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7QC Tools Training

There are seven basic quality tools, which can assist an organization for problem solving and process improvements. The first guru who proposed seven basic tools was Dr. Kaoru Ishikawa in 1968, by publishing a book entitled “Gemba no QC Shuho” that was concerned managing quality through techniques and practices for Japanese firms. It was intended to be applied for “self-study, training of employees by foremen or in QC reading groups in Japan. It is in this book that the seven basic quality control tools were first proposed. valuable resource when applying the seven basic tools (Omachonu and Ross, 2004). These seven basic quality control tools, which introduced by Dr. Ishikawa, are : 1) Check sheets; 2) Graphs (Trend Analysis); 3) Histograms; 4) Pareto charts; 5) Cause-and-effect diagrams; 6) Scatter diagrams; 7) Control charts.

Check Sheet

Check sheets are simple forms with certain formats that can aid the user to record data in a firm systematically. Data are “collected and tabulated” on the check sheet to record the frequency of specific events during a data collection period. They prepare a “consistent, effective, and economical approach” that can be applied in the auditing of quality assurance for reviewing and to follow the steps in a particular process. Also, they help the user to arrange the data for the utilization later (Montgomery, 2009; Omachonu and Ross, 2004). The main advantages of check sheets are to be very easily to apply and understand, and it can make a clear picture of the situation and condition of the organization. They are efficient and powerful tools to identify frequently problems, but they don’t have effective ability to analyze the quality problem into the workplace. The check sheets are in several, three major types are such as Defect-location check sheets; tally check sheets, and; defect-cause check sheets (Kerzner, 2009).

Histogram

Histogram is very useful tool to describe a sense of the frequency distribution of observed values of a variable. It is a type of bar chart that visualizes both attribute and variable data of a product or process, also assists users to show the distribution of data and the amount of variation within a process. It displays the different measures of central tendency (mean, mode, and average). It should be designed properly for those working into the operation process can easily utilize and understand them. Also, a histogram can be applied to investigate and identify the underlying distribution of the variable being explored (Omachonu and Ross, 2004; Forbes and Ahmed, 2011).

Pareto Analysis

It introduced by an Italian economist, named Vilfredo Pareto, who worked with income and other unequal distributions in 19th century, he noticed that 80% of the wealth was owned by only 20% of the population. Later, Pareto principle was developed by Juran in 1950. A Pareto chart is special types of histogram that can easily be apply to find and prioritize quality problems, conditions, or their causes of in the organization (Juran and Godfrey, 1998). On the other hand, it is a type of bar chart that shows the relative importance of variables, prioritized in descending order from left to right side of the chart. The aim of Pareto chart is to figure out the different kind of “nonconformity” from data figures, maintenance data, repair data; parts scrap rates, or other sources. Also, Pareto chart can generate a mean for investigating concerning quality improvement, and improving efficiency, “material waste, energy conservation, safety issues, cost reductions”, etc., (Montgomery, 2009; Kerzner, 2009; Omachonu and Ross, 2004).

Fishbone Diagram

Kaoru Ishikawa is considered by many researchers to be the founder and first promoter of the ‘Fishbone’ diagram (or Cause-and-Effect Diagram) for root cause analysis and the concept of Quality Control (QC) circles. Cause and effect diagram was developed by Dr. Kaoru Ishikawa in 1943. It has also two other names that are Ishikawa diagram and fishbone because the shape of the diagram looks like the skeleton of a fish to identify quality problems based on their degree of importance (Neyestani, 2017). The cause and effect diagram is a problem-solving tool that investigates and analyzes systematically all the potential or real causes that result in a single effect. On the other hand, it is an efficient tool that equips the organization’s management to explore for the possible causes of a problem (Juran and Godfrey, 1998). This diagram can provide the problem-solving efforts by “gathering and organizing the possible causes, reaching a common understanding of the problem, exposing gaps in existing knowledge, ranking the most probable causes, and studying each cause” (Omachonu and Ross, 2004). The generic categories of the cause and effect diagram are usually six elements (causes) such as environment, materials, machine, measurement, man, and method.

Scatter Diagram

Scatter diagram is a powerful tool to draw the distribution of information in two dimensions, which helps to detect and analyze a pattern relationships between two quality and compliance variables (as an independent variable and a dependent variable), and understanding if there is a relationship between them, so what kind of the relationship is (Weak or strong and positive or negative). The shape of the scatter diagram often shows the degree and direction of relationship between two variables, and the correlation may reveal the causes of a problem. Scatter diagrams are very useful in regression modeling (Montgomery, 2009; Oakland, 2003).

Flowchart

Flowchart presents a diagrammatic picture that indicates a series of symbols to describe the sequence of steps present in an operation or process. On the other hand, a flowchart visualize a picture including the inputs, activities, decision points, and outputs for using and understanding easily concerning the overall objective through process. This chart as a problem solving tool can apply methodically to detect and analyze the areas or points Neyestani B. (2017, March). “Seven Basic Tools of Quality Control: An Appropriate Tools for Solving Quality Problems in the Organizations of process may have had potential problems by “documenting” and explaining an operation, so it is very useful to find and improve quality into process (Forbes and Ahmed, 2011),

Control Chart

Control chart or Shewhart control chart was introduced and developed by Walter A. Shewhart in the 1920s at the Bell Telephone Laboratories, and is likely the most “technically sophisticated” for quality management (Montgomery, 2009). Control chart is a special form of “run chart that it illustrates the amount and nature of variation in the process over time”. Also, it can draw and describe what has been happening in the process. Therefore, it is very important to apply control chart, because it can observe and monitor process to study process that is in “statistical control” (No problem with quality) accordant to the samplings or samplings are between UCL and LCL (upper control limit (UCL) and the lower control limit (LCL)). “Statistical control” is not between UCL and LCL, so it means the process is out of control, then control can be applied to find causes of quality problem, as Neyestani B. (2017, March). “Seven Basic Tools of Quality Control: An Appropriate Tools for Solving Quality Problems in the Organizations.” (Omachonu and Ross, 2004). The main aim of control chart is to prevent the defects in process. It is very essential for different businesses and industries, the reason is that unsatisfactory products or services are expensive than spending expenses of prevention by some tools like control charts (Juran and Godfrey, 1998).