Guidance for Semiconductor Supply Chain Resiliency Using SAP® on AWS
Overview
This Guidance demonstrates how to use SAP to integrate data from enterprise resource planning (ERP), manufacturing execution systems (MES), or product lifecycle management (PLM) into engineering and business intelligence dashboards on AWS. Data is collected from multiple sources, transferred to a data lake, prepared for analytics, and then integrated with a business insights dashboard for supply chain stakeholders to report, monitor, and optimize engineering operations.
How it works
These technical details feature an architecture diagram to illustrate how to effectively use this solution. The architecture diagram shows the key components and their interactions, providing an overview of the architecture's structure and functionality step-by-step.
Well-Architected Pillars
The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.
Operational Excellence
The QuickSight dashboard provides the actionable insights required to quickly react to changes in supply and demand, and enables yield management across the entire semiconductor supply chain.
Security
For secure authentication and authorization, customers can implement federated AWS access to directory services on-premises and use AWS Directory Service. Authentication and authorization can be used across the entire architecture, from the remote desktop to running batch jobs.
Reliability
By leveraging AWS IoT Core services, customers are leveraging secure connections between devices and the AWS Cloud. AWS IoT Core services use highly reliable, messaging queuing telemetry transport (MQTT) for the data input from third-party partners. Therefore, temporary transfer issues should be minimized or even eliminated.
Performance Efficiency
The services in this Guidance were selected to ensure compatibility for hi-tech, electronics, and semiconductor customers. Many of these companies have MES/PLM/ERP applications, and the services selected enable data integration from each of those applications.
Cost Optimization
Companies can save time and cost when using AWS Glue for data integration. AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it simple and cost-effective to categorize data, clean it, enrich it, and move it reliably between various data stores and data streams.
Sustainability
By taking a microservices approach coupled with AWS managed serverless services, this Guidance allows customers to limit the amount of infrastructure they needed to provision.
Disclaimer
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