Quality Assurance and Compliance in AI-Driven Supply Chain
Expert-defined terms from the Professional Certificate in AI-Driven Pharmaceutical Supply Chain Management course at LearnUNI. Free to read, free to share, paired with a globally recognised certification pathway.
Artificial Intelligence (AI) #
the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction.
AI #
Driven Supply Chain: a supply chain that uses AI to optimize its operations, including demand forecasting, inventory management, and logistics. An AI-driven supply chain can make data-driven decisions, adapt to changing conditions, and learn from past experiences.
Compliance #
the state of conforming to specified rules, regulations, and practices. In the context of AI-driven supply chains, compliance refers to adhering to regulations and standards related to data privacy, security, and quality.
Data Privacy #
the protection of personal data, including sensitive information, from unauthorized access, use, and disclosure. Data privacy regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), establish rules for the collection, storage, and use of personal data.
Data Security #
the protection of data from unauthorized access, use, and disclosure. Data security measures include encryption, access controls, and network security.
Deep Learning #
a subset of machine learning that uses artificial neural networks with many layers to learn and make decisions. Deep learning models can learn complex patterns and representations from large datasets.
Demand Forecasting #
the process of estimating future demand for a product or service. Accurate demand forecasting is critical for inventory management and supply chain planning.
Machine Learning (ML) #
a subset of AI that uses statistical techniques to enable machines to improve with experience. Machine learning models can learn patterns and make predictions based on data.
Neural Networks #
a type of machine learning model inspired by the structure and function of the human brain. Neural networks can learn complex patterns and representations from data.
Quality Assurance (QA) #
the process of ensuring that products or services meet specified requirements and standards. Quality assurance includes activities such as testing, inspection, and validation.
Quality Control (QC) #
the process of monitoring and controlling the quality of products or services. Quality control includes activities such as testing, inspection, and process control.
Regulations #
rules and guidelines established by governments or regulatory bodies. Regulations related to AI-driven supply chains include data privacy and security regulations.
Standards #
agreed-upon rules and guidelines established by industry groups or consensus bodies. Standards related to AI-driven supply chains include quality management and data exchange standards.
Supply Chain Management (SCM) #
the coordination and management of activities involved in the movement of goods and services from raw materials to end customers. SCM includes activities such as demand forecasting, inventory management, and logistics.
Inventory Management #
the process of planning, organizing, and controlling the flow of goods and materials in a supply chain. Inventory management includes activities such as demand forecasting, order management, and inventory optimization.
Logistics #
the planning, implementation, and control of the efficient, effective flow of goods, services, and related information from the point of origin to the point of consumption. Logistics includes activities such as transportation, warehousing, and distribution.
In conclusion, this glossary provides a comprehensive list of terms, concepts, a… #
Understanding these terms is crucial to successfully managing and optimizing AI-driven supply chains. By adhering to regulations and standards, implementing quality assurance and control processes, and effectively managing inventory and logistics, organizations can improve their supply chain performance and better meet the needs of their customers.