts show that the process is now in a state of control.
 
Reworked X-Bar and R charts
 
 

P-Chart for Variable Sample Size

 

Other statistical methods can be applied that can analyze nonconforming data points.  The use of the P-Chart is utilized here to measure the fraction nonconforming for a variable sample size.  The process is measured initially and hourly for three consecutive shifts.  The process was monitored for a specified time and data points were recorded.  By observing the resulting data we can see that there is indeed trening that takes place towards the end of each shift.  By omitting the data points at eight and sixteen hours we can see that the process is in control.  The link below illustrates the p-chart and supporting data. 

 

P-Chart for Variable Sample Size:

https://wnordling.tripod.com/sitebuildercontent/Assignment%203/P-Chart_Variable_Sample_Size.xls

SUMMARY:

 

The main objective of this exercise was to utilize control charts to illustrate how inspected product failed to meet the acceptance criteria.  The control charts showed the non-conformances being generated and that the process was not in control.  By eliminating the measured points that were not able to meet the control limit the analysis showed that the process was indeed in control.  The corrected control charts show that defective product can be identified and that process corrections can ensure that the process in question is in fact in control.  This also illustrated that improvements will ensure that the process is in control.

 

FURTHER WORK NEEDED/PROPOSED:

 

The process as described above will continue to be monitored with special emphasis placed on shift change over.  Significant events during the processing time (i.e. starts, stops and shift changes) may warrant more frequent sampling to avoid such occurrences in the future.

 

REFERENCES:

 

Total Quality Management 3D eBook, CIMware USA, Inc., and CIMware Ltd. UK

Ranky, IE673 Total Quality Management, eLearning Pack ID: 673-Spring 2008-61-12

“Reference” website URL http://Cimwareukandusa.com

http://www.crayola.com

http://www.endlessgames.com/

http://www.unclerez.com/products.htm

http://www.gefanuc.com/

Introduction to Statistical Quality Control, 5th Edition, Douglas C. Montgomery (text used for coefficients).

 

IE673-852 TOTAL QUALITY MANAGEMENT