Overview:

Our client, an Indo-German company operating in the Industry 4.0 domain, is renowned for their expertise in domain knowledge, technology, and process orientation. They required a SaaS- based product to monitor key machine parameters such as Overall Equipment Efficiency (OEE) and other Key Performance Indicators (KPIs). They needed a solution that would provide real-time data visualization and analysis, facilitate asset and device provisioning, and allow for hierarchical configuration. Applied Cloud Computing Pvt. Ltd (ACC), an AWS SaaS solution provider, was chosen to develop and deliver this solution.

Problem Statement:

Our client faced real-time challenges in monitoring and analyzing key machine parameters.They lacked a centralized system to track OEE, downtime analysis, condition-based monitoring, energy management, and cycle time adherence. The existing methods were time-consuming,inefficient, and lacked a visually appealing dashboard for senior management. Hence the client wanted to revamp the system.

Why ACC?

ACC was selected as the preferred partner due to its expertise in delivering SaaS-based solutions and its ability to leverage AWS services. With a focus on UI/UX and a track record of successful implementations, ACC was well-equipped to address Our client’s requirements. ACC’s comprehensive approach to system configuration, data visualization, and security aligned perfectly with Our client’s needs.

Solution | Architecture & Services

ACC developed a SaaS-based product, Smart Gate, to address Our client’s requirements for real-time monitoring and analysis of key machine parameters. The solution offered a visually appealing dashboard with map views, image views, line graphs, dial gauges, and pie charts. It allowed hierarchical configuration from customers to locations, lines, and assets. ACC leveraged several AWS services for hosting, storage, database management, monitoring, authentication, visualization, device provisioning, and serverless computing. The solution provided scalability, seamless integration, and mobile accessibility.

AWS Services used:

Amazon EC2 (Elastic Compute Cloud): Utilized for hosting the SaaS application and managing the backend infrastructure.

Amazon S3 (Simple Storage Service):Employed for storing and retrieving configuration data, machine parameters, and user profiles.

Amazon RDS (Relational Database Service): Utilized for efficient database management, ensuring data consistency and reliability.

Amazon CloudWatch: Configured to monitor the application’s performance, generate alerts for anomalies, and track downtime.

Amazon API Gateway:Used to create APIs for data transfer between the frontend, backend, and mobile app.

Amazon Cognito:Implemented for user authentication, login, and role-based access control.

Amazon QuickSight:Integrated for creating visually appealing dashboards with map views, image views, line graphs, dial gauges, pie charts, and tables.

AWS IoT Core:Leveraged for device provisioning, data ingestion, and real-time monitoring of sensors and devices.

AWS Lambda:Utilized for serverless computing, enabling ad hoc dashboard creation and dynamic tag addition without touching the database

Outcome:

By partnering with ACC and implementing the Smart Gate SaaS solution, our client achieved significant outcomes. The solution provided real-time monitoring and analysis of key machine parameters such as OEE and other KPIs. The visually appealing dashboard enabled senior management to gain valuable insights at a glance. Hierarchical configuration and role-based access ensured data security and appropriate access levels. The solution facilitated efficient downtime analysis, condition-based monitoring, energy management, and cycle time adherence. Users could drill down from a global level to a machine level for detailed analysis.
The scalable and future-ready architecture allowed for the easy addition of new tags without touching the database. Overall, the Smart Gate solution empowered Our client to optimize machine performance, make informed decisions, and improve operational efficiency