How Industry 4.0 can help enhance overall efficiencies and deliver across-the-board gains?
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
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 /
(This article was first featured in the October 15, 2019 issue of Autocar Professional)