Quality Control MCQ Quiz in मल्याळम - Objective Question with Answer for Quality Control - സൗജന്യ PDF ഡൗൺലോഡ് ചെയ്യുക

Explanation:

P-chart (Proportion or Fraction Defective Chart):

• It is used to monitor and control the fraction produced in a process that is defective or non-conforming.
• It follows a binomial distribution.
• This chart is best suited in cases where inspection is carried out to classify articles as either excepted or rejected.

\(Fraction\;defective = \frac{{Number\;of\;defective\;articles}}{{Size\;of\;sample}} \Rightarrow P = \frac{{\sum d}}{N}\)

Working rule

• Calculate the average fraction defective.
• Compute σ the standard error of fraction defective.
• \(Standard\;error\;of\;\vec p\;\left( {{\sigma _p}} \right) = \sqrt {\frac{{\vec p \times \vec q}}{{\vec n}}\;} ,\;(\vec q = \left( {1 - \vec p} \right)\)
• Now calculate both the limits.

Additional Information

Control charts:

• A control chart is a graphical representation of the collected information.
• It indicates whether a process is in control or out of control.
• It determines process variability and detects unusual variations taking place in a process.
• It ensures the product quality level.
• It provides information about the selection and setting of tolerance limits.

Types of Control Charts:

Variable charts are meant for the variable type of data. X bar and R Chart, X bar and sigma chart, the chart for the individual units

Attribute charts are meant for attribute type of data. p chart, np chart, c chart, u chart, U chart.

Control charts for the variable type of data (X bar and R charts)

• In the x bar chart, the sample means are plotted in order to control the mean value of a variable.
• In the R chart, the sample ranges are plotted in order to control the variability of a variable.
  • R charts are used to monitor the variation of a process based on samples taken from the process at given times (hours, shifts, days, weeks, months, etc.).
  • The measurements of the samples at a given time constitute a subgroup.

Control charts for Attribute type data (p, c, u charts)

• p-charts calculates the percentage defective in the sample; p-charts are used when observations can be placed in two categories such as yes or no, good or bad, pass or fail etc.
• c-charts counts the number of defects in an item; c-charts are used only when the number of occurrences per unit of measure can be counted such as the number of scratches, cracks etc.
• u-chart counts the number of defects per sample; The u chart is used when it is not possible to have a sample size of a fixed size.

Explanation:

Six Sigma:

(i) It is a methodology and symbol of quality.

(ii) It is a quality philosophy and way of improving the performance by knowing where you are and where you can be.

(iii) It is a purely scientific method used for the process improvement and this method is known as DMAIC [ Define, Measure, Analyze, Improve, Control].

(iv) "Six Sigma quality" is a term generally used to indicate a process is well controlled (within process limits ±3s from the center line in a control chart, and requirements/tolerance limits ±6s from the center line).

(v) Its main focus is the quality improvement and reduction of defects. Its target to bring down the error rate to 3.4 EPMO.

1 million = 3.4 DPMO [ Defect per million opportunity] → used in the manufacturing sector

1 million = 3.4 EPMO [ Error per million opportunity] → used in the service sector

\(DPMO = \frac{{Number\ of\ defect}}{{Number\ of\ unit\ produced}} \times {10^6}\)

\(EPMO = \frac{{Number\ of\ error}}{{Number\ of\ customer\ served}} \times {10^6}\)

Explanation:

According to the Qualitative aspects of quality management, there are two quality control systems

1. Statistical Quality Control (SQC) (Acceptance Sampling): It is defined as the quality control system where statistical techniques are used to control, improve and maintain quality.
2. Statistical Process Control (SPC) (Process Control Charts): It is a graphical representation of quality characteristics and indicate the process is under control or not. These charts are based on the fact that variability exists in all the process.
    

Control Charts and Their Types

Control Chart for Variable

Control Chart for Attribute  

Explanation:

Acceptance sampling:

Acceptance sampling is the process of evaluating a portion of the product/material in a lot for the purpose of accepting or rejecting the lot as either conforming or not conforming to a quality specification.

Operating Characteristic (OC) curve:

The operating characteristic curve for an attribute sampling plan is a graph of fraction defective in a lot against the probability of acceptance.

For any fraction defective p in a submitted lot, The OC curve shows the probability Pa that such a lot will be accepted by the sampling plan.

In a sampling plan, three parameters are specified,

N = lot size from which the samples are drawn,

n = sample size,

C = acceptance number

It means, takes a random sample of n from a lot of N if the sample contains more than C defective, rejects the lot otherwise accept the lot.

There are two terms on the OC curve:

Producer's risk:

• If the quality is good still from the sampling plan some lots are rejected the producer has to suffer.
• The producer risk is the probability of rejecting a good lot that otherwise would have been accepted.

Consumer's or Purchaser's risk:

• if the quality is bad still from the sampling plan some lots are to be accepted the consumer will suffer.
• Consumer's risk is the probability of defective lots being accepted which otherwise would have been rejected.

Explanation:

P-chart (Proportion or Fraction Defective Chart):

• It is used to monitor and control the fraction produced in a process that is defective or non-conforming.
• It follows a binomial distribution.
• This chart is best suited in cases where inspection is carried out to classify articles as either excepted or rejected.

\(Fraction\;defective = \frac{{Number\;of\;defective\;articles}}{{Size\;of\;sample}} \Rightarrow P = \frac{{\sum d}}{N}\)

Working rule

• Calculate the average fraction defective.
• Compute σ the standard error of fraction defective.
• \(Standard\;error\;of\;\vec p\;\left( {{\sigma _p}} \right) = \sqrt {\frac{{\vec p \times \vec q}}{{\vec n}}\;} ,\;(\vec q = \left( {1 - \vec p} \right)\)
• Now calculate both the limits.

Additional Information

Control charts:

• A control chart is a graphical representation of the collected information.
• It indicates whether a process is in control or out of control.
• It determines process variability and detects unusual variations taking place in a process.
• It ensures the product quality level.
• It provides information about the selection and setting of tolerance limits.

Types of Control Charts:

Variable charts are meant for the variable type of data. X bar and R Chart, X bar and sigma chart, the chart for the individual units

Attribute charts are meant for attribute type of data. p chart, np chart, c chart, u chart, U chart.

Concept:

Average Outgoing Quality Limit (AOQL) represents the maximum percentage defective in the outgoing product. The average out going quality depends on the incoming quality, the probability that he lot will be accepted.

1. Incoming quality is good = outgoing quality is good
2. Incoming quality is bad = whole lot is rejected. Therefore, outgoing quality is good since bad parts won’t get through.
3. Incoming quality is neither very good nor very bad = outgoing quality gets worse and % defective reaches maximum known as AOQL 

Option 4 is correct.

The session layer is responsible for various operations such as dialogue controlling, adding checkpoints for synchronization, token management, and various other operation.

Important Points

• In token management, the layer tries to maintain that only one user can manipulate the same critical operation at a time to avoid any kind of collision.
• The collision can take place when two or more users try to attempt the same critical operation at the same time, it can cause a loss.

Explanation:

• Six Sigma is a methodology and symbol of quality.
• It is a quality philosophy and a way of improving performance by knowing where you are and where you can be.
• It is purely a scientific method used for process improvement and this method is known as DMAIC.
  • D- Define
  • M- Measure
  • A- Analyse
  • I- Improve 
  • C- Control
• Its main focus is quality improvement and reduction of defects.
• It targets to bring down the error rate.

Explanation:

Bureau of Indian Standard:

• The Bureau of Indian Standard is responsible for bringing service and products as a mandatory standard.
• It provides safe, reliable and quality goods and minimise the health hazard to the consumer.
• It Appoints the authority besides BIS to verify the reliability of the products and service
• Bureau of Indian Standards is under the Ministry of Consumer Affairs, and it is a National Standard body.
• It was established under the Bureau of Indian Standard Act 1986.
• It was established on 23 December 1986.
• Headquarters is in Manek Bhawan New Delhi.

Explanation:

Evolution of Quality Concept and management

The concept of quality has existed for many years, though its meaning has changed and evolved over time.

• In the early twentieth century, quality management meant inspecting products to ensure that they met specifications.
• In the 1940s, during World War II, quality became more statistical in nature. Statistical sampling techniques were used to evaluate quality, and quality control charts were used to monitor the production process.
• In the 1960s, with the help of so-called quality gurus, the concept took on a broader meaning. Quality began to be viewed as something that encompassed the entire organization, not only the production process. Since all functions were responsible for product quality and all shared the costs of poor quality.
• Quality was seen as a concept that affected the entire organization.
• Current quality concept includes continual improvement and prevention of defects in order to survive in highly competitive market.