The above figure shows a layer-wise approach toward the roadmap of digital maturity and Industry 4.0. It is all about smart use of data which can bring success.
Computerization/automation -> Connectivity -> Data consolidation/visibility -> Analysis/root cause -> Predictability -> Decision Making
Computerization/automation: Automation is an integral part of manufacturing industries. However, the systems have various compositions – legacy to smart device. Connecting does not follow a single rule. On one hand, smart devices can be connected to a Platform using a Unified Architecture. For e.g. OPC UA, other side legacy devices require retrofitting of sensors/connectivity module. This is the first step of IoT enablement to derive the strategy of data collection from field equipment.
Connectivity: This layer does the job of field data consolidation. It is very important that data collected through various protocols from a heterogeneous field and control devices are converted to a unified format. An area that is piquing everybody’s interest in the industry is Edge Analytics. Small foot print Analytics running in the Edge/Gateway devices and finite data storage in Edge helps production managers and operators to take decisions faster.
Data consolidation/visibility: Until now, we talked about data collection from field assets. The manufacturing industry has various OT application, which mostly work in silos. Production employees have a deep understanding of processes and products in their respective work areas. Generally, knowledge exchange beyond their department boundaries is quite uncommon as a culture. To make holistic decisions of operations and production, integration of various production processes is quite important. Modelling of processes and assets and their interaction will help to achieve an integrated system landscape.
Analysis/root cause: Traditional businesses have mature process to handle supply chain, operations, maintenance etc. However, due to a lack of real-time data visibility on assets, processes and their interactions, there is a substantial amount of latency in event detection, root cause analysis, decision-making and action. Industry 4.0 will help companies become more agile and faster in decision-making and troubleshooting. It also helps to align various departments of functions to interact in analysis and decision-making.
Predictability: Until today, forecast in the industry largely depended on people’s knowledge and experience. To bring agility in production processes, forecast is essential. The Predictive Modelling helps in predicting and forecasting key performance indicators of assets and processes. Prediction helps in better planning, and scheduling and planning helps in improving production efficiency and reducing operational and maintenance costs.
Decision making: When all the data is at your disposal, trend and forecast of key performance KPIs as well as an integrated view of the assets, process and their interactions is in place, decision-making becomes much faster.
The Risk of “No-Change”
Digitization will help manufacturers achieve meaningful differentiation. If they opt for “no change”, they will be out of the race. The tilt toward Industry 4.0 has been noticed across the entire industry. It is the compelling need in today’s world. Consumers can decline digitization but an industry cannot. They run the risk of obsoleting themselves.
Large organizations like PTC, Microsoft, GE, Siemens, AWS are investing to build industry-ready platforms –analytics, machine learning, digital twin, AR/VR etc. to enable Industry 4.0. Semiconductor companies – Intel, Cisco, Dell etc. are evolving with new, secure and robust industrial products to complement the rapid industry need.
The digitization / IoT journey of manufacturing Industry can provide many benefits.
- Brings IT-OT convergence
- Prevention of loss of production
- Reduces downtime
- Improves machine's utilization, OEE calculation (Overall equipment effectiveness)
- Early detection of equipment failure.
- Production Optimization and Improvements
- Improve Quality.
- Real-time visibility of Plant and Production
- Effective resource utilization
- Predictive and Preventive Analytics
Digital, agile businesses outperform traditional businesses. For your company’s success, it‘s important to learn and adopt faster than others.
Gartner Report: Best Practices for Integrating IoT-Connected Products.
Reference Architectural Model Industrie 4.0 (RAMI 4.0)