Fast facts on smart manufacturing

How Industry 4.0 can help enhance overall efficiencies and deliver across-the-board gains?

Infrastructure
One of the core elements of digital manufacturing is the use of data sensors in the machines, capturing the data and use of cloud-based applications for data storage and analytics.

The model seeks to determine the level of deployment of the embedded sensors and use of analytics in areas such as

- Manufacturing processes

- Enterprise Asset Management (EAM)

- Enterprise Resource Management (ERP)

- Reporting systems

- IT integration

- Monitoring workplace/shopfloor safety

- Data security

Operations
The dominant use of smart manufacturing tools is in core manufacturing operations. The maturity model evaluates the extent of adoption of these tools in operations such as:

- Plant layout — simulation and optimisation

- Design for Manufacturability (DfM)

- Design for Quality (DFQ)

- Product design modelling, simulation and validation

- Level of automation in manufacturing processes

- Metrics-based data – translation to organizational knowledge.

- Looping of sensor data for quality / yield optimisation and resolutions.

Supply chain and logistics
A key feature of Industry 4.0 frameworks is integrating
the supply chain and related information with customers and suppliers. The maturity model identifies these linkages through:

- Integration and alignment  of information flow with customers and suppliers

- Reporting of supply chain activities to internal/external stakeholders enabling real-time decision making

- Digitisation of warehousing operations

- Use of collaborative tools with suppliers, customers

- Creation of traceability chains up to component /
part level.

(This article was first featured in the October 15, 2019 issue of Autocar Professional)