Technologies for the Factory of the Future

To future-proof manufacturing, drive profits and serve customers, organizations must examine supply chains, sustainability, digital transformation and more 

TAKEAWAYS:
● The foundation for manufacturing’s future is data and organizations’ ability to effectively capture and use data in every factory element.
● Manufacturers need to think beyond operations when they apply Manufacturing 4.0 so that they also evolve their supply chains and sustainability efforts.
● AI/ML and virtual tools can have big effects that can be amplified with collaboration, optimization and continuous improvement.  

Globally, manufacturers are experiencing growing pressure to reduce carbon emissions in their production processes. The manufacturing industry is characterized by disruptions and volatility, supply chain problems, upcoming inflation, and increased financial costs, making it paramount that manufacturers find innovative solutions to face the challenges ahead.

Sustainability issues and digital transformation have become the main drivers for the next three to five years and that will shape the future of the manufacturing industry towards 2030. These trends drive the necessity of true innovation further. Even though there has been plenty of focus on buzzwords like Industry 5.0 and similar, this is now becoming a reality. The path forward is clear: manufacturers must engender greater resilience and future readiness by optimizing resource usage, minimizing waste, and embracing renewable energy sources. However, the difficulty lies in simultaneously ensuring profitable operations.

Embrace the Future of Manufacturing Through Data

A key component in all the trends and challenges is data, like reliable data on environmental sustainability, traceability throughout the value chain and product life cycle, and real-time data to detect supply chain disruptions.

For manufacturing companies, emerging technologies help expand the opportunities to become a data-driven factory of the future. Using low-cost sensors and IoT, gathering data throughout the manufacturing process is now possible. With advanced AI and machine learning algorithms, organizations can enable predictive maintenance of expensive manufacturing machinery and reduce costs and downtime. Digital twins can enable virtual simulation of development, testing, and validation of products, and AR/VR can even let customers try products before they are made.

Implement Resilient Supply Chains

Better visibility of the supply chain can lead to a more flexible manufacturing value network. For example, production can either be moved in-house or outsourced to an alternate location when a disruption occurs without adversely affecting operations.

Four clusters of disruptive digital technologies will enable supply chain digitization.

1. Commodity IoT sensors with the ability to capture and process data and connect/exchange data with other systems over communications networks to provide transparency.
2. Cloud computing and access to advanced algorithms enable organizations to derive insight, model, analyze and make accurate predictions to provide flexibility and efficiency.
3. Technologies like robotics, business process management and robotic process automation, and voice assistants and chatbots enable the automation of physical and non-physical processes, leading to faster and more efficient processing.
4. Combining disparate IT and OT data sources into a single system to generate digital operational insights and business KPIs at an enterprise level.