Assignable cause
| Assignable cause |
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| See also |
Assignable causes of variation have an advantage (high proportion, domination) in many known causes of routine variability. For this reason, it is worth trying to identify the assignable cause of variation, in such a way that its impact on the process can be eliminated, of course, assuming that project managers or members are fully aware of the assignable cause of variation. Assignable causes of variation are the result of events that are not part of the normal process. Examples of assignable causes for variability are (T. Kasse, s.237):
- incorrectly trained people
- broken tools
- failure to comply with the process
Identify data of assignable causes
The first step you need to take when planning data collection for assignable causes is to identify them and explain your goals. This step is to ensure that the assignable causes data that the project team gathers provides the answers that are needed to carry out the 'process improvement' project efficiently and successfully. The characteristics that are desirable and most relevant for an assignable causes are for example: relevant, representative, sufficient. In the planning process for collecting data on assignable causes, the project team should draw and mark a chart that will provide the findings before actual data collection begins. This step gives the project team an indication of what data that can be assigned is needed (A. van Aartsengel, S Kurtoglu, s.464).
Types of data for assignable causes
There are two types of data for assignable causes, qualitative and quantitative. Qualitative data is obtained from deseriography resulting from observations or measures of different types of characteristics of the results of the process in terms of narrative words and statements. However, the next group of data, which are quantitative data on assignable causes, are derived from the description of observations or measures of process result characteristics in terms of measurable quantity in which numerical values are used (A. van Aartsengel, S. Kurtoglu, s.464).
Determining the source of assignable causes of variation in an unstable process
If an unstable process occurs then the analyst must identify the sources of assignable cause variation. The source and the cause itself must be investigated and, in most cases, unfortunately also eliminated. Until all such causes are removed, then the actual capacity of the process cannot be determined and the process itself will not work as planned. In some cases, however, assignable cause variability can improve the result, then the process must be redesigned (W. S. Davis, D. C. Yen, s.76). There are two possibilities for making the wrong decision, which concerns the appearance of assignable cause variations: there is no such reason (or it is incorrectly assessed) or it is not detected (N. Möller, S. O. Hansson, J. E. Holmberg, C. Rollenhagen, s.339).
Examples of Assignable cause
- '* Poorly designed process': A poorly designed process can lead to variation due to the inconsistency in the way the process is operated. For example, if a process requires a certain step to be done in a specific order, but that order is not followed, this can lead to variation in the results of the process.
- '* Human error': Human error is another common cause of variation. Examples include incorrect data entry, incorrect calculations, incorrect measurements, incorrect assembly, and incorrect operation of machinery.
- '* Poor quality materials': Poor quality materials can also lead to variation. For example, if a process requires a certain grade of material that is not provided, this can lead to variation in the results of the process.
- '* Changes in external conditions': Changes in external conditions, such as temperature or humidity, can also cause variation in the results of a process.
- '* Equipment malfunctions': Equipment malfunctions can also lead to variation. Examples include mechanical problems, electrical problems, and computer software problems.
Advantages of Assignable cause
One advantage of identifying the assignable causes of variation is that it can help to eliminate their impact on the process. Some of these advantages include:
- Improved product quality: By identifying and eliminating the assignable cause of variation, product quality will be improved, as it eliminates the source of variability.
- Increased process efficiency: When the assignable cause of variation is identified and removed, the process will run more efficiently, as it will no longer be hampered by the source of variability.
- Reduced costs: By eliminating the assignable cause of variation, the cost associated with the process can be reduced, as it eliminates the need for additional resources and labour.
- Reduced waste: When the assignable cause of variation is identified and removed, the amount of waste produced in the process can be reduced, as there will be less variability in the output.
- Improved customer satisfaction: By improving product quality and reducing waste, customer satisfaction will be increased, as they will receive a higher quality product with less waste.
Limitations of Assignable cause
Despite the advantages of assigning causes of variation, there are also a number of limitations that should be taken into account. These limitations include:
- The difficulty of identifying the exact cause of variation, as there are often multiple potential causes and it is not always clear which is the most significant.
- The fact that some assignable causes of variation are difficult to eliminate or control, such as machine malfunction or human error.
- The costs associated with implementing changes to eliminate assignable causes of variation, such as purchasing new equipment or hiring more personnel.
- The fact that some assignable causes of variation may be outside the scope of the project, such as economic or political factors.
One of the approaches related to assignable cause is to identify the sources of variability that could potentially affect the process. These can include changes in the raw material, the process parameters, the environment, the equipment, and the operators.
- Process improvement: By improving the process, the variability caused by the assignable cause can be reduced.
- Control charts: Using control charts to monitor the process performance can help in identifying the assignable causes of variation.
- Design of experiments: Design of experiments (DOE) can be used to identify and quantify the impact of certain parameters on the process performance.
- Statistical Process Control (SPC): Statistical Process Control (SPC) is a tool used to identify, analyze and control process variation.
In summary, there are several approaches related to assignable cause that can be used to reduce variability in a process. These include process improvement, control charts, design of experiments and Statistical Process Control (SPC). By utilizing these approaches, project managers and members can identify and eliminate the assignable cause of variation in a process.
References
- Davis W. S., Yen D. C. (2019)., The Information System Consultant's Handbook: Systems Analysis and Design, CRC Press, New York
- Kasse T. (2004)., Practical Insight Into CMMI, Artech House, London
- Möller N., Hansson S. O., Holmberg J. E., Rollenhagen C. (2018)., Handbook of Safety Principles, John Wiley & Sons, Hoboken
- Van Aartsengel A., Kurtoglu S. (2013)., Handbook on Continuous Improvement Transformation: The Lean Six Sigma Framework and Systematic Methodology for Implementation, Springer Science & Business Media, New York
Author: Anna Jędrzejczyk
