Digital Transformation in Manufacturing: 2025 Trends, Success Cases, and Strategies

Digital Transformation in Manufacturing: 2025 Trends, Success Cases, and Strategies

23 January 2025

By Sursha Wu

Digital transformation has reshaped manufacturing. From electronics to automotive production, companies are using AI, digital management, and software to improve quality and reduce costs. This article covers 2025 trends in smart manufacturing, success cases, and practical strategies to help businesses navigate digital transformation effectively.

Digital Transformation Trends: Industry 5.0

Many companies focus on Industry 4.0, using automation, robotics, and IoT to enhance manufacturing. However, as businesses embrace Industry 4.0, Industry 5.0 is emerging.

Industry 5.0 focuses on human-machine collaboration and personalized production. It aims to enhance production flexibility and efficiency while promoting sustainability. Leading manufacturers invest in proactive strategies to stay competitive in a rapidly evolving market.

Manufacturing Digital Transformation Success: LEO PAPER GROUP

Watch Johnny Fong, CEO of Leo Paper Group, share insights on their digital transformation journey.

 

Leo Paper Group, one of China’s top 10 printing companies, specializes in diverse paper products, from books to packaging.

Managing production variability in such a complex environment is a significant challenge.

Transformation Begins with Lean Manufacturing

Long before Industry 4.0 became a buzzword, we were already on the journey of lean manufacturing.
── Johnny Fong, CEO, Leo Paper Group

Lean manufacturing focuses on reducing waste and improving efficiency. For Leo Paper Group, Industry 4.0 is not just a trend but a transformative process to enhance production workflows and environments.

The company established lean manufacturing as the key to its digital transformation and improved the way it manages production lines.

“Data” is the Foundation of Smart Manufacturing

Although the benefits of data ownership are clear, achieving full control of data remains challenging, especially in complex manufacturing environments.

In busy production settings, data is the key to managing operations effectively.

In a busy production environment, the most effective way to manage operations is through data. Real-time data collection is a top priority for management.

However, manufacturing operations often involve data from multiple systems, which can lead to fragmented data. Without a unified system, it becomes difficult to maintain data consistency and reliability.

Read More: What is data ownership?

IoT and Machines

In Leo Paper Group’s factories, key equipment such as printing are equipped with IoT systems, known internally as the Heartbeat System.

These systems collect and transmit production data at regular intervals, tracking machine operation status and setup times to ensure efficiency.

AI Vision and Human Operations

Download Success Case: How to manage production line by AI Vision

In addition to machine-driven processes, human labor plays a crucial role in paper manufacturing.

In the past, the lack of effective tools made it difficult to address inefficiencies in manual operations, such as inconsistent takt times and unbalanced line.

With cameras and AI vision analysis now integrated into production lines, all actions are tracked, analyzed, and recorded. AI vision supports time and motion studies, accurately monitoring cycle times and analyzing operator behavior to optimize workflows and improve efficiency.

Download the Case Study: How a Global Top 3 EMS Used AI Vision for Time and Motion Studies on Production Lines.

Real-Time Data and the Command Center

Now with sensing device, with real-time information, real-time data capturing, the next thing is do have a dashboard.
── Johnny Fong, CEO, Leo Paper Group

In a busy production environment, management has recognized that data-driven management is the most effective approach.

However, manufacturing processes often involve data from multiple systems, leading to fragmented and unintegrated data. Lack of unified data slows anomaly detection and issue resolution.

Factories need an integrated management platform that combines data from machines and human operations to provide clear production insights. This platform should help managers quickly identify root causes of issues, so that the managers could take immediate action. This kind of platform can really unlock the full potential of data-driven management.

What’s more, with robust data support, managers can use the data as a foundation for long-term strategic plans for quality and efficiency issues.

Support Real-Time Production Data: HOP

Addressing Pain Points in Production Management

PowerArena has identified common challenges in manufacturing digital transformation and provided validated solutions to help manufacturers overcome obstacles effectively.

 

Managing Human Operations

Over 72% of factory tasks are still performed by human workers. Robots haven’t yet replaced all jobs in factories.
Source: Kearney

In environments with manual operations, such as electronics manufacturing or automotive assembly, variability in human actions can impact quality and efficiency.

For instance, differences in operator training, physical condition, or experience can lead to inconsistent product quality and varying assembly speeds.

Traditional management methods lack comprehensive tracking and analysis of these actions, leaving managers without a clear understanding of production line performance.

→ AI Vision for Tracking and Analysis

By installing cameras and adopting AI vision technology, factories can precisely track, analyze, and record all production activities.

Well-trained AI models can identify whether operators are using the correct components, placing them accurately, and following standard procedures. When anomalies occur, AI provides actionable insights into their causes.

This technology significantly reduces the time and effort required for process management while delivering actionable production insights through visual data.

Fragmented Data and Limited Insights

Here’s an example from a real PowerArena case. A factory noticed a drop in production efficiency during specific periods and observed operators leaving their workstations.

However, the factory relied on IE engineers to manually collect and monitor production data. The information was incomplete, fragmented, and lacked an integrated long-term view of production line performance. This made it difficult for management to accurately evaluate the efficiency and capacity of each process..Continue reading the case study for more insights.

→ HOP: A Digital Solution for Unified Management

HOP Platform: Root cause analysis is clear and easy to understand, helping managers quickly identify anomalies, optimize efficiently, and improve production line performance.

 

HOP, Human Operation Platform solves data fragmentation by integrating machine and human data into a unified system.

HOP provides clear visual insights, 24/7 tracking, and actionable reports to support better decision-making.

Managers can quickly pinpoint anomalies, analyze root causes, and implement improvements to optimize production lines, improve quality, and reduce costs.

Book a demo of HOP to see how it can transform your production management process.

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