End-to-end traceability of materials

• SMT leveraged AWS Greengrass to deploy IATM middleware components (local webapp, middleware service, PostgreSQL) at the edge, enabling local processing, filtering of RFID Tags data, secure communication with cloud and remote monitoring, collecting middleware logs from AWS CloudWatch remotely
• Amazon MQ ensured reliable, low-latency communication between on-prem middleware and cloud backend services for event notifications and workflow automation. Amazon MQ used to collect Asset tracking data from IATM Device Middleware and inter-service communication for shock absorber, loose coupling and performance improvement
• Amazon SQS/SNS is used along with SQS, a Lambda function to subscribe to a topic to publish data and communicate between IATM services and Notification Lambda to trigger the email notification, etc.

Real-time location system (RTLS)

• Pallets, totes, material boxes and containers were tagged with RFID passive Tags and tracked through RTLS-IATM solution
• Amazon Event Bridge used to run a scheduler job and call API business logic to trigger Notification emails and publish data to the customer system at regular intervals, e.g., transfer of materials, requisition delivery details
• AWS Lambda-powered serverless services used for the deployment of authorization, reconciliation and notifications ATM components, ensuring seamless and scalable operations

Inventory visibility and reporting

• Amazon RDS Aurora (PostgreSQL) was the central data store for WIP, asset and inventory data across manufacturing zones. All the IATM backend microservices, e.g., AssetMgmt, SmtAsset, UserMgmt, etc. using RDS as backend data storage
• Amazon S3 was used to store application resources, images, pages and logs, while Amazon CloudFront accelerated content delivery to end users globally. S3 was also used to store and run the CF Template and transfer the Docker images to customer environments
• Interactive dashboards were built using APIs exposed through Amazon API Gateway, supported by AWS Lambda for authorization of requests and integration with ALB/NLB. Used to expose the IATM backend limited services API, which are accessible from the IATM Web application and Mobile application
• AWS ELB (Elastic Load Balancing), ALB and NLB are used to distribute the application load among multiple running IATM services and instances
• AWS Route 53 was used for Domain Name resolution

ERP and system integration

• SMT backend microservices were containerized and deployed on Amazon ECS and AWS Fargate for flexible, serverless compute. While AWS ECR used to store the SMT services Docker images
• A CI/CD pipeline was established using AWS CodeCommit, CodeBuild and CodeDeploy, ensuring automated deployments, version control and continuous updates in the development and QA environments
• AWS Direct Connect and VPN Gateway provided secure, low-latency connectivity between the client’s on-prem manufacturing plants and AWS-hosted services
• AWS CloudFormation was used to run the IATM cloud formation template to create the required Infrastructure, AWS services, resources and IATM APIs. On a need basis, Cloud Shell was used to run the AWS commands and the CF template

Security, compliance and monitoring

• Access controls were managed with AWS IAM, while AWS KMS ensured encryption keys management for RDS to encrypt the sensitive inventory and production data
• AWS VPC and private subnets isolate workloads, with NAT Gateway and Network ACLs providing controlled access. NACL is used to allow certain inbound ports, such as 443 and EC2, RDP ports, Amazon MQ MQTT ports 8883, etc.
• AWS CloudWatch and AWS X-Ray monitored system health, captured logs and traced end-to-end transactions
• AWS Config and CloudTrail tracked configuration changes and user activities, ensuring compliance and audit readiness
• AWS Certificate Manager secures web applications with SSL/TLS certificates, while AWS WAF protects against external threats
• AWS Parameter Store was used to store the backend micro-services, Lambda functions, application properties (key-value) and secret keys for the application/services
• AWS Systems Manager uses a need-based approach for accessing EC2 instances from a browser and for Patch management
• Amazon EC2 (Windows, Linux), EFS was used for additional compute resources and storage requirements, for example, a jump box, Windows RDP machine for testing purposes
• Other AWS Supporting services, such as AWS Cost Explorer and Calculator, wereused to check, visualize, and analyze the cost of AWS resources over time. Calculators are used to calculate the cost of different AWS services and compute. It helped in comparing, decision making, planning and overall cost optimization