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How M Mahajan Pdf.rar Can Help You Master Statistical Quality Control


Statistical Quality Control By M Mahajan Pdf.rar lemay cranberries pe




Statistical quality control (SQC) is a methodology used to monitor and control the quality of products or services. SQC uses statistical tools and techniques to measure and analyze the data gathered during manufacturing or service delivery to ensure that the products or services meet or exceed customer expectations.




Statistical Quality Control By M Mahajan Pdf.rar lemay cranberries pe



SQC can help improve customer satisfaction, reduce costs, increase productivity, and enhance competitiveness. SQC can also help identify and eliminate defects, errors, waste, and variation in processes.


In this article, we will discuss some of the main tools and techniques of SQC, such as acceptance sampling, statistical process control, and design of experiments. We will also explain how to apply them in practice using examples and case studies.


Introduction




Statistical quality control (SQC) is a branch of statistics that deals with the application of statistical methods to monitor and control the quality of products or services. SQC can be divided into two main categories: acceptance sampling and statistical process control.


Acceptance sampling is a technique that involves inspecting a sample of items from a lot or batch to determine whether to accept or reject the whole lot or batch based on the quality found in the sample. Acceptance sampling can be used when testing every item is impractical, costly, or destructive.


Statistical process control (SPC) is a technique that involves using graphical displays called control charts to monitor the variation in a process over time. SPC can help determine whether a process is in a state of statistical control, meaning that it only exhibits common cause variation (random variation inherent in the process), or whether it is out of control, meaning that it exhibits special cause variation (variation due to external factors that affect the process).


Another technique that can be used in SQC is design of experiments (DOE), which is a method that involves planning, conducting, analyzing, and interpreting controlled tests or experiments to evaluate the effects of various factors on a response variable. DOE can help optimize processes, improve products, solve problems, and generate new knowledge.


The objectives of SQC are to:



  • Ensure that products or services conform to specifications and meet customer needs



  • Detect and prevent defects, errors, waste, and variation in processes



  • Improve process efficiency, effectiveness, reliability, and capability



  • Reduce costs associated with poor quality, such as rework, scrap, warranty claims, customer complaints, etc.



  • Increase customer satisfaction, loyalty, and retention



  • Enhance competitiveness and profitability



The benefits of SQC are:



  • It provides objective and quantitative data for decision making



  • It helps identify root causes of problems and potential solutions



  • It helps reduce variation and improve consistency and uniformity



  • It helps improve process performance and output quality



  • It helps foster a culture of continuous improvement and learning



Acceptance Sampling




Acceptance sampling is a technique that involves inspecting a sample of items from a lot or batch to determine whether to accept or reject the whole lot or batch based on the quality found in the sample. Acceptance sampling can be used when testing every item is impractical, costly, or destructive.


For example, suppose a company receives a shipment of 1000 widgets from a supplier. The company wants to ensure that the widgets meet the quality standards before using them in production. However, testing every widget is not feasible because it would take too much time, money, and resources. Moreover, testing every widget would damage them and make them unusable. Therefore, the company decides to use acceptance sampling to inspect a sample of widgets and make a decision based on the sample results.


Types of Acceptance Sampling Plans




An acceptance sampling plan consists of two main components: the sample size (n) and the acceptance criterion (c). The sample size is the number of items to be inspected from the lot or batch. The acceptance criterion is the maximum number of defective items that can be found in the sample for the lot or batch to be accepted.


For example, an acceptance sampling plan of n = 50 and c = 2 means that 50 items will be inspected from the lot or batch, and if 2 or fewer defective items are found, the lot or batch will be accepted; otherwise, it will be rejected.


There are two main types of acceptance sampling plans: attribute sampling plans and variable sampling plans.


Attribute sampling plans are based on counting the number of defective items or defects in a sample. An item is either defective or not defective, and a defect is either present or not present. Attribute sampling plans can be further classified into single sampling plans, double sampling plans, multiple sampling plans, sequential sampling plans, etc.


Variable sampling plans are based on measuring a continuous characteristic or variable of interest in a sample, such as weight, length, diameter, etc. Variable sampling plans can provide more information than attribute sampling plans with smaller sample sizes. Variable sampling plans can be further classified into mean (or average) plans, range plans, standard deviation plans, etc.


How to Design an Acceptance Sampling Plan




The design of an acceptance sampling plan depends on several factors, such as:



  • The type and nature of the product or service



  • The quality characteristics or specifications to be inspected



  • The acceptable quality level (AQL) and the lot tolerance percent defective (LTPD)



  • The producer's risk (α) and the consumer's risk (β)



  • The cost and benefit of inspection



The acceptable quality level (AQL) is the maximum percentage of defective items that can be considered satisfactory as a process average. The AQL is usually specified by the producer or supplier.


The lot tolerance percent defective (LTPD) is the maximum percentage of defective items that can be tolerated in a lot or batch. The LTPD is usually specified by the consumer or customer.


The producer's risk (α) is the probability of rejecting a good-quality lot or batch. The producer's risk is usually set by the producer or supplier.


The consumer's risk (β) is the probability of accepting a poor-quality lot or batch. The consumer's risk is usually set by the consumer or customer.


The cost and benefit of inspection refers to the trade-off between the cost of inspecting more items and the benefit of reducing the risk of accepting poor-quality lots or batches.


To design an acceptance sampling plan, one can use various methods, such as:



  • Using standard tables or charts that provide various combinations of sample size and acceptance criterion for different levels of AQL, LTPD, α, and β



  • Using software or calculators that can generate optimal or customized acceptance sampling plans based on user inputs



  • Using mathematical formulas or models that can calculate the sample size and acceptance criterion based on AQL, LTPD, α, and β



Advantages and Disadvantages of Acceptance Sampling




Some of the advantages of acceptance sampling are:



  • It can save time, money, and resources compared to 100% inspection



  • It can reduce damage and waste caused by destructive testing



It can provide statistical evidence for quality assurance and certification 71b2f0854b


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