SPC,SQC & QC TOOLSMOHAMETH HISAM M RA31001916018

Relationship between SPC,SQC & QC

Statistical Process ControlStatistical 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.

Application

•Control of Variation •Continuous Improvement •Predictability of Processes •Elimination of Waste •Product Inspection

The Seven Old Tools

1. Control chart 2. Run chart 3. Pareto chart 4. Flow chart 5. Cause and effect diagram 6. Histogram 7. Scatter diagram

Control chart is a graph used to study how a process changes over time. Data are plotted in time order. A control chart always has a central line for the average, an upper line for the upper control limit and a lower line for the lower control limit. These lines are determined from historical data.

Control Chart

Data Category Chart Type Statistical QtyVariable Data X-bar & R Mean & Range

X-tilde & R Median & RangeX-Rs Individual Values

Attributes Data P- Chart Percent of defectivesnP- Chart Number of defectivesC- Chart Number of defectsU- Chart Number of defects per unit

Run Chart

A run chart is a line graph of data plotted over time. By collecting and charting data over time, you can find trends or patterns in the process. Because they do not use control limits, run charts cannot tell you if a process is stable.

Pareto chartPareto Chart is a type of chart that contains both bars and a line

graph, where individual values are represented in descending order by bars, and the cumulative total is represented by the line.

Flow Chart A flowchart is a type of diagram that represents an algorithm, workflow or process, showing the steps as boxes of various kinds, and their order by connecting them with arrows. This diagrammatic representation illustrates a solution model to a given problem. Flowcharts are used in analyzing, designing, documenting or managing a process or program in various fields

Cause and Effect Diagram (Fishbone Analysis)

Cause and Effect diagram is a diagram which visually displays the many causes for a problem or effect. It helps to find the root cause of a problem.

Histogram

A histogram is a graphical representation of the distribution of numerical data. It is an estimate of the probability distribution of a continuous variable. It consisting of rectangles whose area is proportional to the frequency of a variable and whose width is equal to the class interval.

Scatter DiagramScatter Diagram is a graph in which the values of two variables

are plotted along two axes, the pattern of the resulting points revealing any correlation present.

The Seven New Tools

1. Affinity diagram2. Relational diagram3. Tree diagram4. Matrix diagram5. Program decision process chart6. Arrow diagram7. Prioritization Matrix

Affinity DiagramAn Affinity Diagram is a tool that gathers large amounts of

language data (ideas,opinions, issues) and organizes them into groupings based on their natural relationships . The Affinity process is often used to group ideas generated by Brainstorming.

Relationship DiagramAn entity-relationship diagram (ERD) is a graphical

representation of an information system that shows the relationship between people, objects, places, concepts or events within that system. An ERD is a data modeling technique that can help define business processes.

Tree DiagramTree diagram a way of representing the hierarchical nature of a structure in a graphical form. It helps to list the various criteria based on their importance.

Matrix diagram

A Matrix Diagram (MD) is a tool that allows a team to identify the presence and strengths of relationships between two or more lists of items. It provides a compact way of representing many-to-many relationships of varying strengths.

The process decision program chart (PDPC) systematically identifies what might go wrong in a plan under development. Countermeasures are developed to prevent or offset those problems. By using PDPC, you can either revise the plan to avoid the problems or be ready with the best response when a problem occurs.

Program decision process chart

Arrow diagramArrow diagramming method (ADM) is a network diagramming technique in which activities are represented by arrows. ADM is also known as the activity-on-arrow (AOA) method. The arrow diagram shows the required order of tasks in a project or process, the best schedule for the entire project, and potential scheduling and resource problems and their solutions. The arrow diagram lets you calculate the “critical path” of the project.

A prioritization matrix is a simple tool that provides a way to sort a diverse set of items into an order of importance. It also identifies their relative importance by deriving a numerical value for the priority of each item.

Prioritization Matrix

Statistical Quality Control

Statistical quality control refers to the use of statistical methods in the monitoring and maintaining of the quality of products and services.

Sampling technique is the most widely used SQC tool

SamplingSampling is concerned with the selection of a subset of

individuals from within a statistical population to estimate characteristics of the whole population. Each observation measures one or more properties (such as weight, location, colour) of observable bodies distinguished as independent objects or individuals.

Probability SamplingProbability sampling is a sample in which every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined.

1. Simple random sampling 2. Systematic sampling3. Stratified sampling 4. Cluster sampling

Simple random samplingIn a simple random

sample (SRS) of a given size, all such subsets of the frame are given an equal probability. Furthermore, any given pair of elements has the same chance of selection as any other such pair (and similarly for triples, and so on). This minimises bias and simplifies analysis of results.

Systematic samplingSystematic sampling (also known as interval sampling) relies

on arranging the study population according to some ordering scheme and then selecting elements at regular intervals through that ordered list. Systematic sampling involves a random start and then proceeds with the selection of every kth element from then onwards.

Stratified samplingWhen the population is heterogeneous, the use of simple random sample may not produce representative sample. Some of the bigger strata may get over representation while some of the small ones may Entirely be eliminated. Look at the variables that are likely to affect the results, and stratify the population in such a way that each stratum becomes homogeneous group within itself. Then draw the required sample by using the table of random numbers. Hence in stratified random sampling a sub- sample is drawn utilizing simple random sampling within each stratum.

Cluster sampling

The purpose of cluster sampling is to sample economically while retaining the characteristics of aprobability sample. Groups or chunks of elements that, ideally, would have heterogeneity among themembers within each group are chosen for study in cluster sampling. This is in contrast to choosingsome elements from the population as in simple random sampling, or stratifying and then choosingmembers from the strata, or choosing every nth case in the population in systematic sampling.

Non-probability sampling is any sampling method where some elements of the population have no chance of selection or where the probability of selection can't be accurately determined. It involves the selection of elements based on assumptions regarding the population of interest, which forms the criteria for selection. Hence, because the selection of elements is non-random.

Non-probability sampling

1. Quota sampling2. Convenience sampling3. Purposive sampling4. Self-selection sampling5. Snowball sampling

  Quota sampling, the population is first segmented into mutually exclusive sub-groups, just as in stratified sampling. Then judgement is used to select the subjects or units from each segment based on a specified proportion. 

Quota sampling

In quota sampling the selection of the sample is non-random. For example, interviewers might be tempted to interview those who look most helpful. The problem is that these samples may be biased because not everyone gets a chance of selection. This random element is its greatest weakness and quota versus probability has been a matter of controversy for several years.

Convenience sampling

Convenience sampling  is a type of non-probability sampling which involves the sample being drawn from that part of the population which is close to hand. That is, a population is selected because it is readily available and convenient.

For example, if the interviewer were to conduct such a survey at a shopping centre early in the morning on a given day, the people that he/she could interview would be limited to those given there at that given time, which would not represent the views of other members of society in such an area, if the survey were to be conducted at different times of day and several times per week.

Purposive sampling is a sampling technique in which researcher relies on his or her own judgment when choosing members of population to participate in the study.

Purposive sampling

TV reporters stopping certain individuals on the street in order to ask their opinions about certain political changes constitutes the most popular example of this sampling method. However, it is important to specify that the TV reporter has to apply certain judgment when deciding who to stop on the street to ask questions; otherwise it would be the case of random sampling technique.

Self-selection sampling is appropriate when we want to allow units or cases, whether individuals or organisations, to choose to take part in research on their own accord. The key component is that research subjects (or organisations)volunteer to take part in the research rather than being approached by the researcher directly.

Self-selection sampling

Snowball samplingSnowball sampling (or chain sampling, chain-referral

sampling, referral sampling) is a non-probability sampling technique where existing study subjects recruit future subjects from among their acquaintances. Thus the sample group is said to grow like a rolling snowball. As the sample builds up, enough data are gathered to be useful for research. This sampling technique is often used in hidden populations which are difficult for researchers to access 

For example, people who have many friends are more likely to be recruited into the sample.

Quality controlQuality control (QC) is a procedure or set of procedures

intended to ensure that a manufactured product or performed service adheres to a defined set of quality criteria or meets the requirements of the client or customer. 

The various techniques used in QC are1. PDCA Cycle2. 5S 3. Kaizen

PDCA Cycle

PDCA (plan–do–check–act or plan–do–check–adjust) is an iterative four-step management method used in business for the control and continual improvement of processes and products. It is also known as the Deming circle/cycle/wheel

5S is the name of a workplace organization method that uses a list of five Japanese words: seiri, seiton, seiso, seiketsu, and shitsuke. They all start with the letter "S". The list describes how to organize a work space for efficiency and effectiveness by identifying and storing the items used, maintaining the area and items, and sustaining the new order. The decision-making process usually comes from a dialogue about standardization, which builds understanding among employees of how they should do the work.

5S

Kaizen is a lean manufacturing tool that improves quality, productivity, safety, and workplace culture. Kaizen focuses on applying small, daily changes that result in major improvements over time.

Kaizen