Mr. Cao Dai An
Head of Technology and Solutions Office and AI Practice for ASEAN and Japan
June 23, 2026
Manufacturing enterprises are currently facing many intensifying pressures at the same time, including geopolitical instability, cost volatility, supply chain disruption, labor shortages, cybersecurity risks, and increasingly high customer expectations, while still having to continuously improve output, quality, traceability, and safety standards.
Solutions such as lean or automation, while necessary, remain largely localized and can lead to fragmented operations. In this context, smart manufacturing is emerging as a critical approach, connecting systems, data, and processes to improve speed, flexibility, and operational efficiency.
As we enter 2026, scaling digital transformation across all manufacturing operations is no longer a choice, but has become an urgent requirement to maintain and strengthen competitiveness.
When Manufacturing Becomes βSmartβ
In a traditional manufacturing environment, the issue is not the lack of data, but the dispersion of data. ERP systems provide part of the information; the same is true for MES and MOM; in addition, there are maintenance systems, quality control tools, operating logs, spreadsheets, and operator experience. When these data sources are not connected in real time, decision-making is delayed and improvements occur only locally.
Smart manufacturing establishes a βconnected execution layerβ across the entire value chain, linking operational technology (OT) with enterprise systems, standardizing critical processes, and improving visibility and operational monitoring for teams at the plant.
Automation plays a central role in this transformation, but its true value is realized only when robots, computer vision systems, quality inspection, and operational control are integrated with industrial data, MOM systems, MES, data analytics, Digital Twins, and enterprise systems.
An effective operating model will combine:
- Real-time visibility
- Standardized execution processes
- Secure integration across ETβITβOT
- Digital Twins for simulation and scenario testing
- Industrial Artificial Intelligence (Industrial AI) for anomaly detection and decision support
GenAI is gradually opening up new value, helping transform engineering, maintenance, and operational data into useful guidance at the point of work. On that foundation, Agentic AI further elevates this by driving the transition from insight to action β automatically triggering processes, recommending next steps, and shortening the time required to address issues in production, quality, and maintenance.
These capabilities help improve planning efficiency, quality control, traceability, maintenance optimization, and energy consumption, thereby improving the quality of decision-making in daily operations.
Why Many Transformation Programs Have Not Created Sustainable Value
Many enterprises have implemented pilot projects, individual automation efforts, or digital transformation roadmaps. However, the greatest challenge lies in scaling these efforts across entire lines, plants, regions, or business units.
Common barriers include:
- Discrete use cases that are difficult to replicate
- Insufficiently rigorous data governance
- Legacy technology infrastructure
- Technology choices that are not aligned with operational reality
- System integration challenges
- Increased cybersecurity risks as more devices are connected
In particular, the human factor plays a decisive role. Smart manufacturing cannot be only a technology initiative detached from production operations; it requires the synchronized participation of plant leadership, engineering, IT, operations, supply chain, maintenance, and frontline teams.
As manufacturing increasingly relies on data and software, enterprises need to establish clear organizational structures, strengthen data capabilities, and implement practical training programs β while drawing on field experience rather than replacing it entirely.
An Effective Transformation Model
Enterprises that achieve clear progress often begin with a number of core operational priorities such as productivity, downtime, quality, energy consumption, compliance, traceability, or asset performance.
From there, the focus shifts to building an βend-to-end execution layerβ through:
- Standardizing MOM, MES, and data models
- Connecting ERP, PLM, and manufacturing systems
- Applying standards such as ISA-95 to ensure interoperability
On this foundation, advanced technologies deliver clear effectiveness:
- Industrial AI detects abnormal trends early
- Real-time analytics supports rapid response
- Predictive maintenance minimizes downtime
- Connected quality systems improve traceability
For global manufacturing enterprises, the key factor is the ability to standardize and replicate, including common governance, consistent KPIs, cybersecurity controls, reusable data models, and synchronized deployment methods.
The Role of Hitachi Digital Services in the Transformation Journey
Digital transformation delivers value only when strategy, plant operations, and implementation are designed in alignment. Hitachi Digital Services brings comprehensive capabilities in manufacturing, global deployment, enterprise systems, and plant technology.
Hitachiβs solutions focus on connecting ETβITβOT, ensuring that data and processes are aligned from design, planning, production, and maintenance to service. At the same time, Hitachi Digital Services helps enterprises effectively apply Industrial AI, GenAI, and Agentic AI in practical ways β from identifying operational risks and improving maintenance decisions to turning insights into guided actions across the plant.
A representative example is the Hitachi Smart Manufacturing Operations Management (SMOM) solution suite, which helps enterprises:
- Connect plant operations with Enterprise Resource Planning (ERP) systems
- Orchestrate production from orders to execution, quality, materials, and maintenance
- Deploy in stages, reducing risk compared with a βbig-bangβ model
The solution is designed flexibly for many manufacturing models, from small-lot production to mass production or large-scale customization.
We help manufacturers reduce transformation risk, shorten time to value, and build capabilities that can hold up in live production through advisory support, operating model design, systems integration, industrial data strategy, plant-level execution, cybersecurity-aware integration, and managed services.
Real-world implementations have recorded clear results. In a connected vehicle project for a leading Japanese automotive group, Hitachi Digital Services built a highly secure data platform, enabling real-time connectivity and opening up new mobility services. In another project in high-speed rail operations and control, Hitachi Digital Services worked with the customer to build a next-generation operating ecosystem using AI β integrating real-time monitoring, predictive and condition-based maintenance, and intelligent operations. By applying Industrial AI and Agentic AI, the platform connects data across systems and assets, transforms information into guided action, and thereby improves operational accuracy, optimizes maintenance efficiency, and drives sustainable performance at scale.
With a comprehensive approach, from strategic consulting and operating model design to systems integration, plant implementation, and managed services, Hitachi Digital Services helps enterprises reduce risk, shorten time to value, and build sustainable capabilities in real manufacturing environments.