Context
Introduction
The pharmaceutical industry faces mounting concerns over the safety and oversight of medications produced through global supply chains, especially with growing reliance on Chinese manufacturing. https://en.wikipedia.org/wiki/Pharmaceutical_industry_in_China?utm_source=chatgpt.comhttps://prosperousamerica.org/china-owns-americas-generic-drug-supply-chain-u-s-china-commission-says/?utm_source=chatgpt.comhttps://www.uscc.gov/sites/default/files/2019-11/Chapter%203%20Section%203%20-%20Growing%20U.S.%20Reliance%20on%20China%E2%80%99s%20Biotech%20and%20Pharmaceutical%20Products.pdf?utm_source=chatgpt.com
Role
• The learner steps into the role of a Quality Assurance Analyst at MedSafe Pharma.
• They are responsible for analyzing defect incidence data, detecting patterns that suggest compromised manufacturing practices, and flagging high-risk production batches.
Business Objectives
• The task is to analyze defect patterns in pharmaceutical components to identify risk signals and inform supplier audits or production adjustments.
• The learner’s analytical skills and understanding of manufacturing metrics enable them to detect meaningful trends in defect types, frequencies, and correlating factors
Products
• The deliverable is a concise report and visual summary of defect analysis, highlighting high-risk production lines, temporal trends, and supplier recommendations.
• This product demonstrates how defect detection insights can support informed quality control and supply chain resilience.
Codebook
Columns:
• defect_id: Unique identifier for each defect.
• product_id: Identifier for the product associated with the defect.
• defect_type: Type or category of the defect (e.g., cosmetic, functional, structural).
• defect_description: Description of the defect.
• defect_date: Date when the defect was detected.
• defect_location: Location within the product where the defect was found (e.g., surface, component).
• severity: Severity level of the defect (e.g., minor, moderate, critical).
• inspection_method: Method used to detect the defect (e.g., visual inspection, automated testing).
• repair_action: Action taken to repair or address the defect.
• repair_cost: Cost incurred to repair the defect (in local currency).
Dataset
License
Not Provided
Tags
Data Provenance
