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Statistical Quality Control

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  Statistical Quality Control** Meaning: S.Q.C. means planned collection & effective use of data for studying causes of variations in quality either as between processes, procedures, materials, machines etc. or over periods of time. By statistical quality control, we mean the various statistical methods used for the maintenance of the quality in manufactured product. Purpose of SQC: 1) To provide a basis for a better understanding of the variations that exists in quality characteristics. 2) To help directly or indirectly to improve quality. 3) To help in separating the assignable causes from the chance causes. 4) Better uniformity of quality. 5) Better utilization of raw materials. 6) More efficient use of equipment. 7) Less scrap and rework, hence lowering costs. 8) Better inspection. 9) Improved producer-consumer relations. Quality of Product: Quality product means good or excellent product. In industry, a quality product is one that fulfils custom...
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Statistical Quality Control

  ⭐ Meaning of Quality 1️⃣ Conformance to specifications 2️⃣ Fitness for use 3️⃣ Customer satisfaction 4️⃣ Delighting the customer 5️⃣ Enchanting the customer (modern view) 🌟 Dimensions of Quality Attribute Meaning Performance How well it works Features Additional characteristics Reliability Consistency Conformance Meeting standards Durability Life of the product Serviceability Ease of repair Aesthetics Look & feel Reputation Brand trust 🔧 Quality Control A procedure to measure quality, compare with standards, and correct deviations. 🔹 Quality must be planned → achieved → controlled → improved continuously 📊 Statistical Quality Control (SQC) Applying statistical methods to control and improve product quality. 🎯 Purpose of SQC ✔ Reduce variation ✔ Improve quality ✔ Lower scrap & rework ✔ Better productivity & inspection 🖼 Seven Quality Control Tools (7-QC) Below are simplified visual representations to help you post: Tool Simple visual image Fl...
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Partial and Multiple Correlation Coefficient

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  PARTIAL CORRELATION   MULTIPLE CORRELATION   When the value of a variable is influenced by another variable, the relationship between them is a simple correlation. In a real-life situation, a variable may be influenced by many other variables. For example, the sales achieved for a product may depend on the income of the consumers, the price, the quality of the product, sales promotion techniques, the channels of distribution, etc. In this case, we have to consider the joint influence  of several independent variables on the dependent variable. Multiple correlations arise in this context. Coefficient Of Multiple Linear Correlations   The coefficient of multiple linear correlation is given in terms of the partial correlation coefficients as follows:
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NON-PARAMETRIC TEST - Test for Randomness

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Simulation

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NORMAL DISTRIBUTION - Definition, MGF, Mean and Variance

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  Procedure testing of hypothesis 1.       Setting up of hypothesis – Null hypothesis and Alternative hypothesis. 2.       Defining the level of significance (α) 3.       Computation of test statistic  The test statistics is a statistic based on appropriate probability distribution. It is used to test                     whether the null hypothesis set up should be accepted or rejected. Z – Distribution: Use z- distribution under normal curve for large sample (i.e., if the sample size n≥    30). The Z – statistic is defined as 4.       Critical region or critical value. The rejection region or critical region is the region of the standard normal curve corresponding to a predetermined level of significance (α). The value of the sample statistics defines the region of acceptance and rejection is call...
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