Lesson #3 - Data Collection “There is Data All Around Us - Our Job is to Analyze It!”
THE QUALITY WEB
© The Quality Web, authored by Frank E. Armstrong, Making Sense Chronicles - 2003 - 2016

WHY DATA COLLECTION IS IMPORTANT

Within any manufacturing environment, product information or "data" is collected for a variety of reasons. Some of the common reasons for having this data are: 1.  Data to assist in understanding the actual process or situation. 2.  Data for product analysis. 3.  Data for process control (SPC). 4.  Data for regulation – a basis for raising or lowering a data standard, for example, temperature or thickness. 5.  Acceptance or rejection data – used to approve or reject products or parts. The purpose of collecting data is usually to gather information about the product or to follow up with some form of action. That is, after evaluating the actual conditions revealed by the data, some form of proper action should be taken. The first major critical step, however, is to ensure that the data represents typical conditions, or is data taken from normal circumstances. The second major critical step is to have a purpose for collecting the data. Therefore, before we actually collect data, we should ask the following questions: 1.  Define What we are measuring and Why are we measuring this information? 2.  Define Where and When should we measure this information? 3.  Define How should we be measuring this information and at what time intervals? 4.  Define What measurement tool? 5.  Define Who should be measuring this information? Data can be collected in many ways, depending upon the reason for the data, and the type of information we are seeking. Thus, data can be basically divided into two main groups: 1.  Measurement data: continuous data of length, weight, time, torque, etc. 2.  Countable data: enumerate data such as the number of defectives, percentage defective, number count of each defect, etc. Once we collect this data, it should be analyzed, and the information extracted through the use of statistical methods. For that reason, data should be collected and organized in such a way as to make data analysis more simple and meaningful. Therefore, you need to clearly record the nature of the data collected. You should also record the purpose of the measurements and their characteristics; the date; the instrument or method of measuring; the person performing the measurement; and any other pertinent information to the collection process. To properly record this data, you need to have a consistent time period, for example, measured every hour or every two hours, and make sure you are measuring production parts. In the case of collecting data to count defects, ensure you count each and every item produced, as well as the defects, during the collection period so you can compare how many defects were produced in relation to the total production of parts. Let us now summarize our data collection steps: 1.  Clarify the purpose of collecting the data – it is useless if there is no real reason to collect the data. 2.  Collect data efficiently – make the method reliable, consistent and specify a standard period of time. 3.  Take action according to the data – once you have collected the data, make it effective by analyzing the data and using it for improvement. Have an improvement action as a result of the collection process. 4.  When establishing a basis for collecting data, be sure to ask and answer the What, When, Where, How & Who questions mentioned above. There are a large variety of Quality Tools and Statistical Process Control Methods (SPC) within the realm of Total Quality Management. We are, however, going to only concern ourselves with 7 Basic Quality Tools within this web site. They are: Check Sheets Pareto Diagrams Histogram Diagram Cause-and-Effect or "Fishbone" Diagram Scatter Diagrams Control Charts NP Charts

One Last Important Concept

We have considered the importance of Team Dynamics and the relevance of Data Collection. You now have the basic underlying concepts of how to approach your production problems, and should be ready to begin learning what the "7 Basic Quality Tools" are to help you improve your Production Processes and Product Quality. There still needs to be a methodology to your actions, however. You should not just learn these tools, assemble a team, analyze the problem and then blindly go out and "slay dragons"! The recommended course of action is to follow what is called the "DEMING CYCLE".  This cycle is summarized in four basic words: PLAN, DO, CHECK and ACT.  Deming later changed this to the PLAN, DO, STUDY, and ACT cycle.  Basically, the PDSA cycle is: PLAN - Brainstorm your problem areas, then plan out what actions should be taken. DO - Take those actions decided upon and implement them. Put them into action, don't wait! STUDY THE RESULTS!! Frequently monitor and check on the actions you implmented. The actions may need "tweaking", they may be totally wrong and you will need to rethink the process, or you may have success. ACT - Once you have the results of your actions implemented, ACT upon them. If they are wrong, reassemble the team and come up with another solution, and begin the PDCA cycle all over again. If the actions taken are right, then validate them, put them into permanent action. If they are partially successful, then reassemble the team and decide how needs to be done further. What adjustments need to be made to make the action work 100% Repeat the cycle over and over until you have 100% success. YOU ARE NOW READY TO BEGIN YOUR LESSONS ON THE 7 BASIC QUALITY TOOLS - CLICK HERE TO GET STARTED.
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Lesson #3 - Data Collection “There is Data All Around Us - Our Job is to Analyze It!”
The Quality Web
© The Quality Web, authored by Frank E. Armstrong, Making Sense Chronicles - 2003 - 2016

WHY DATA COLLECTION IS IMPORTANT

Within any manufacturing environment, product information or "data" is collected for a variety of reasons. Some of the common reasons for having this data are: 1.  Data to assist in understanding the actual process or situation. 2.  Data for product analysis. 3.  Data for process control (SPC). 4.  Data for regulation – a basis for raising or lowering a data standard, for example, temperature or thickness. 5.  Acceptance or rejection data – used to approve or reject products or parts. The purpose of collecting data is usually to gather information about the product or to follow up with some form of action. That is, after evaluating the actual conditions revealed by the data, some form of proper action should be taken. The first major critical step, however, is to ensure that the data represents typical conditions, or is data taken from normal circumstances. The second major critical step is to have a purpose for collecting the data. Therefore, before we actually collect data, we should ask the following questions: 1.  Define What we are measuring and Why are we measuring this information? 2.  Define Where and When should we measure this information? 3.  Define How should we be measuring this information and at what time intervals? 4.  Define What measurement tool? 5.  Define Who should be measuring this information? Data can be collected in many ways, depending upon the reason for the data, and the type of information we are seeking. Thus, data can be basically divided into two main groups: 1.  Measurement data: continuous data of length, weight, time, torque, etc. 2.  Countable data: enumerate data such as the number of defectives, percentage defective, number count of each defect, etc. Once we collect this data, it should be analyzed, and the information extracted through the use of statistical methods. For that reason, data should be collected and organized in such a way as to make data analysis more simple and meaningful. Therefore, you need to clearly record the nature of the data collected. You should also record the purpose of the measurements and their characteristics; the date; the instrument or method of measuring; the person performing the measurement; and any other pertinent information to the collection process. To properly record this data, you need to have a consistent time period, for example, measured every hour or every two hours, and make sure you are measuring production parts. In the case of collecting data to count defects, ensure you count each and every item produced, as well as the defects, during the collection period so you can compare how many defects were produced in relation to the total production of parts. Let us now summarize our data collection steps: 1.  Clarify the purpose of collecting the data – it is useless if there is no real reason to collect the data. 2.  Collect data efficiently – make the method reliable, consistent and specify a standard period of time. 3.  Take action according to the data – once you have collected the data, make it effective by analyzing the data and using it for improvement. Have an improvement action as a result of the collection process. 4.  When establishing a basis for collecting data, be sure to ask and answer the What, When, Where, How & Who questions mentioned above. There are a large variety of Quality Tools and Statistical Process Control Methods (SPC) within the realm of Total Quality Management. We are, however, going to only concern ourselves with 7 Basic Quality Tools within this web site. They are: Check Sheets Pareto Diagrams Histogram Diagram Cause-and-Effect or "Fishbone" Diagram Scatter Diagrams Control Charts NP Charts

One Last Important Concept

We have considered the importance of Team Dynamics and the relevance of Data Collection. You now have the basic underlying concepts of how to approach your production problems, and should be ready to begin learning what the "7 Basic Quality Tools" are to help you improve your Production Processes and Product Quality. There still needs to be a methodology to your actions, however. You should not just learn these tools, assemble a team, analyze the problem and then blindly go out and "slay dragons"! The recommended course of action is to follow what is called the "DEMING CYCLE". This cycle is summarized in four basic words: PLAN, DO, CHECK and ACT.  Deming later changed this to the PLAN, DO, STUDY, and ACT cycle.  Basically, the PDSA cycle is: PLAN - Brainstorm your problem areas, then plan out what actions should be taken. DO - Take those actions decided upon and implement them. Put them into action, don't wait! STUDY THE RESULTS!! Frequently monitor and check on the actions you implmented. The actions may need "tweaking", they may be totally wrong and you will need to rethink the process, or you may have success. ACT - Once you have the results of your actions implemented, ACT upon them. If they are wrong, reassemble the team and come up with another solution, and begin the PDCA cycle all over again. If the actions taken are right, then validate them, put them into permanent action. If they are partially successful, then reassemble the team and decide how needs to be done further. What adjustments need to be made to make the action work 100% Repeat the cycle over and over until you have 100% success. YOU ARE NOW READY TO BEGIN YOUR LESSONS ON THE 7 BASIC QUALITY TOOLS - CLICK HERE TO GET STARTED.
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