Smart Manufacturing: Making Smarter Decisions with Data

What is smart manufacturing?

Manufacturing that improves performance by enabling the integrated and intelligent use of resources and processes across the cyber, physical, and human spheres.

Today, manufacturing is a hypercompetitive environment shaped by rapid change, rising supply chain disruption, and tough customer and regulatory demands. Organizations need coordinated operations across cyber-physical systems – with full data availability, maximum efficiency, and constant real-time availability.

 

 

What are key technologies for smart manufacturing?

Smart manufacturing requires every industrial asset or part of the system to have its own identity (IP address) and wireless connectivity. Individual devices are equipped with intelligent sensors for transmitting key information (data) to central data management on site or in the cloud. Control devices like smart actuators also enable an automated, remote response to high-level decisions.

A consolidated set of technologies and integrated digital infrastructure are key elements of smart manufacturing. Companies need data from all sources in one place. Cutting-edge visualization and analytics make a strategic big picture possible. Edge computing provides a secure data buffer between local sites and the internet or cloud, while AI and machine learning facilitate research, analysis, and automated operations.

Smart manufacturing paves the way for many operational improvements, such as preventive maintenance and predictive analytics. The benefits of optimized efficiency and resource management help today’s manufacturers meet progressively tougher sustainability obligations.

Because smart manufacturing increasingly involves complex, interconnected systems as well as critical assets, safety and security are extremely important. Blockchain technology promises considerably higher security as well as smart automation potential. Good data architecture and design, AI, and advanced robotics can be used to prevent accidents or conduct emergency factory shutdowns remotely. With the help of drones and AR/VR modeling, manufacturers can keep humans away from dangerous areas or tasks. A core smart manufacturing technology is the digital twin, which is covered in more detail below.

What are some examples of smart manufacturing?

Successful smart manufacturing is not only a matter of technology. It places higher demands on company culture, staff skill sets, and ecosystem partners. Here are some examples of how this multilayered approach can work:

1.) Seamless integration of systems and operations

Traditional manufacturing challenges include legacy systems, operational silos, resource inefficiency, and fragmented control. All of these point to the core task of smart manufacturing: connecting the organization (and ecosystem) as a seamless 360° whole. To achieve this, many organizations are moving to more open, modular, and secure solutions and to IT/OT convergence.

Smart manufacturing is also holistic at the human and operational levels. The lack of a skilled workforce is currently a serious problem. Integrated operations offer a powerful, comprehensive answer. This includes providing global HR transparency, concentrating expertise at the enterprise core, and shifting toward remote plant operation. Yokogawa’s approach to smart manufacturing and digital transformation embodies the integrated operations approach.

2.) The digital twin: A core technology for smart industry

A digital twin uses actual data to create a parallel, real-time virtual model of entire plants and systems. This enables manufacturers to accurately test planned changes or possible scenarios in a safe virtual environment. The digital twin is also a powerful foundation for workforce training and continuous optimization. In supply-chain management, for example, it also enables the automation of tasks such as blend property and ratio control. Digital twins enable real-time optimization across the entire plant and beyond. This includes total energy optimization and continuous emission monitoring. This benefits the entire community by reducing CO2, saving energy costs, and providing energy security, making the digital twin a key sustainability tool.

Key Elements for Smart Manufacturing; Information Integration and Digital Twins allow organizations to benefit from the latest technologies

3.) Granular case study: Asset failure prediction

Manufacturers often struggle to identify potential failures, prevent labor shortfalls, and transition from reactive to proactive maintenance. High costs make it difficult to ensure an adequate number of sensors, and companies struggle when it comes to leveraging their data.

Fortunately, high-performance IIoT sensors offer a powerful foundation. Companies can visualize this sensor data on proactive dashboards to provide actionable insights to operators. They can also use it to simulate potential failures via predictive analytics.

The results include substantial improvements in plant availability (+20%), maintenance costs (-40%), and workplace safety and efficiency (+30%).

Conclusion

Smart manufacturing combines the benefits of cyber-physical systems, automation, big data, smart analytics, predictive modeling, and cultural innovation. For manufacturers, it is the goal of a demanding journey. Fast movers can secure a competitive advantage now and remain relevant tomorrow.

Learn more

Websites

Read here more about Smart Manufacturing and the Smart Manufacturing Methodology by Yokogawa.

Whitepaper

Brochure

Video

Watch this video about "The Evolution of Industrial Automation"