Manufacturing 4.0: From data to decisions

Manufacturing 4.0 is about unlocking the value of the Fourth Industrial Revolution, or Industry 4.0, which can help an organization thrive—even amid disruption.

With the infusion of digital technologies in facilities and operations, manufacturers are redefining possibilities for resource and production process efficiency, asset utilization, labor productivity, quality enhancement, time to market reduction, and service value-add.

“Smart manufacturing,” which is driven by the analysis of data generated by advanced sensors, software, and robotics, can lead to improved decision making. Heightened visibility and insights are generated from the combination of production data and operational data within an organization and across ecosystem partners.

In addition, the potential value of data sharing in manufacturing process optimization has been estimated at over $100 billion.

Data rich, information poor

As part of Industry 4.0, cyber-physical models and digital integration of new technologies across the value chain help increase efficiency and provide mass customization capability. The convergence of information technology (IT) and operational technology (OT) systems creates interconnectivity between autonomous manufacturing equipment and broader computer systems.

However, our recent survey of 2,360 manufacturing industry executives in 32 countries revealed that manufacturers are not tapping the full power of big data, and many face significant technology barriers. Despite the revolutionary potential of data insights in manufacturing, most organizations are not using data from equipment, processes, and systems in any meaningful way to draw insights for continuous process improvement.

Only 28% of manufacturing organizations are using data from equipment, processes, and systems to draw insights for continuous process improvement.

For example, predictive maintenance involves the continuous collection and analysis of sensor data to identify faults prior to failures and prompt interventions only when needed. But only a quarter of organizations are optimizing asset or equipment maintenance schedules based on analysis of failure modes and balancing reliability and cost.

Fewer than 1 in 5 have real-time access to important manufacturing data across the enterprise, which could include useful unstructured data from spreadsheets, industrial social media, email, text files, video, or CAD.

Driving business value through Industry 4.0

Executives identify a combination of technologies that are important to advancing their manufacturing objectives. More than three quarters cite AI, which is not surprising given AI-generated insights help improve visibility and predictability of manufacturing operations. Security technologies, cited by 70%, are necessities with the continued risk of cybersecurity attacks in IT and OT environments.

Cited by almost 68%, cloud computing provides connectivity and can run applications and store data. And the Internet of Things (IoT), cited by 67%, connects sensors and devices to networks to take advantage of large amounts of real-time data. For example, if an assembly line is experiencing a disruption, products can be rerouted or delayed to help reduce wasted time and cost.

The combination of edge- and cloud-computing infrastructure provides localized optimization and connected assets for smart manufacturing. However, only 84% of respondents are in the earlier stages of edge computing maturity, with nearly half at the pilot stage and the rest having advanced to implementation in some production lines.

Executives rank the most important technologies driving success in manufacturing

Not surprisingly, manufacturing respondents tell us their top objectives are increasing production yield, improving product quality, addressing sustainability, and reducing machine downtime. Yet, there is a gap between ambition and performance: Despite these objectives, only 36% of respondents are maintaining desired throughput and yield to a significant or very great extent.

However, our research revealed a group of organizations that are ahead of their peers in terms of digital transformation. Having instilled a data-driven culture for their organizations, these Data Transformers offer a model for other organizations to follow.

The Manufacturing 4.0 advantage

In addition to surpassing their peers in digital maturity, Digital Transformers also stand out due to superior business and operational performance. 71% say they outperformed their competitors in revenue growth over the last 3 years. Data Transformers also exhibit both decision-making and mass customization success.

84% of Data Transformers have significantly integrated artificial intelligence (AI) and machine learning in their data platforms.

Dependent on a transparent, efficient supply chain, Data Transformers have implemented AI to a greater degree than their peers for procurement and logistics. 50% have fully implemented or implemented at scale raw material/component/subassembly procurement, and 41% have done so for logistics.

By leveraging technologies to align business objectives with improved outcomes, these data mature organizations are distinguishing themselves through their insights, cyber resilience, enterprise architecture, manufacturing excellence, workforce capabilities, and digital integration.

Overall, Data Transformers stand out in 6 key areas:

— Tap the potential of data.

— Achieve cyber resilience.

— Create an enterprise architecture connecting the plant floor to business systems.

— Increase manufacturing excellence with technology.

— Embrace the manufacturing worker of the future.

— Integrate digital with manufacturing operations and management.

Cost-effective digital manufacturing solutions are needed to keep factories and supply chains running smoothly while producing high-quality products.

Download the report to discover how industry leaders are leveraging Manufacturing 4.0 for greater customer value and ongoing operational improvements that help drive productivity and profitability.