Industry 4.0 adopted manufacturing architecture benefits

The benefits of Industry 4.0 adopted manufacturing architecture

?Adopt the Business Agility

Rather than the big monolith application, the architecture recommends building small fined grained microservices which are built around business capabilities. The architecture enables the manufacturing to archive business agility and responds to market changes by providing a cloud framework and platform to develop and deploy applications at scale while leveraging the DevOps and continuous integration / continuous delivery cycle.?When manufacturing has a new business or existing business is changing, the business capability team can quickly make a change to the manufacturing service they own or build new functionality and can quickly deploy to production without any dependency on the other teams. This massively speeds up development and go to market compared to the monolith approach which requires thorough testing of the system even for a small change.?

Manufacturing services are deployed using the CI/CD pipeline after going through automated unit tests, functional tests, and security scans. Manufacturing services are safely deployed using blue-green and canary deployment patterns, which allows deployment and rollbacks during business hours without business interruption.?

Manufacturing services are stateless by design while keeping immutable infrastructure in mind. These services can be scaled up when demand grows or scaled-down when demand decreases.?

?Go to production fast

For a traditional manufacturing application, it should take months, or years to launch the changes to the production environment. Normally the change should go through the design, development, test, and pick up the deployment window in non-business hours with risky deployment.?The new architecture enables manufacturing lunch features into production faster. Through the DevOps method, the developer can see the changes go live after the code is check-in. The changes can be tested through the automated test in the instance which is duplicated from a production environment.?Changes get deployed to production through the Continue Integration/Continuous Deployment pipeline after passing through automated unit tests, function tests, integration tests, performance/stress tests, and security scans.

Transparency

In traditional manufacturing, the applications are a monolith, the data integration is a bottleneck of the system deployment since each application has itself standard or data format.

In industry 4.0 adopted manufacturing architecture, the message bus is used to push the data when the data is changed via publish/subscribe method. For example, during the machine shop floor downtime, the machine event is published to the message bus. The operator or manager will see on the screen the machine state is changed. The backend event triggers the maintenance order to be created and the email is sent to the maintenance team and supervisor. This message bus can integrate with the cloud event as well, like AWS's simple notification service (SNS). Manufacturing services interact with each other via published and versioned APIs. These APIs are typically RESTful APIs with JSON serialization, but other protocols and serialization formats are supported.?

The transparency afforded by Industry 4.0 technology provides operators with comprehensive information to make decisions. Inter-connectivity allows operators to collect immense amounts of data and information from all points in the manufacturing process, and identify key areas that can benefit from the improvement to increase functionality.

?Scale

Manufacturing Services in The adopted Industry 4.0 manufacturing architecture are designed to be stateless for scaling. Cloud-native infrastructure provides the scaling capability.?

The manufacturing can start the business from the NPI which has limited resources and service requirements. When the business is stable, the demand is increased, and the resource can be easily scale up.

Manufacturing Service can also be scaled up during the scheduled time when the team anticipates high demand, for example, when morning clicks in time.