Quality control

Introduction

In manufacturing, quality control is a process that ensures customers receive products free from defects and meet their needs. When done the wrong way, it can put consumers at risk.

Quality control can be achieved by two methods-

1. Statistical process control- chart used
2. Six Sigma- follow key principles

Statistical process control-

Statistical process control (SPC) is defined as the use of statistical techniques to control a process or production method.
The seven quality improvement tools-

Cause-and-effect diagram: (also called Ishikawa or fishbone chart): Identifies many possible causes for an effect or problem and sorts ideas into useful categories.

Check sheet: A structured, prepared form for collecting and analyzing data; a generic tool that can be adapted for a wide variety of purposes.

Control charts: Graphs used to study how a process changes over time. Comparing current data to historical control limits leads to conclusions about whether the process variation is consistent (in control) or is unpredictable (out of control, affected by special causes of variation).

Histogram: The most commonly used graph for showing frequency distributions, or how often each different value in a set of data occurs.

Pareto chart: Shows on a bar graph which factors are more significant.

Scatter diagram: Graphs pairs of numerical data, one variable on each axis, to look for a relationship.

Stratification: A technique that separates data gathered from a variety of sources so that patterns can be seen (some lists replace “stratification” with “flowchart” or “run chart”).

Some following control charts are used in industries-

• X-bar chart.- In this chart, the sample means are plotted in order to control the mean value of a variable (e.g., size of piston rings, the strength of materials, etc.).

• R chart.- In this chart, the sample ranges are plotted in order to control the variability of a variable.

• S chart.- In this chart, the sample standard deviations are plotted in order to control the variability of a variable.

• S**2 chart.- In this chart, the sample variances are plotted in order to control the variability of a variable.

• C chart - In this chart, we plot the number of defectives (per batch, per day, per machine, per 100 feet of pipe, etc.). This chart assumes that defects of the quality attribute are rare, and the control limits in this chart are computed based on the Poisson distribution(distribution of rare events).

• P chart - in this chart, we plot the percent of defectives (per batch, per day, per machine, etc.) as in the U chart. However, the control limits in this chart are not based on the distribution of rare events but rather on the binomial distribution (of proportions). Therefore, this chart is most applicable to situations where the occurrence of defectives is not rare

Benefits of quality control-

• Increase customer loyalty
• Gain repeat business
• Gain new customers from referrals
• Maintain or improve your position in the market
• Improve safety
• Reduce liability risks
• Contribute to overall positive branding of your product

Quality Assurance process

Seven quality control tools

Six Sigma

Six Sigma is a systematic approach to eliminating errors. Six Sigma is a quality-control methodology developed in 1986 by Motorola

The Six Sigma DMAIC approach is typically used to improve an existing process.

it can be achieved by following this procedure

• Define the problem and desired outcome
• Measure the ability of the process
• Analyze the data and identify the root cause of variations (defects
• Improve or modify the process so that fewer variations (defects) are produced
• Control the process. Prevent and correct variations before they result in defects

six sigma process has a process mean (average) that is six standard deviations from the nearest specification limit. This provides enough buffer between the process of natural variation and the specification limits.

Example, if a product must have a thickness between 3.25mm and 3.30 mm to meet customer requirements, then the process mean should be around 3.275, with a standard deviation less than 0.025 (3.30 would be 6 standard deviations away from 3.275), assuming a normal distribution.

Key of six sigma-

• Focusing on customer requirements
• Using extensive measurement and statistical analysis to understand how work gets done and to identify the root cause of problems (variations)
• Being proactive in eliminating variation and continually improving the process
• Involving people in Six Sigma cross-functional teams
• Being thorough and being flexible