SQC & SPC

Abhishek Sharma (051)

Achal Singhal (052)

Ankit Kr Saraogi (054)

Bharat Sakarwal (055)

Nandagopal P (100)

Shashank Shetter (105)

OBJECTIVE

To learn about Quality control tool-“Statistical Quality Control” and “Statistical Process Control” in the manufacturing industry and the steps involved in implementation of them.

STATISTICAL QUALITY CONTROL

CATEGORIES OF SQC CONT..

Descriptive Statistics used to describe the quality characteristics and

relationships. statistics such as the mean, median, standard

deviation, the range, and a measure of the distribution of data are included.

CATEGORIES OF SQC

Acceptance sampling is the process of randomly inspecting a sample

of goods and deciding whether to accept the entire lot based on the results.

Acceptance sampling determines whether a batch of goods should be accepted or rejected.

CATEGORIES OF SQC CONT…

Statistical process control (SPC) involves inspecting a random sample of the

output from a process and deciding whether the process is producing products with characteristics that fall within a predetermined range.

SPC answers the question of whether the process is functioning properly or not.

All three of these statistical quality control categories are helpful in measuring and evaluating the quality of products or services. However, statistical process control (SPC) tools are used most frequently because they identify quality problems during the production process

STATISTICAL PROCESS CONTROL

SPECIFIC SPC TOOLS AND PROCEDURES

Seven quality tools are available to help organizations to better understand and improve their processes. Check Sheet Cause-and-Effect Sheet Flow Chart Pareto Chart Scatter Diagram Probability Plot Histogram Control Charts

PARETO CHART

PARETO CHART

The Pareto chart can be used to display categories of problems graphically so they can be properly prioritized.

ANALYSIS OF SELECTED PROBLEM

Once a major problem has been selected, it needs to be analysed for possible causes.

Cause-and-effect diagrams, scatter plots and flow charts can be used in this part of the process.

CAUSE AND EFFECT OR FISHBONE DIAGRAM

The fishbone chart organizes and displays the relationships between different causes for the effect that is being examined.

This chart helps organize the brainstorming process.

The major categories of causes are put on major branches connecting to the backbone, and various sub-causes are attached to the branches.

A tree-like structure results, showing the many facets of the problem. The method for using this chart is to put the problem to be solved at the head, then fill in the major branches.

FISHBONE DIAGRAM

FLOWCHARTING

After a process has been identified for improvement and given high priority, it should then be broken down into specific steps and put on paper in a flowchart.

This procedure alone can uncover some of the reasons a process is not working correctly.

Flowcharting also breaks the process down into its many sub-processes.

Analysing each of these separately minimizes the number of factors that contribute to the variation in the process.

FLOWCHARTING

SCATTER PLOTS

The Scatter plot is another problem analysis tool. Scatter plots are also called correlation charts.

A Scatter plot is used to uncover possible cause-and-effect relationships.

It is constructed by plotting two variables against one another on a pair of axes.

A Scatter plot cannot prove that one variable causes another, but it does show how a pair of variables is related and the strength of that relationship.

SCATTER PLOTS

DATA GATHERING AND INITIAL CARTING

The following tools will help with gathering data related to the problem. Check sheets Histogram Probability plot

CHECK SHEETS

HISTOGRAM

PROBABILITY PLOT

CONTROL CHART

CONTROL CHARTS

Fluctuation or variability is an inevitable component of all systems and is expected, arising naturally from the effects of miscellaneous chance events.

However, variation outside a stable pattern may be an indication that the process is not acting in a consistent manner.

Statistical Process Control charts graphically represent the variability in a process over time. When used to monitor the process, control charts can uncover inconsistencies and unnatural fluctuation.

CONTROL CHARTS

ZONES IN CONTROL CHARTS

CONTROL LIMITS

AVERAGE CHARTS

RANGE CHARTS

CASE ON SPC IMPLEMENTATION IN MANUFACTURING

INDUSTRY PROFILE

This firm is the collaboration of three industries to mark its presence as one of the largest firm of the automotive rubber parts industry, situated in northern India.

It is recognized as the largest manufacturing company in the field of Automobile Rubber Parts in India, with its wide range of parts.

It has also achieved TS-16949:2002, QS-9000 and ISO-9002 standards of quality assurance

RANGE OF PRODUCTS

Its product range offers following class products: Oil Seals Radial Shaft Seals Shock Absorbers/Rod Seals Hydraulic Seals Shaft Seals Valve Stem Seals

DESCRIPTION OF CASE STUDY

Shocker seals are the main components in this industry which needed more attention because of their higher rejection.

These shocker seals have percentage rejection more than 9.1%.

SPC techniques are required to implement on these products to reduce the percentage rejection.

OVERVIEW OF OPERATIONS

ROOT CAUSES

Moulding is the first process of manufacturing of shocker seals. It is found that various moulding defects are responsible for the rejection. Following defects are observed in this process, causing for rejection. Air trap Tear Knitting Foreign matter Curing Excess material Less material Dirty cavity

ROOT CAUSES CONT…

Air trap Insufficient Vacuum Improper Environmental temperature

Tear Higher temperature Improper manual loading

Material (excess/less) Improper setting of grub screw volume

Cold bit Improper cleaning of nozzle hole Dirty Top portion of mould

ROOT CAUSES CONT…

Trimming Offset trimming problem Spiral Lining problem Step Trimming problem

CAUSE AND EFFECT DIAGRAM

RECOMMENDATIONS In-process inspection is must for each manufacturing

operation. Adequate Vacuum must be created. Proper Environmental temperature should be

maintained Maintain temperature of the casting between 19000C

to 21000C. Manual loading should be replaced by mechanised

loading. Grubbed screw volume should be maintained at the

required level. Clean the nozzle hole properly. Clean top portion of mould properly. Trimming should be done very carefully

IMPLEMENTATION OF X AND R CHARTS TO DIAMETERS OF SHOCKER SEALS

Assumptions The sample size (n) of 4 is considered and 400

observations of outer diameter of shocker seals for are taken in random manner. These

observations are taken after removing the root causes.

Target outer diameter of shocker seals = 62 mm ± 0.10 mm (tolerance).

X CHART So, upper and lower specification limits can be calculated as:

Upper specification Limit (USL) = 62.10 mm and Lower specification Limit (USL) = 59.90 mm

Mean ( X ) Chart Mean or Average of one sample can be calculated as: = (X1 + X2+ X3+ X4) ÷ 4 X Where, n is the sample size = 4 (for this case) Similarly, Mean or Average of 400 samples can be calculated as Where, k is the number of subgroups = 400 (for this case) X=

24800.70/400 = 62.002 mm and Average range can be calculated as:

= 30.02/400 = 0.075 Upper control limit= 62.002+0.738×0.075 = 62.06 mm Lower control limit = 62.002 - 0.738×0.075 = 61.94 mm

A2 = 0.738, D4 = 2.28, D3= 0 (values of these factor, corresponding to sample size, are available in all the books of Quality control)

X CHART

R CHART

Range (R) Chart =30.02/400 = 0.075 Where, k is the number of subgroups = 400 Upper control limit on R chart 2.28x0.075 = 0.171x0.075=0 Lower control limit on R chart

R CHART

CONCLUSIONS

The basic requirements of the manufacturing processes are studied then the statistical process control of the specific process is found out.

SPC analysis may easily help in improving the efficiency of the manufacturing process thus decreasing the number of defective products, thus saving a lot of re-work cost and valuable time.

After implementing the required suggestions/ recommendations for shocker seals, it is found that process capability is improved and it is greater than required.

LEARNING

Statistical process control (SPC) is the application of statistical methods to the monitoring and control of a process to ensure that it operates at its full potential to produce conforming product. We learnt what are the steps involved in implementation of SPC.

The example of Automotive Seals helped us understand the process of implementation and the practicality involved in the process. It made us understand the benefits which an organization can achieve by implementing SPC in their system.

THANK YOU