This article is about answer of possible problem or question in i-Insuline Project view of Quality Management process.
1-) Which quality standard do you use in your project and why?
Our project I-insulin is about diabetic patients, and the healthcare industry. That is why we are using FDA(Food and Drug Administration), DTSec(Diabetes Technology Society) quality certificate. And also, other parts of our project consist of AI, data security. That is why we choose ISO 9001, ISO27001(information security) quality certificate for the I- insulin project.
2-) What is the cost role in a quality management plan, can you give an example in your project?
Our mentality is the cost of avoiding mistakes is less than the cost of correcting them.
Total cost of quality can be calculated by:
1- Prevention Cost:(training, time to do it right)
2- Appraisal Cost:(testing, inspections)
3- INT/EXT Failure Cost:(rework, lost business)
4- Total cost=P+A+IF+EF
Our i-Insulin project is based on human health, that is why quality is vital for us. Because any mistake in this project can cause a huge health problem for humans(patients). As a result, quality is an important part for us in this project. Like all other health care projects, we put quality before cost. For example, we are planning to use 1 million parameters for AI, this will increase our cost. However, these parameters will give us more accurate results.
3-) How do you control the quality?
In our case the qualitative results will be monitored, internally, by the quality manager and, externally, by health care providers. To ensure that the results are matched to the quality standards chosen by us and required by the Italy. (FAND-Italian Diabetic Association) and EU regulations(ECDC-European Centre for Disease Prevention and Control).
4-) What is the acceptable quality tolerance and how did you decide?
According to recent research papers, the accuracy of AI in the medical industry reaches 72-81%. In our project, the risk probability of software error is not high, but impact of software error is very high. That is why, we set a little bit higher accuracy aim in our project, and it’s 92%.
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