Pareto Analysis Case Study

4.1 Pareto Methodology

Steps involved in the study:

Step 1: Factory Selection

After gathering information I made contact with plywood manufacturing company i.e. Gattani Ply, where I can place or utilize my knowledge to make some contribution for the development of the company. Thus I have selected a particular plywood manufacturing company at Jorhat, Assam.

Step 2: Conducting of Case Study

After selecting factory a proper case study is to be done over production line, to analyze and collecting required information.

Step 3: Collecting Information

In this step I have gathered information on the Quality Control system of the plywood manufacturing company. Here I have collected data of various defects from the plywood production section provided

4.2 p Chart Methodology

A p chart is a data analysis technique for determining if a measurement process has gone out of statistical control. The p chart is sensitive to changes in the proportion of defective items in the measurement process. The “p” in p chart stands for the proportion of successes of a binomial distribution. The p control chart consists of:

Vertical axis = the percentage of defectives for each sub-group;

Horizontal axis = the sub-group designation. A sub-group is frequently a time sequence (e.g., the number of defectives in a daily production run where each day is considered a subgroup).

In addition, horizontal lines are drawn at the mean number of defectives and at the upper and lower control limits. The distribution of the number of defective items is assumed to be binomial. This assumption is the basis for the calculating the upper and lower control limits. The control limits are calculated as:

UCL=p bar+3√((p bar(1-p bar))/n) CL=p bar

LCL=p bar-3√((p bar(1-p

So I have chosen subgroup be of 4 data points each. The number of samples is represented by the letter “n” and the number of subgroups is represented by the letter “k”

Step 3: Record the data on a data sheet

The data sheet is designed so that it is easy to compute the values of X bar and R for each sub group

Step 4: Find the mean value (X bar) Step 5: Find the range, R

R = X (largest value) - X (smallest value)

Step 6: Find the overall mean, or X double bar

Total the mean values of X bar, for each subgroup and divide by the number of subgroups (k)

Step 7: Compute the average value of the range (R)

Total R for all the groups and divide by the number of subgroups (k)

Step 8: Compute the Control Limit Lines

X bar Control Chart: CL = X double bar UCL = X double bar + A2 * R bar LCL = X double bar - A2 * R bar

R Control Chart: CL = R bar UCL = D4 * R bar LCL = D3 * R bar

Step 9: Construct the Control Chart

Draw in the Control lines CL, UCL and LCL, and label them with their appropriate numerical values

Step 10: Plot the X bar and R values as computed for each