2 answers
2 answers
Updated
Isabel’s Answer
Hello Recee,
The term "human error in failure analysis" refers to the mistakes that people make while trying to figure out why a certain material or component didn't work as expected. These errors can happen when data is collected incorrectly, when test results are misunderstood, when important evidence is missed, or when personal bias affects judgment. In the field of materials science and engineering, such errors can distort our understanding of why the failure occurred, leading to inappropriate suggestions on how to avoid similar problems in the future. To reduce the chances of human error, we need to be very careful about quality control. This includes sticking closely to scientific methods, keeping accurate records, getting our work checked by others, and continually training to improve our skills. This way, we can ensure our analysis results are accurate and dependable.
The term "human error in failure analysis" refers to the mistakes that people make while trying to figure out why a certain material or component didn't work as expected. These errors can happen when data is collected incorrectly, when test results are misunderstood, when important evidence is missed, or when personal bias affects judgment. In the field of materials science and engineering, such errors can distort our understanding of why the failure occurred, leading to inappropriate suggestions on how to avoid similar problems in the future. To reduce the chances of human error, we need to be very careful about quality control. This includes sticking closely to scientific methods, keeping accurate records, getting our work checked by others, and continually training to improve our skills. This way, we can ensure our analysis results are accurate and dependable.
Updated
Sasha’s Answer
Hello Recee,
It's thrilling to know you're interested in Material Science and Engineering.
Pointing to human error as the primary cause is a common way to overlook deeper issues, and sadly, it occurs more frequently than it should. Over-reliance on human error as the main cause is counterproductive as it initiates a blame game that can harm your company's quality culture. Worse still, the real problems may go unresolved, leading to repeated issues.
The key stakeholders involved in examining the specific defect or failure usually form a cross-functional team. This team identifies potential root causes through brainstorming. Tools such as the Ishikawa Diagram (Fishbone diagram), Five Whys Technique, Failure Mode Effect Analysis, Fault Tree Analysis, and Risk Ranking often aid in performing a clear root cause analysis.
What lies beneath human error?
Root cause analysis (RCA) involves following your line of thinking until no more questions arise. Your thought process should halt only when you find a direct link to the problem. Labeling an issue as 'human error' often leaves some challenging questions unresolved. Digging deeper into these issues can reveal systemic flaws.
Consider a simple example of a parallax error that happens when two scientists measure a liquid's volume using a measuring cylinder. The error might happen because one scientist measures the volume by observing the lower meniscus, while the other measures the upper meniscus. It's easy to label this as 'human error,' but the real issue could be systemic, like the absence of a standard operating procedure specifying which meniscus to measure for a particular liquid.
In FDA-regulated manufacturing, you're expected to not only identify causes but also eliminate them through appropriate Corrective and Preventive Actions. Labeling the issue as 'human error' without addressing it denies the chance to enhance your quality management system. Frequent 'human error' issues suggest that your quality management relies on individuals rather than the system. Such systemic flaws could be the hidden villains in many FDA-regulated situations.
It's crucial to objectively investigate causes labeled as human error using human factors engineering and cognitive psychology models like the Skills, Rules, Knowledge (SRK) framework. This framework helps understand how people perform tasks and make definitive decisions.
While investigating, try to gather more information about the following topics:
- Procedures
- Employee training
- Quality control
- Communications
- Human engineering
- Work direction
- Management systems
Most importantly, identifying 'human error' as the root cause doesn't conclude the matter; it's merely the starting point. Our duty is to build a sturdy system that prevents 'human error' from happening initially. The aim of corrective actions is to diminish or eradicate human error or to enhance system reliability by making errors less likely or easier to detect and correct before an incident occurs.
I hope you find this information useful. Good luck!
It's thrilling to know you're interested in Material Science and Engineering.
Pointing to human error as the primary cause is a common way to overlook deeper issues, and sadly, it occurs more frequently than it should. Over-reliance on human error as the main cause is counterproductive as it initiates a blame game that can harm your company's quality culture. Worse still, the real problems may go unresolved, leading to repeated issues.
The key stakeholders involved in examining the specific defect or failure usually form a cross-functional team. This team identifies potential root causes through brainstorming. Tools such as the Ishikawa Diagram (Fishbone diagram), Five Whys Technique, Failure Mode Effect Analysis, Fault Tree Analysis, and Risk Ranking often aid in performing a clear root cause analysis.
What lies beneath human error?
Root cause analysis (RCA) involves following your line of thinking until no more questions arise. Your thought process should halt only when you find a direct link to the problem. Labeling an issue as 'human error' often leaves some challenging questions unresolved. Digging deeper into these issues can reveal systemic flaws.
Consider a simple example of a parallax error that happens when two scientists measure a liquid's volume using a measuring cylinder. The error might happen because one scientist measures the volume by observing the lower meniscus, while the other measures the upper meniscus. It's easy to label this as 'human error,' but the real issue could be systemic, like the absence of a standard operating procedure specifying which meniscus to measure for a particular liquid.
In FDA-regulated manufacturing, you're expected to not only identify causes but also eliminate them through appropriate Corrective and Preventive Actions. Labeling the issue as 'human error' without addressing it denies the chance to enhance your quality management system. Frequent 'human error' issues suggest that your quality management relies on individuals rather than the system. Such systemic flaws could be the hidden villains in many FDA-regulated situations.
It's crucial to objectively investigate causes labeled as human error using human factors engineering and cognitive psychology models like the Skills, Rules, Knowledge (SRK) framework. This framework helps understand how people perform tasks and make definitive decisions.
While investigating, try to gather more information about the following topics:
- Procedures
- Employee training
- Quality control
- Communications
- Human engineering
- Work direction
- Management systems
Most importantly, identifying 'human error' as the root cause doesn't conclude the matter; it's merely the starting point. Our duty is to build a sturdy system that prevents 'human error' from happening initially. The aim of corrective actions is to diminish or eradicate human error or to enhance system reliability by making errors less likely or easier to detect and correct before an incident occurs.
I hope you find this information useful. Good luck!