Manufacturing companies have invested significantly in plant automation on their shop floors. But there is still a large gap in using data to improve equipment functionality and operational performance as well as create new insights. Utilizing cloud technologies like powerful analytic tools, machine-learning algorithms, and AI on AWS brings out these insights and leverages existing PLC investments.

This AWS based IIoT solution can be leveraged to establish an Industry 4.0 strategy and foundation which will provide the following:

• Connect machine data from PLC to the cloud by installing and configuring an edge gateway. This is an additional service provided as part of this offering outside of the AWS environment
• Provide near real time OEE/OPE metrics to executives and plant supervisors.
• Provide a foundation and framework for connecting multiple plant locations to the cloud

The complete end-to-end solution from the manufacturing floor to the executive offices will require the following major components:

• PLCs on the manufacturing floor. The solution can support multiple PLCs like Allen Bradley, Brankamp, Siemens, Rockwell etc.
• AWS based connectivity, data gathering, storage, and visualization. This component is provided by this service offering and will utilize the following AWS Services:
  • AWS IoT Core
  • Amazon Athena
  • Amazon S3 buckets
  • Amazon Kinesis
  • Amazon CloudWatch
  • AWS Managed Grafana

This solution can be used to accomplish any or all of the following:

• Data strategy/plant automation/data modernization for digital transformation. This is the overarching industry 4.0 strategy. Connected machinery, sensors that will generate data which can then be used to automate tasks.
• Global plant and equipment efficiency analysis in near real-time. OEE/OPE measurement by plant will be used to measure quality, performance, and reliability of equipment in near real-time. This information will speed up decision making ability.
• Equipment downtime analysis and predictive maintenance. Downtime analysis can be used to measure shift effectiveness, supervisor actions on machine setup, troubleshooting, training operators, etc.
• Raw material grade/production analysis for supply chain. Product defects can be easily traced to raw materials and metallurgy analysis, machine technical issues.
• With readily available data, the business can innovate faster on new methods, products, etc. Machine twins for automating line tasks and simulation of production line changes.