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- Keshav Ram Singhal
krsinghal@rediffmail.com
keshavsinghalajmer@gmail.com
Blog on 'Quality Concepts and ISO 9001: 2008 Awareness' at http://iso9001-2008awareness.blogspot.in

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Monday, December 11, 2017

Revised Edition of Training Handbook on 'ISO 9001:2015 QMS Awareness'


Revised Edition of Training Handbook on 'ISO 9001:2015 QMS Awareness' released.

CONTENTS


# 01 - Learning objectives
# 02 - Historical background
# 03 - Standard development timeline for ISO 9001:2015
# 04 - Why new version?
# 05 - Key feature changes
# 06 - Structure and terminology
# 07 - Meaning of certain terms
# 08 - Foreword of the standard
# 09 - Introduction
# 10 - ISO 9001:2015 clauses in brief
# 11 - Context of the organization
# 12 - Leadership
# 13 - Management representative in ISO 9001:2015 QMS?
# 14 - Planning
# 15 - Support
# 16 - Operation
# 17 - Performance evaluation
# 18 - Improvement
# 19 - Tips for organizations using ISO 9001:2008
# 20 - Transition Planning
# 21 - Developing and implementing ISO 9001:2015 QMS
# 22 - Risk-based Thinking - An integral part of ISO 9001:2015 QMS
# 23 - Understanding the process approach and PDCA
# 24 - Quality management principles
# 25 - Change management in ISO 9001:2015
# 26 - Adding value to the audit
# 27 - Evaluation questionnaire
# 28 - Feedback
# 29 - Acknowledgement


If you are interested to see the preview, please send an email to keshavsinghalajmer@gmail.com.

Thanks,

Keshav Ram Singhal


Monday, December 4, 2017

TRAINING HANDBOOK ON 'ISO 9001:2015 QMS - APPLYING RISK-BASED THINKING (RBT)'


TRAINING HANDBOOK
ON
ISO 9001:2015 QMS - APPLYING RISK-BASED THINKING (RBT)


CONTENTS


# 01 - Introduction

# 02 - The 2008 global financial crisis and risk management

# 03 - Definition of risk

# 04 - Nature and impact of risk

# 05 - Why we need risk-based thinking?

# 06 - Risk-based thinking in ISO 9001:2015 QMS

# 07 - Benefits of applying risk-based thinking

# 08 - Summarized hint for applying risk-based thinking

# 09 - Risk awareness culture in your organization

# 10 - Risk management or formal risk-based approach

# 11 - Process diagram for Risk-based thinking (RBT)

# 12 - Understanding the organization and its context, Step-by-step process

# 13 - External and internal issues of an organization, Some external issues, Some internal issues

# 14 - Format - Context of the organization - Determining external and internal issues

# 15 - Understanding the needs and expectations of interested parties

# 16 - Format - Determining interested parties and their needs and expectations

# 17 - Interested parties and their needs and expectations - A few examples

# 18 - Planning and addressing risks and opportunities

# 19 - Overview of risk assessment tools and techniques

# 20 - Brainstorming

# 21 - Check-lists

# 22 - Failure Modes and Effect Analysis (FMEA)

# 23 - Delphi technique for risk determination

# 24 - A simple method to determine risks and opportunities

# 25 - Format for determining risks and opportunities

# 26 - Examples of some risks

# 27 - Opportunities and a few examples

# 28 - Risk register

# 29 - Risk matrix and risk matrix chart diagram

# 30 - Conclusion

# 31 - Bibliography (a list of a few books and web pages)

# 32 - Evaluation Questionnaire

# 33 - Your feedback

# 34 - Acknowledgement

By attending the training and/or reading this literature, a participant will be able to understand:
- Concept of risk-based thinking,
- ISO 9001:2015 QMS requirements related to risk-based thinking,
- Benefits of using risk-based thinking,
- An overview of various risk assessment tools - Techniques and methodologies that you may apply in your QMS,
- Using risk-based thinking to achieve better internal controls.
- Demonstrating risk-based thinking during audits (internal and external).

If you are interested to see the Preview of the Training Handbook, please send an email to:
keshavsinghalajmer@gmail.com or krsinghal@rediffmail.com.

Friday, December 1, 2017

Delphi technique for risk determination


Delphi technique for risk determination

The Delphi technique can be used to determine risks. Delphi technique is an information-gathering technique used as a way to reach a consensus of experts on a subject. Experts on the subject participate in this technique anonymously. The Delphi Technique is a method used to estimate the likelihood and outcome of future events. A group of experts exchange views, and each independently gives estimates and assumptions to a coordinator, who reviews the data and thereafter prepares a summary report. The group members discuss and review the summary report, and give updated forecasts to the coordinator, who again reviews the updated data and prepares a second report. This process continues until all participants reach a consensus. This technique can be applied at any stage of the risk determination process or at any phase of a system life cycle, wherever a consensus of views of experts is needed.

The experts at each round have a full record of what forecasts other experts have made, but they do not know who made which forecast. Anonymity allows the experts to express their opinions freely, encourages openness and avoids admitting errors by revising earlier forecasts.

The technique is an iterative process. It first aims to get a broad range of opinions from the group of experts. A group of experts are questioned using a semi-structured questionnaire. The experts do not meet so their opinions are independent. The results of the first round of questions, when summarised, provide the basis for the second round of questions. Results from the second round of questions feed into the third and so on to final round. The aim is to clarify and expand on issues, identify areas of agreement or disagreement and begin to find consensus. Following steps should be undertaken:

- Select a Coordinator.
- Select experts for the group as the technique relies on a panel of experts.
- Define the issue of risk determination to the group members.
- Round one questions - Ask general questions to gain a broad understanding of the experts view. The questions may go out in the form of a questionnaire or survey. Collate and summarise the responses, removing any irrelevant material and looking for common viewpoints.
- Round two questions - Based on the answers to the first questions, the next questions should delve deeper into the risk determination to clarify specific issues. These questions may also go out in the form of a questionnaire or survey. Again, collate and summarise the results, removing any irrelevant material and look for the common ground. We should remember that the exercise is done to build consensus.
- Round three questions - The final questionnaire aims to focus on supporting decision making. Again, collate and summarise the results, removing any irrelevant material and look for the commonly agreed points. You may have more than three rounds of questioning to reach a closer consensus.
- Act on coordinator's findings - After the round of questions, hope that the team experts will have reached a consensus and the coordinator will have a view of future risks and opportunities. Analyse the findings and put plans in place to deal with future risks and opportunities.

Predicting the future is not an exact science, but the Delphi Technique can help in understanding the likelihood of future events and what impact they may have on the process, product and service. Delphi technique is labour intensive and time consuming, so a slow process. Since the opinion in Delphi technique needs to be expressed in writing, the participants need to be able to express themselves clearly in writing.



Thursday, July 6, 2017

Understanding Statistical Tools and Techniques - 11 - PROCESS MAPPING



PROCESS MAPPING

Process mapping is a workflow diagram that brings forth a clear understanding of a process or a number of processes. A process map is a planning and management tool that visually describes the flow of work. Process map shows a series of events that produce an end result. A process map is also known as a flowchart, process flowchart, process chart, functional flowchart, functional process chart, process model, workflow diagram, business flow diagram or process flow diagram.

The purpose of process mapping is to gain better understanding of a process and to improve efficiency. It provides insight into a process. It helps the involved people to know the process steps and brainstorm ideas for process improvement. It is a documented information that increase communication.

Process mapping involves following steps:

Step 1 - Select the process for which process mapping is to construct and determine boundaries of the process - where to start (beginning of the process) and where to end (process end).

Step 2 - List all steps involved in the process with sufficient information.

Step 3 - Sequence all steps from start to end.

Step 4 - Draw process map by using appropriate symbols.

Step 5 - Check the flowchart for completeness and include pertinent information.

Step 6 - Finalize the flowchart.

Common process mapping symbols are described in the below figure:



How you liked the write-up. Please post your comments. Thanks.

- Keshav Ram Singhal


Wednesday, July 5, 2017

Understanding Statistical Tools and Techniques - 10 - STRATIFICATION




STRATIFICATION

Stratification is a statistical tool used in combination with other analysis tool. When data from a variety of sources or categories lump together, it is difficult to visualize the meaning of data. Stratification technique separates the data so that pattern of the data can be seen.

Stratification is a technique used to analyze or divide a universe of data into homogeneous groups (strata) often data collected about a problem or event represents multiple sources that need to be treated separately. It involves looking at process data, splitting it into distinct layers (almost like a rock is stratified) and doing analysis to possibly see a process improvement. Stratification is related to segmentation, but it is different from segmentation.



Following procedure will be useful:

- Before collecting data, consider the information and sources of data that can have effect on the results. Plan to collect stratification information.
- After collecting data, when you plot or graph the collected data on scatter diagram or control chart or histogram or any other analysis tool, use different marks or colours to differentiate data from various sources.
- Data plotted or graphed that differentiate from each other are said to be stratified.
- Analyze subsets of stratified data separately.




Some examples of different sources that may require data to be stratified are different equipment, shifts, departments, materials, suppliers, products, days or time.

Thus, analysis of survey data can be benefited from stratification technique.

How you liked the write-up. Please post your comments. Thanks.

- Keshav Ram Singhal


Monday, July 3, 2017

Understanding Statistical Tools and Techniques - 09 - SCATTER DIAGRAM




SCATTER DIAGRAM

A scatter diagram is a graphical representation of two variables showing the relationship between them. If variables are correlated, the points will fall along a line or a curve. This diagram is also known as a scatter plot, x-y graph, or correlation chart. It is a problem solving tool.

We can use scatter diagram when we may have paired numerical data and one variable data is dependent on other variable. Scatter diagram can be constructed by plotting two variables against one another on a pair of axes. With the help of scatter diagram, we can try to determine whether two variables are related and potential root causes of problems.



It will be useful to draw scatter diagram after brainstorming causes and effects using a cause and effect diagram to determine whether a particular cause and effect are related. A scatter diagram is used to uncover possible cause-and-effect relationship.

Following procedure will be useful to construct a scatter diagram:
- Decide two variables against which you wish to see the relationship
- Collect pairs of data of these two variables
- Draw a graph with independent variable on the horizontal axis and the dependent variable on the vertical axis
- For each pair of data, put a dot or symbol where x-axis value intersect y-axis value
- Look at the pattern of dots (or symbols) to see if a relationship is obvious
- If data form a line or a curve, it indicates that variables are correlated




When data forms a line or curve, then you may use regression analysis or correlation analysis by using following steps:
- Decide the points from top to bottom by drawing horizontal line
- Divide the points from left to right by drawing a vertical line
- If number of points is odd, you should draw the line through the middle point
- In this way, you will be able to divide points on the graph into four quadrants
- Count the points in each quadrant (leaving the point on the line)
- Add diagonally opposite quadrants
- Find smaller sum and total of points in all quadrants
- A = points in upper left + points in lower right
- B = points in upper right + points in lower left
- Q = the smaller of A and B
- N = A + B
- Look up the limit for N on the trend test table



- If Q is less than the limit, two variables are related
- If q is greater than or equal to the limit, the pattern could have occurred from random chance and we can say that no relationship is demonstrated

How you liked the write-up. Please post your comments. Thanks.

- Keshav Ram Singhal


Friday, June 30, 2017

Understanding Statistical Tools and Techniques - 08 - PARETO CHART




PARETO CHART

A Pareto chart looks like a bar graph, but it contains both bars and a line graph. It is one of the basic tools of quality control. The length of the bars in the graph represents frequency or cost (time or money). These bars are arranged with longest bar on the left and shortest to the right. This is a tool which can be used to analyze the ideas from brainstorming session. This tool is also known as Pareto diagram or Pareto analysis. This tool is used to identify the vital few problems or causes of problems that have the greatest impact on the process. This chart pictorially represents data in the form of a ranked bar chart that shows the frequency of occurrence of items in descending order. The Pareto chart is named after Wilfried Fritz Pareto, an Italian engineer, sociologist, economist, political scientist and philosopher. He introduced the concept of Pareto efficiency.



It is significant to use Pareto chart:

- To analyze data about frequency of problems or causes of problems in a process
- To focus on the most significant problem or cause, when there are many problems or causes
- To analyze broad causes
- To communicate with others about the data



Following procedure will be useful to use Pareto chart and its analysis:

- Decide the categories of group items
- Decide approximate measurement (frequency, quantity, cost, or time)
- Decide the time period to gather data and use in the Pareto chart (one work cycle, one full day, or one week)
- Collect data, record and assemble data for the category each time
- Subtotal the measurements for each category
- Determine the appropriate scale for the measurements data collected
- Mark the scale on the left side of the chart
- Construct and label bars for each category by placing the tallest to the left, next tallest to its right and so on
- Calculate the percentage for each category
- Draw a right vertical axis and label it with percentage in a graph paper. Be sure that left measurement corresponds to one-half and it should be exactly opposite 50% on the right scale.
- Calculate and draw cumulative sums
- Add the subtotals for the first category and second category and place a dot above the second bar indicating the sum, then add subtotal of third category to the sum and place a dot above the third bar indicating the new sum and so on. Continue the adding subtotals and placing dots for all bars.
- Connect the dots, starting from the top of first bar. The last dot should reach 100 percent on the right side

In this way we can visualize the most important factors among a typically large set of factors through the Pareto chart. A Pareto chart often represents the most common sources of defects, the highest occurring type of defect, or the most frequent reasons for problems.

How you liked the write-up. Please post your comments. Thanks.

- Keshav Ram Singhal


Thursday, June 29, 2017

Understanding Statistical Tools and Techniques - 07 - HISTOGRAM




HISTOGRAM

A histogram is a snapshot of variation or distribution, where data are grouped into cells and their frequency represented as bars. It is a commonly used graph to show frequency distribution. It looks like a bar chart, but it is different from the bar chart. We can put the data from the check sheets into a histogram. A histogram is a set of vertical bars whose areas are proportional to the frequency represented.

The histogram helps in analyzing the capability of a process. The variables being measured are shown along x-axis and the frequency occurrences of each measurement is charted along y-axis.



A histogram is convenient for large amounts of data particularly when the range is wide. It gives a picture of the extent of variation. It highlights unusual areas and indicates probability of particular values occurring. Histogram depicts the central tendency or mean of the data and its variation or spread.

A histogram is useful in showing characteristics of the process being measured, such as:

- Whether results of the process show a normal distribution – a bell curve?
- Whether the range of the data indicates that the process is capable of producing product as per defined specifications?
- How much improvement is necessary to meet specifications?



It is convenient to use histogram when data are numerical and we want to see the shape of data distribution to determine whether the output of a process shows normal distribution.

Following procedure will be useful:

- Decide a process to observe
- Collect at least 50 consecutive data points from the process
- Use histogram worksheet to set up histogram
- Draw x- and y-axes on the graph paper. Y-axes should be used mark and label for counting data values (frequency values) and x-axis to mark and label with variable values from the histogram worksheet.

For using histogram, we need to use histogram worksheet to set up the histogram on graph paper. Histogram worksheet helps in determining the number of bars, the range of numbers that go into each bar and labels for the bar edge.

How you liked the write-up. Please post your comments. Thanks.

- Keshav Ram Singhal


Sunday, June 25, 2017

Understanding Statistical Tools and Techniques - 06 - CONTROL CHART



CONTROL CHART

One of the key tools of Statistical Process Control (SPC) is a control chart. It is used to study and monitor a repetitive process, so that the process may remain in control.

Organizations use interrelated processes resulting output as a product. The outcome of a process is never exactly the same every time. Fluctuation or variability is an inevitable component of all processes or systems and it is expected. Fluctuation or variability arises naturally from the effects of miscellaneous chance events. If outcome of a process remains within the stable pattern, then we can say that the process is OK, but variation outside a stable pattern may be an indication that the process is not OK in a consistent manner. Event or outcome, finally beyond expected variability indicates that the process is out of control.



The control chart is a graph, which is used to show how a process changes over time. Data are plotted in time order. A control chart for a process has the following lines:

- A central line for the average
- An upper line for the upper control limit
- A lower line for the lower control limit

The values for the central line, upper line and lower line (i.e. control limits) are determined from historic data. These can be determined by computation based upon (i) the data covering past and current process records, (ii) statistical formulae whose reliability has been proved in practice. By comparing current data to these lines in the graph, one can come to the conclusion whether the process is in control or out of control. There are various types of control charts, divided in two groups – (i) Control chart for variables, and (ii) Control chart for attributes.



A control chart can be used:

- To control ongoing process by finding and correcting problems as they occur
- To predict the expected range of outcome from a process
- To determine whether a process is stable
- To analyze patterns of a process variations from special causes or common causes
- To determine whether improvement initiatives should aim to prevent specific problem or make changes to the process

Following procedure will be useful:

- Select the process that you wish to study, monitor or control
- Define the process control chart with average central line, upper control limit line and lower control limit line
- Determine the appropriate time period for collecting and plotting data
- Collect data and construct the control chart graph by plotting the data on the chart
- Analyze the graph, identify those signals which are ‘out-of-control’ on the chart and mark them on the graph
- Investigate the cause
- Document investigation process mentioning how investigated, what are the causes, what needs to be done to correct the ‘out-f-control’ situation

Standard control limits are located at 3-sigma away from the average or central line of the chart, known as 3-sigma limits. Control limits define a zone where observed data for a stable and consistent process occurs virtually all the time – 99.7%. Any fluctuations within these limits come from the common causes inherent to the process. Any fluctuations beyond the control limits results from a special cause that require fundamental change or improvement in the process. Any fluctuations beyond the control limits show that the process is out-of-control. When fluctuations are noticed beyond control limits then it is required to investigate and eliminate the special cause. Thus control chart can be used as a quality-monitoring tool.

How you liked the write-up. Please post your comments. Thanks.

- Keshav Ram Singhal



Saturday, June 24, 2017

Understanding Statistical Tools and Techniques - 05 - CHECK SHEET



CHECK SHEET

A check sheet is an organized way of collecting and structuring data. This is a generic tool that can be used for a wide variety of purposes. With the use of this tool, we can collect the facts in a most efficient way. Data is collected and ordered (organized) by adding tally or check marks against predetermined categories of items or measurements. A check sheet simplifies the task of analysis.



A check sheet should be used:
- When data can be observed and collected repeatedly by a particular person or at a particular place
- When collecting data relates to frequency or pattern of events, problems, defects, defect location, defect causes etc.
- When collecting data relates to a particular production process

Following procedure will be useful:
- Define the event or problem to be observed
- Develop operational definitions
- Decide the time and duration of data collection
- Design the check sheet form in such a way that data can be recorded simply by marking check marks or Xs or other similar symbols. The design of check sheet form should make use of input from those who will actually use the check sheet.
- On the fixed time and duration, collect and record data on the check sheet.



A check sheet should be developed in such a way that it is easy to understand. A check sheet is a simple chart for gathering data. When check sheet is designed clearly and cleanly, it assist in gathering accurate and pertinent data, and also allow person concern to read and use data easily.

A check sheet can be kept electronically.

How you liked the write-up. Please post your comments. Thanks.

- Keshav Ram Singhal