From 2026, the European Union adjusted and narrowed the scope of its Corporate Sustainability Reporting Directive (CSRD). The detective  now focused mainly on large corporations with more than 1,000 employees and net revenue above €450 million.

That policy shift has created a strategic misconception for many manufacturing leaders. Many assume ESG compliance pressure has cooled off. In practice, global supply chain operations tell a very different story.

Most factories – especially in the plastics industry – aren’t directly subject to the legal reporting requirement. Even so, they still face enormous indirect pressure from European buyers. Multinational corporations need to hit net-zero targets and manage their own Scope 3 reporting. To do that, they push data transparency requirements down through their entire supplier network.

The real question facing plastic factories today isn’t the passive “Is our company legally required to file a CSRD report?” It’s this: “When a strategic customer asks for an emissions audit, can the factory produce accurate, instant, fully traceable data?” That question is exactly what separates suppliers who keep their place in the value chain from those who get phased out.

The Plastics Industry Is Losing Money From Disconnected Energy Data

Alongside external compliance pressure, plastic manufacturers are also fighting an internal profitability problem. Energy costs make up a large share of the cost structure for plastic products. Yet most leadership teams are still running the business on fragmented metrics – where electricity consumption data is completely disconnected from what’s actually happening on the shop floor.

Here’s the core issue: if a factory only knows its total electricity usage at the end of the month, it’s nearly impossible to tell how efficiently that energy is actually being used.

3 Core Risks of Manual Energy Data Management

For factories still consolidating data through Excel or utility bills, a Scope 3 emissions data request from an EU partner can quickly turn into a bottleneck:

NxOEE: A Competitive Advantage for the Plastics Industry

NxOEE connects factories directly to shop-floor data, tracks performance in real time, and builds a single, consistent data source for both daily operations and EU partner requirements — built on three pillars:

1. Real-time performance and energy monitoring – Track machine status, output, cycle time, and OEE by machine, shift, or mold code. Instant alerts on performance drops let teams catch and fix issues before they eat into margins.
2. Less dependence on manual data entry – Production data is collected automatically and centralized in one system, cutting the time spent reconciling spreadsheets and reducing reporting errors.
3. Transparent production data – Track OK/NG rates, progress, and production events, so the factory can pull traceable data on demand — for internal analysis or for a customer’s audit request.

The result: shop-floor data doesn’t just power OEE management – it becomes the foundation for tracking energy efficiency, reducing scrap, and meeting the ever-rising data demands of the EU supply chain.

Conclusion

In an increasingly demanding global market, manufacturers with a transparent, real-time energy data platform don’t just protect their position in the supply chain – they actively optimize margins and build a durable competitive edge.

Is your factory ready to answer an emissions audit request at any moment?

Learn more about the NxFactory EMS platform and turn your energy data into a real competitive advantage.

Many plastics plants still hit their production plan every month. Yet their OEE stays at 60–65%. That’s well below the 85% benchmark internationally certified plants typically use as a reference for high performance.

That gap between actual and expected performance quietly eats away at operating costs, day after day.

Where the OEE Gap Is Quietly Draining Operating Costs

• Expensive raw material waste: Mold trials and setup runs generate scrap – flash, short shots, warping – that burns through engineering-grade resin directly.
• Idle power losses: Injection molding machines still draw significant power during invisible downtime. For example, they keep drawing power while waiting on resin drying, mold changes, or temperature stabilization.
• On-Time Delivery (OTD) risk: Cycle time drift of just 1–2 seconds per cycle adds up to hours of delay. This threatens OTD performance and credibility with Tier-1/Tier-2 supply chain partners.

These losses rarely come from major breakdowns. In fact, a machine can sit in a “Running” state while quietly operating below standard speed. It might also take longer to set up, or produce more scrap than usual. If teams still log this data manually, or it stays scattered across different sources, the plant has no way to pinpoint where the performance gap is coming from.

3 Technical Blind Spots Holding Back Injection Molding Performance

In real plastics production floors, performance typically erodes through three technical blind spots:

• Invisible downtime (Availability loss): Short stoppages — mold changes, resin drying, machine cleaning — often go unlogged, or operators record them inaccurately. These “invisible” 5–10 minute gaps add up to significant losses over time, yet they’re extremely hard to catch.
• Cycle Time Drift (Performance loss): A drift of just 1–2 seconds in cooling time or part-ejection can be enough. The machine keeps running normally, but total shift output drops noticeably, and no alert ever fires.
• Scrap during setup (Quality loss): Flash, short shots, and warping tend to spike during trial runs. Without tight control over injection pressure and temperature, teams waste engineering resin — and that waste eats directly into the company’s profit margin.

3 Barriers Keeping Plastics Plants From Controlling OEE in Practice

1. Lack of real-time monitoring: Operators still log downtime manually, which makes the data prone to errors. As a result, it doesn’t accurately reflect machine status at the moment an issue occurs. If nobody records a stoppage the instant it happens, short stops are easy to miss or lump together. Because of this, the plant can’t pinpoint actual downtime or recurring causes.
2. Diverse machinery, difficult to connect consistently: One of the biggest concerns for plastics plants rolling out new software is machine diversity. Most shop floors run multiple generations of injection molding machines from different vendors, each with its own communication protocol. Because of this, collecting production data on a single, unified platform becomes a real technical hurdle. Teams often can’t fairly compare data from one machine to another.
3. Incomplete downtime cause logging: Teams record downtime, but often skip the specific cause. A stop might be due to a mold change, waiting for material, adjusting process parameters, or troubleshooting a fault — yet nobody properly categorizes any of it. As a result, the business struggles to identify its biggest bottleneck and prioritize a fix.

MES Gives Manufacturers Visibility to Improve Performance

Combining MES with IoT lets manufacturers collect data directly from machines. That data becomes an accurate basis for measuring all three pillars of OEE:

Availability – precise tracking of run time and downtime.

Performance – optimizing cycle time and hitting actual output targets.

Quality – tightly managing the ratio of good parts to scrap.

👉 Explore our MES & IoT solutions for real-time production visibility and OEE improvement at HERE!

Beyond Measurement: Audit-Ready Traceability for Global Supply Chains

Real-time data doesn’t just support measurement – it carries strategic value too. Plastics plants operating in global supply chains face constant pressure from strict process audits. Automatically logging data – temperature, injection pressure, downtime history – creates transparent, audit-ready traceability. This is a major advantage for proving quality management capability to international partners.

As a result, plant management shifts entirely. Instead of looking at one consolidated number at the end of a period, managers can immediately identify which OEE component is dragging performance down, and exactly why. That visibility enables faster, better-informed improvement decisions.

NTQ Factory × TMT Vietnam Group: Bringing the Data Challenge to the Plant Floor

NTQ Factory is solving exactly this challenge in practice at TMT Vietnam Group, a company specializing in precision molds and injection-molded plastics manufacturing. In its digital transformation project with NTQ Factory, the two sides focused on building a data platform. The goal: connect production data and strengthen operational governance.

Machine diversity – one of the three barriers above – was a central part of that challenge. With NxFactory, NTQ Factory addressed it directly. The platform connects and standardizes data across machines from different brands and generations already on the shop floor. This meant TMT didn’t need to replace its existing equipment to build a centralized, real-time data foundation for the whole plant.

Beyond that, NxFactory now consolidates data from machines and the shop floor into a single system. This gives the business real-time visibility into performance. It also reveals the root causes behind specific performance drops, so teams can prioritize the right improvements.

Conclusion

Low OEE rarely comes down to machine stoppages alone. More often, it comes from losses that are hard to see: in downtime, cycle time, and quality. When teams connect and update data in real time, a plant can move from simply knowing OEE has dropped to actually understanding why – and what to fix.

For plastics manufacturers, that shift is the foundation for higher equipment performance, tighter production control, and – step by step – a genuinely smart operation.

👉 Ready to optimize your plastics plant’s performance? Book a consultation with an NTQ expert at nfactory.vn/request-a-demo/

TMT Vietnam Group: Elevating Management with Operational Data

Precision engineering demands ever-higher quality, faster timelines, and greater operational efficiency. As a result, companies increasingly rely on technology and data to manage production. TMT Vietnam Group holds a key position in the plastics and precision mold value chain, so it has proactively chosen to digitize its entire operating system. Beyond upgrading equipment and facilities, TMT Vietnam Group wants transparent management and precise, real-time control over productivity and equipment performance.

This project marks a concrete step in that direction. It reflects the proactive, innovative mindset of TMT’s leadership and team as they search for new ways to improve efficiency and unlock more value from production data.

NTQ Factory: Deep Technology Expertise with a Practical Approach

Alongside TMT Vietnam Group, NTQ Factory brings its strength as a Smart Manufacturing specialist. The company offers IoT data connectivity, builds software infrastructure, and optimizes factory operations.

From the earliest pre-project stage, NTQ Factory’s experts worked directly on-site with TMT’s technical team. Together, they studied the specific operating characteristics of each machine and production process. This combination – TMT’s rigorous industry expertise and NTQ Factory’s hands-on technology skills – is expected to deliver practical value and help shape modern operating standards across the manufacturing industry.

Project Kick-off: Building Momentum for a Smart Factory in the Plastics Industry

At the kick-off event, representatives from both sides agreed on project goals, implementation direction, and a coordination plan. The project follows a “Push and Pull” collaboration model. In other words, it combines TMT’s hands-on operational experience with NTQ Factory’s technology capabilities to unlock maximum production efficiency.

The Digital Transformation Project follows a clear roadmap. Its main focus is making production data transparent, so leadership and engineers can easily observe, measure, and make timely decisions based on reliable data.

Through direct IoT connections between machines and the management system, TMT is shifting away from a traditional factory model. In the old model, staff had to inspect and monitor machines mostly on-site. Now, the company is moving toward a smart factory model, where teams can monitor and control the entire production process online, anytime and anywhere, in real time. This shift also aligns with the growing global use of Overall Equipment Effectiveness (OEE) as a benchmark for operational efficiency.

The centralized management system continuously updates machine status, output volume, defect rates, downtime, and production progress. As a result, leadership can stay informed and make quick decisions without needing to visit the factory in person.

From a Single Project to a Long-Term Partnership

TMT Vietnam Group is a reputable name in plastics and molds, and NTQ Factory is a specialized technology firm. Their collaboration highlights the value of connecting manufacturing experience with technology capability to build a smart factory. It also reflects a broader trend: domestic companies are increasingly forming alliances and using technology as a lever to raise the quality of Vietnamese manufacturing on the global supply chain map.

Right after the kick-off ceremony, both teams began their first joint tasks. This marks the start of a shared journey toward innovation, growth, and further progress in smart manufacturing.

About TMT Vietnam Group

TMT Vietnam Group was founded in 2014. Since then, the company has built a strong reputation in Vietnam for precision mold design and manufacturing, plastic injection molding, and high-precision technical plastic components made to international standards. With nearly 400 employees and a modern production facility, TMT Vietnam Group now supplies numerous domestic and international manufacturing corporations. It meets high standards for quality, precision, and production capacity.

About NTQ Factory

NTQ Factory is a specialized provider of consulting and implementation services for Smart Manufacturing, part of the NTQ technology ecosystem. Its team of engineers and technology experts focuses on the shop floor. Because of this hands-on approach, NTQ Factory has successfully deployed smart manufacturing solutions for large-scale production lines and factories in Vietnam, Japan, South Korea, and Europe. The company helps manufacturers optimize Overall Equipment Effectiveness (OEE), improve operational efficiency, make data-driven decisions, and build comprehensive digital transformation infrastructure.

On July 31, the VSIP Bắc Ninh 2026 Business Insights Seminar took place at VSIP Bắc Ninh. More than 60 business leaders, factory managers, and technology experts attended from across the region. The event was co-organized by NTQ Factory, BIPO, and Esign.AI. Together, they offered practical, real-world perspectives on how manufacturers can use AI, data, and digital platforms. The goal: boost operational efficiency, strengthen governance, and build a foundation for sustainable growth

For more on the host venue, visit the official VSIP website.

VSIP Bắc Ninh 2026: Practical Insights for Real Manufacturing Challenges

Throughout the VSIP Bắc Ninh 2026 program, sessions focused on real challenges. Each one paired a problem with a proven, practical approach. In turn, this helped businesses see how to build a smarter, more connected operating model step by step.

Key topics covered included:

• Closing the gap between shop-floor data and executive decisions. This helps companies respond faster to incidents and make data-driven calls.
• Applying AI to workforce time management, payroll, and compliance. As a result, HR management becomes more efficient.
• Digitizing signing and cross-border compliance processes. This prepares businesses to scale within global supply chains.

Rather than simply showcasing technology, the program centered on real implementation stories. Attendees heard lessons learned directly from manufacturers. Consequently, they left with a clearer picture of how digital solutions solve concrete production problems.

Closing the Gap Between the Factory Floor and Business Decisions

One keynote session at VSIP Bắc Ninh 2026 stood out. Presented by NTQ Factory, it was titled “From Manual to Smart Factory: Closing the Data Blind Spot Between the Shop Floor and Business Decisions.”

Using real-world manufacturing scenarios, the session broke down three common operational gaps: Time, Truth, and Cause. Together, these gaps explain why so many factories still struggle to turn data into effective decisions.

But the session didn’t stop at identifying problems. It also laid out a practical roadmap for building real-time operational data streams. This roadmap, in turn, sets the stage for future AI adoption and stronger operational efficiency.

To see this roadmap in action, explore NTQ Factory’s smart manufacturing solutions.

Hands-On Technology and Networking at VSIP Bắc Ninh 2026

Beyond the presentations, VSIP Bắc Ninh 2026 gave attendees a chance to experience real solutions firsthand. These are technologies already deployed in live manufacturing environments.

At the exhibition area, businesses explored several technologies, including:

• AI-powered smart manufacturing management platforms
• AI camera systems
• Smart warehousing combined with autonomous mobile robots
• A range of digital solutions from technology partners

Overall, the exchange between businesses, experts, and solution providers was lively. As a result, an open forum took shape. There, managers shared real challenges, swapped implementation experience, and explored new partnerships for their manufacturing transformation journey.

VSIP Bắc Ninh 2026: Building the Foundation for Sustainable Growth Together

VSIP Bắc Ninh 2026 offered more than practical AI and smart manufacturing insights. Above all, it underscored one key idea: data connects people, processes, and technology. In turn, this connection improves operational efficiency and supports better decisions.

Through this event, NTQ Factory reaffirmed its commitment to manufacturers. Specifically, the company pledged continued support as businesses build strong data foundations and smarter operations. NTQ Factory also extends sincere thanks to VSIP Bắc Ninh, co-organizers, technology partners, and every attendee who helped make VSIP Bắc Ninh 2026 a success. Looking ahead, this seminar should serve as a springboard. From here, new connections and collaborations can grow, further driving sustainable development across Vietnam’s manufacturing community.

What Is an AI Camera?

An AI camera combines a standard camera with artificial intelligence — mainly Computer Vision and Edge AI. As a result, it doesn’t just record video; it understands the scene in real time. A regular camera simply streams raw footage to a storage server. An AI camera, however, can spot objects on its own — people, smoke, fire, or defective products. It then triggers instant alerts. So, no one needs to watch the monitor around the clock.

AI Camera vs. Regular Camera: What’s the Difference?

This is the core distinction between an AI camera and traditional CCTV:

• Regular camera (traditional CCTV): It only records and stores footage. To find out what happened, someone has to review the recording later, or watch the live feed constantly. In other words, a regular camera can’t “understand” the image. All analysis still depends on a human.
• AI camera: It analyzes the video stream in real time. It also detects anomalies — smoke, fire, unusual behavior, or product defects — on its own. Then, it proactively sends alerts through a siren, email, mobile app, or Telegram, usually within seconds. In short, an AI camera shifts monitoring from a passive role (evidence after the fact) to an active one (prevention and timely intervention).

Put simply, a regular camera is an eye that records. An AI camera, by contrast, is a brain that understands and reacts.

Pros and Cons of AI Cameras

Advantages

• Earlier incident detection: The system doesn’t wait for dense smoke or a serious incident. Instead, it catches problems early and helps limit damage.
• Less dependence on manual monitoring: Staff no longer need to watch screens 24/7.
• Works with existing infrastructure: Most AI camera solutions today plug directly into an existing IP camera network. So, factories avoid a full hardware overhaul.
• Quantified data for management: The system delivers real-time metrics — headcount, idle time, defect rates — and these numbers support better operational decisions.

Disadvantages

• Upfront investment: AI software, and sometimes dedicated processing hardware like GPUs, usually push the initial cost above standard CCTV.
• Accuracy depends on real-world conditions: Image quality, lighting, and camera angle all affect model accuracy. Likewise, the model needs proper tuning for its specific environment.
• Requires model tuning time: The system isn’t plug-and-play. Instead, it usually needs a survey phase and a training phase tailored to each factory before it reaches high accuracy.
• Privacy considerations: Because the system recognizes and tracks human behavior, businesses need a clear, transparent data-use policy for their employees.

Weighing these benefits against the trade-offs helps a business pick the right implementation partner — one that maximizes the upside and limits the downsides above. This is exactly why NTQ Factory built its AI Camera solution around existing infrastructure and a short deployment timeline.

NTQ Factory’s AI Camera Solution

Camera AI NTQ Factory turns a standard surveillance system into an “actively intelligent” one. It does this through three core application streams:

1. AI-Sentinel — Smoke/Fire Alerts and Fire Safety

The system scans video feeds in high-risk zones — chemical warehouses, alcohol or solvent storage — and catches smoke or flame at the earliest stage. As a result, it overcomes the delay of traditional fire sensors. Once it detects an incident, the system draws a bounding box on screen. Then, it sends alerts through a siren, email, mobile app, or Telegram in under 30 seconds. At the same time, it automatically logs visual evidence for investigation or insurance purposes.

2. People-Flow — Workforce Statistics and Behavior Analysis

The system counts and updates worker or visitor numbers in real time, across production lines, workshops, or entry and exit zones. It also recognizes behavior patterns. For instance, it flags a worker who leaves their station too long or stands idle. Consequently, managers can redistribute labor and lift productivity right away.

3. Quality Inspection — Quality Control and Traceability

Camera Vision integration lets the system inspect finished products. In the beverage industry, for example, it checks fill level, label quality, and cap seal integrity (pass/fail). At the same time, it scans batch codes to support product traceability.

Technology Advantages and Deployment Speed of Camera AI NTQ Factory

• Works with existing infrastructure: The solution connects directly to a factory’s existing IP camera network over the local network. So, no new hardware is required.
• High-performance processing: Edge AI and Computer Vision, paired with dedicated Nvidia RTX graphics cards, keep LiveView latency under 2 seconds.
• Rapid rollout: Site survey, installation, configuration, model tuning, and acceptance testing all fit into about 4 weeks.

Case Study

NTQ Factory has already deployed its AI Camera solution across a range of industries:

• Electronics factory (South Korea): The team integrated more than 80 IP cameras across a 10,000m² facility. As a result, fire and smoke detection accuracy reached about 95%. Likewise, behavior recognition and people counting topped 98% accuracy. Idle time dropped by more than 35%, and the system eliminated 70% of manual headcount reporting.
• Fire/smoke monitoring in heavy industrial settings: The solution has run successfully at a dairy production plant. In addition, teams use it in real-world settings at a construction site and a steel plant — both heavy industrial environments with high levels of dust and smoke.
• People counting and traffic analytics: Teams use this feature at a tourist destination and a heritage site to manage crowd flow and visualize visitor traffic patterns.

Conclusion

An AI camera isn’t just a technology upgrade. Rather, it marks a shift in mindset — from “record now, review later” to “detect and respond as it happens.” Through three application streams — AI-Sentinel, People-Flow, and Quality Inspection — Camera AI NTQ Factory helps factories secure 24/7 safety. At the same time, it optimizes resources and product quality, without replacing existing camera infrastructure.

Want a deployment roadmap tailored to your factory? Contact the NTQ Factory team for a free consultation.

The Make In Vietnam Awards — organized annually by Vietnam’s Ministry of Science and Technology — is where the country’s most impactful digital products earn national recognition. The 2025 edition brought a landmark moment for NTQ Factory: NxFactory, its smart manufacturing platform, took home the Silver Award among the nation’s outstanding digital solutions.

More than a trophy, this recognition carries weight. Make In Vietnam evaluates entries against rigorous criteria: real-world applicability, measurable business impact, and competitive readiness in international markets. Earning Silver in this field validates NxFactory not just as a promising product, but as a mature, deployable solution capable of driving meaningful change on the factory floor.

[NxFactory Granted Silver Award At Make In Vietnam 2025]

The Problem NxFactory Was Built to Solve

To understand why this recognition matters, it helps to understand the pressure manufacturers are operating under right now.

Global supply chains have never been more volatile. Product lifecycles are shrinking. Customer demand for customization is rising. And skilled manufacturing talent remains in short supply across the region. Traditional production management systems — built for a more predictable era — were never designed to handle this level of complexity.

NxFactory addresses this gap directly. Rather than digitizing existing processes, the platform enables manufacturers to fundamentally rethink how factories operate, sense, and decide. It connects the shop floor to the control room to the boardroom — creating a continuous intelligence loop across every layer of production.

Core capabilities include:

• Automated real-time data acquisition from machines and production lines
• Equipment condition monitoring with early fault detection
• AI-powered predictive insights to stay ahead of disruptions
• Intelligent production planning that adapts to live operational data
• Multi-dimensional reporting and dashboards for operational leadership

The result is a shift from reactive firefighting to proactive optimization — and from gut-feel decisions to data-backed confidence.

Measured Results, Not Just Features

Make In Vietnam doesn’t reward ambition alone — it rewards outcomes. NxFactory’s track record in live deployments demonstrates exactly that:

These figures come from real factory environments, where every percentage point translates directly into margin, capacity, and competitive advantage.

Mr. Nguyen Huu An, Vice CEO of NTQ Factory, put it plainly: “This recognition affirms our vision to build a technology platform that enables manufacturers to operate leaner, gain real-time visibility into data, and compete confidently across global value chains.”

[Mr. Nguyen Huu An, Vice CEO of NTQ Factory]

Three Consecutive Years on Vietnam’s Innovation Stage

The 2025 Silver Award doesn’t stand alone — it’s the latest chapter in a consistent record of national recognition:

2023 — Gold Award for NTQ’s Global Development Center (GDC)
In its first-ever Make In Vietnam entry, NTQ claimed the top honor in the Outstanding Digital Products for Foreign Markets category. The GDC model now serves clients across more than 20 countries, delivering specialized technology from Vietnam to global markets.

2024 — Top 10 New Digital Technology Products for NxUniverse
NTQ’s comprehensive Generative AI ecosystem earned recognition for its cross-industry versatility and its potential to transform how organizations work with knowledge and information.

2025 — Silver Award for NxFactory
The smart manufacturing platform extends NTQ’s innovation track record into one of the most demanding and strategically critical sectors in the regional economy.

Taken together, these wins tell a deliberate story: NTQ has built innovation capability across three distinct technology domains — global delivery infrastructure, AI ecosystems, and manufacturing intelligence — without losing depth or quality in any of them.

Why This Matters Beyond One Company

For years, Vietnam’s smart manufacturing software market has been dominated by international platforms designed for Western or East Asian factory contexts. NxFactory is changing that equation.

Built by a Vietnamese team, for manufacturers operating in the region’s specific economic and operational context, NxFactory offers something global platforms often can’t: deep local relevance without sacrificing technical sophistication. The Make In Vietnam Silver Award is independent confirmation that the platform meets international standards — not just local ones.

This has practical implications for manufacturers evaluating digital transformation investments. A locally developed, nationally recognized solution means lower integration barriers, more accessible support, stronger cultural alignment, and a partner that understands the nuances of doing business in Vietnam and Southeast Asia.

What Comes Next

NTQ Factory is committed to deepening NxFactory’s capabilities — expanding AI-driven features, broadening integration support, and scaling the platform’s reach into new markets beyond Vietnam. The ambition isn’t only to serve domestic manufacturers well, but to demonstrate that Make In Vietnam technology can compete and win in international markets.

The 2025 Silver Award marks a milestone. The road ahead is about turning that milestone into momentum.

Exploring digital transformation for your factory? Get in touch with the NTQ Factory team to learn how NxFactory can address your specific manufacturing challenges.

Jointly organized by the Vietnam Chamber of Commerce and Industry (VCCI) and Sunwah Group, the event served as a valuable platform for enterprises seeking deeper market understanding and long-term partnerships in Vietnam.

Vietnam Market Entry Opportunities In A Growing Technology Ecosystem

As part of the event, NTQ Factory delivered a presentation titled:

“Vietnam’s Science & Technology Ecosystem and Co-creation Opportunities in the New Era.”

During the session, NTQ Factory highlighted Vietnam’s transformation from a manufacturing-focused economy into an emerging innovation and technology hub in Southeast Asia.

Several factors continue to strengthen Vietnam market entry opportunities for international businesses:

• Strong foreign direct investment (FDI) inflows
• Rapid digital economy growth
• Expanding innovation ecosystem
• Accelerating smart manufacturing adoption
• Young and highly skilled workforce
• Extensive global trade connectivity

Today, Vietnam’s digital economy contributes more than 14% of GDP and is supported by over 70,000 digital technology companies, creating favorable conditions for global investors and technology enterprises.

Key Considerations For Successful Vietnam Market Entry

Drawing from NTQ’s 15-year globalization journey, the company shared practical lessons on what businesses need to succeed when entering new markets.

According to NTQ Factory, successful Vietnam market entry requires more than financial investment. Companies must also develop strong localization capabilities and establish meaningful relationships within the local business ecosystem.

Key success factors include:

• Understanding local market dynamics
• Building strong local teams
• Developing localization strategies
• Establishing strategic partnerships
• Adapting business models to customer needs

The discussion emphasized that sustainable growth comes from collaboration and adaptability rather than simply replicating existing business models.

The Shift Toward Co-Creation In Vietnam Market Entry Strategies

One of the central themes presented by NTQ Factory was the growing shift from traditional investment approaches toward FDI + Local Co-Creation models.

Instead of bringing existing solutions directly into a new market, enterprises are increasingly choosing to collaborate with local partners to:

• Accelerate adaptation
• Reduce operational risks
• Improve innovation capabilities
• Better understand customer expectations
• Build long-term competitiveness

The session also highlighted several trends shaping Vietnam’s business environment:

• Cross-industry collaboration ecosystems
• Smart manufacturing development
• Supply chain diversification
• Regional business hub expansion
• Knowledge exchange between global and local enterprises

These trends are redefining how companies approach Vietnam market entry and long-term expansion in Southeast Asia.

How NTQ Factory Supports Vietnam Market Entry And Global Growth

As Vietnam continues strengthening its position in the global technology landscape, NTQ Factory shared how it helps enterprises navigate market expansion and technology transformation.

NTQ Factory focuses on four strategic areas:

Understanding Vietnamese Operations

Helping businesses shorten their learning curve through local insights, operational expertise, and ecosystem connections.

Expanding Into Global Markets

Supporting enterprises in leveraging Vietnam as a strategic regional hub for international growth.

Co-Developing Technology

Facilitating technology and R&D collaboration to accelerate innovation and competitiveness.

Connecting Diverse Supply

Helping organizations diversify supply networks and improve adaptability in a changing global environment.

Strengthening Vietnam – China Business Collaboration

Beyond knowledge sharing, the Vietnam – China Investment & Technology Business Exchange 2026 created valuable opportunities for networking and business matching between enterprises from both countries.

For organizations considering Vietnam market entry, the event demonstrated the importance of ecosystem collaboration, localization, and co-creation in achieving sustainable growth.

Through its participation, NTQ Factory reaffirmed its commitment to supporting international businesses, accelerating digital transformation, and strengthening collaboration across Vietnam’s technology and manufacturing ecosystem.

Witnessed by high-level government representatives from Vietnam and South Korea, the MoU reflects a shared ambition to contribute to the ongoing digital transformation of the manufacturing sector – One of the key priorities in both countries’ economic strategies.

Ms. Nguyen Minh Trang – CEO NTQ Factory and Mr. Kim Young Nam – CEO Taejin System at the signing table 

Ecosystem That Leverages Smart Factory Adoption 

Under the MoU framework, NTQ Factory and Taejin System aim to establish a comprehensive collaboration to co-develop and deploy internationally standardized Smart Factory and AI Factory solutions in Vietnam.

The partnership is built upon the complementary strengths of both parties. Taejin System brings over 22 years of experience in delivering manufacturing management and Smart Factory solutions in South Korea. Meanwhile, NTQ Factory contributes strong capabilities in implementing advanced & comprehensive smart factory solutions tailored to various sectors, an experienced consultant team with deep insights into Vietnam’s manufacturing landscape, and granting advantages to implement large-scale projects from the foundation of NTQ Holdings – With 15 years of experience delivering successful projects for global markets, 1500+ employees, and 8 offices across Japan, Korea, Hong Kong, Europe and US. 

Together, the two companies will focus on developing an end-to-end solution ecosystem, spanning from strategic consulting to the implementation of an AI-powered smart manufacturing management platform tailored to the Vietnam market. This integrated approach enables enterprises to achieve synchronized, scalable, and sustainable digital transformation, rather than isolated improvements.

In the context of Vietnam’s rapidly evolving manufacturing sector, the demand for Smart Factory adoption is becoming increasingly urgent. As the Government positions digital transformation as a core pillar of national economic development, manufacturers are under growing pressure to modernize operations, enhance productivity, and improve global competitiveness. This collaboration is therefore expected to play a practical role in supporting manufacturers to accelerate their transition toward smarter, data-driven production models.

Beyond technical implementation, the collaboration also serves as a strategic foundation for both parties to demonstrate their capabilities to government stakeholders, to unlock funding opportunities, and participate in larger-scale Smart Factory initiatives in the future.

Strategic Significance – Strengthening Vietnam – South Korea Cooperation Through Smart Manufacturing

The Vietnam – Korea Business Partnership 2026 serves as a key trade promotion platform, bringing together numerous South Korean and Vietnamese enterprises to explore business matching, technology exchange, and investment opportunities. As a structured mechanism for fostering bilateral economic cooperation, the event plays an important role in strengthening connections between the two business communities and accelerating collaboration in high-potential sectors, including digital transformation and manufacturing. High-level government executives from both countries, notably including South Korea’s President Lee Jae Myung and Vietnam’s Prime Minister Le Minh Hung, participated in this event, highlighting the strategic importance of this platform. 

More than 73 business deals were signed at the event, across different industries including energy, tech, and infrastructure development – Demonstrating a tight economic relationship between the two economies. 

Companies participating in the signing ceremony at the Vietnam–Korea Business Partnership 2026.

Within this broader context, the MoU signing between NTQ Factory and Taejin System represents a meaningful and symbolic milestone. It reflects the growing depth of the comprehensive strategic partnership between Vietnam and South Korea, particularly in areas that are critical to future industrial growth. 

The collaboration between NTQ Factory and Taejin System represents a shared commitment of both parties in expanding smart factory adoption across Vietnamese and Korean-invested manufacturers, aiming to enhance their capabilities to elevate their competitiveness internationally, while fostering operations that align with the local environment. For NTQ Factory, this MoU embarks on a great step in building a global technology partner ecosystem around NxFactory, reinforcing the positioning of “Made In Vietnam” MES Solution in contributing to making a significant impact on the development of the regional smart factory.

Looking ahead, NTQ Factory and Taejin System expect this alliance to serve as a long-term catalyst: Not only for expanding Smart Factory adoption in Vietnam but also for strengthening bilateral cooperation through tangible, technology-driven outcomes. In doing so, the partnership contributes to attracting high-quality investment flows and reinforces Vietnam’s position as a rising hub in the global manufacturing landscape.

Most plant managers believe their equipment is operating at good capacity. However, when measured in practice, the average OEE of manufacturing plants globally is only around 60%. In other words, 40% of production capacity is being wasted every day without anyone seeing it.

So where does your factory stand?

The Silent Productivity Drain

In most factories, three problems occur continuously: unplanned machine stoppages, production shifts running slower than planned, and defective products requiring rework. Despite this, few people measure them systematically.

The consequences are:

• Leadership makes decisions based on gut feel or outdated paper reports
• The engineering team cannot accurately identify which equipment is the true bottleneck
• The entire factory continuously misses output targets without a clear root cause

That is precisely why OEE — Overall Equipment Effectiveness — was created to solve this problem.

What Is OEE? Formula & Definition

Simply put, OEE (Overall Equipment Effectiveness) or Total Equipment Efficiency is the global standard metric for evaluating how effectively a piece of manufacturing equipment actually operates compared to its theoretical potential.

The OEE Formula

OEE = Availability × Performance × Quality

Worked Example

Assume a production shift has the following metrics:

• Availability: 90% (machine stopped for 30 minutes in a 5-hour shift)
• Performance: 85% (running slower than standard speed)
• Quality: 98% (2% scrap rate)
• → Result: OEE = 90% × 85% × 98% ≈ 75%

What Is a Good OEE Score?

 Note for engineers: OEE is not an absolute number. Specifically, job shop factories typically have lower OEE than mass production factories, and that is completely normal.

The Six Big Losses Destroying Your OEE

To understand more clearly, OEE is built on the Six Big Losses framework in TPM (Total Productive Maintenance). Specifically, these 6 losses are divided by component:

 Affecting Availability:

1. Unplanned Downtime: unplanned failures, unexpected breakdowns
2. Planned Downtime: mold changes, adjustments, new product setup

 Affecting Performance:

3. Speed Loss: running below design speed
4. Minor Stops & Idling: small jams, temporary sensor faults, brief waits

Loss Group Quality:

5. Production Defects: scrap and rework during stable production
6. Startup Defects: defective output when starting a shift or after product changeover

Notably, Performance loss is the most commonly overlooked. The reason is that the machine is still running, but slower than standard by 10–20% and no one sees that on the shift report.

Beyond that, each industry has its own weaknesses. For example, the electronics & packaging sector suffers heavily from minor stops and setup time when changing SKUs frequently. Meanwhile, the automotive sector is particularly sensitive to Quality rate due to strict tolerance requirements.

From Metric to Action: A Smart Manufacturing IoT Platform

Knowing what OEE is only gets you so far. The more important question is: how do you collect accurate, continuous data and turn it into specific actions?

Many factories still calculate OEE manually recording in Excel after each shift, or entering data from paper reports. This leads to delayed data, inaccuracy, and zero ability to spot trends in real time.

A smart IIoT platform like NxFactory by NTQ Factory takes a completely different approach:

• Direct PLC/SCADA integration to capture machine signals in real time — no manual input required
• Automated OEE calculation per machine, per shift, per line — down to the minute
• Six Big Losses Pareto analysis to identify the right priority root cause
• Anomaly alerts when Availability or Performance drops below threshold
• Real-time shopfloor dashboards displayed on factory screens so the entire team monitors together

As a result, factories deploying NxFactory report clear outcomes: 17% reduction in machine downtime, 12% shorter production cycles, and up to 50–90% reduction in manual reporting effort.

In other words, these results do not come from a prettier OEE number but because the operations team can finally see the right problem, at the right time. To better understand how the system works, you can learn more about AI analytics & production reporting.

Conclusion: OEE Is the Common Language of the Modern Factory

In summary, OEE is not just a metric — it is the common language between leadership, production management, and the engineering team. When all three groups look at the same accurate data, the factory can improve systematically.

Therefore, if your factory has not yet measured OEE or is still doing so manually this is the moment to change that.

👉 Learn more or schedule a free demo at: nfactory.vn/request-a-demo/

1. What Is Predictive Maintenance — and How Is It Different From Scheduled Maintenance?

Most factories in Vietnam currently operate under one of two familiar models.

Reactive Maintenance: Fix it when it breaks. This approach is simple to manage, but extremely costly when failures strike mid-production shift.

Preventive Maintenance: Change the oil, replace filters, and run inspections on a fixed schedule — whether the machine needs it or not. This is more proactive; however, it still wastes resources and cannot prevent failures that occur between scheduled service dates.

Predictive Maintenance is the next step in this progression. Instead of responding to breakdowns or following a fixed calendar, the system continuously reads live data from each machine — temperature, vibration, pressure, rotational speed, current draw — and forecasts when a failure is likely to occur before the machine actually stops.

Three Models, One Core Difference

At their core, all three models differ on a single point: the timing of the maintenance decision.

Reactive maintenance makes the decision after the failure has already occurred. As a result, repair costs are highest and downtime is completely uncontrolled. Preventive maintenance makes the decision according to a fixed schedule — more disciplined, but still wasteful because parts are replaced even when the machine does not yet need it. Predictive maintenance is different — the decision is driven by real data, so maintenance happens on the right machine, at the right time, at the lowest possible cost. The only trade-off is the upfront investment in IoT sensors and monitoring software.

More importantly, predictive maintenance is not a future technology. It is already running inside Japanese and Korean FDI factories in Vietnam today.

2. The True Cost of a Single Unplanned Stoppage

Factory managers typically measure downtime by the number of hours a machine is down. However, the real figure is far larger once all cost categories are added together.

Emergency repair costs are typically 30–50% higher than planned procurement, because parts must be sourced urgently rather than through normal supply channels.

Lost output: A production line that stops for two hours at an electronics factory can mean thousands of lost units.

Quality costs: A machine in a degraded state often affects product quality before it stops entirely — defect rates rise without anyone understanding why.

Indirect labour costs: Emergency meetings, incident reports, and customer calls to explain late deliveries all add up.

Reputation with partners: For export-oriented factories, a single missed delivery can jeopardise a long-term commercial contract.

According to Deloitte research, unplanned downtime costs large industrial facilities an average of $260,000 per hour. For mid-sized plants in Vietnam, the absolute number is smaller — however, the impact on revenue remains highly significant.

3. How Predictive Maintenance Works in Practice

No deep technical knowledge is required. Below is how the system operates from a factory manager’s perspective.

Step 1 — Connect the Machines

IoT sensors measuring temperature, vibration, and current are installed on production equipment. Data is collected continuously — not at end of shift, not once a week, but every second.

Step 2 — Establish a Baseline

The system learns what “normal” looks like for each individual machine. For example, what is the typical operating temperature of a CNC machine running at full capacity? What is the expected vibration level? This baseline becomes the reference point for all future comparisons.

Step 3 — Detect Anomalies Early

When any parameter deviates from the baseline — for instance, if a bearing temperature rises 8°C above its normal range — the system immediately sends an alert to the supervisor and maintenance team. This happens before the operator on the floor notices anything is wrong.

Step 4 — Make an Informed Decision

Rather than stopping production for a scheduled inspection, the maintenance team checks the dashboard and plans proactively: this machine needs attention at the end of Friday’s shift, therefore no production targets for the week are disrupted.

Step 5 — Analyse Root Causes

The complete data history for every machine is stored in the system. Consequently, when an incident occurs, the engineering team can trace backward to understand why — and take steps to prevent it from recurring.

4. How Vietnamese Factories Are Applying This: Two Real Cases

Case 1: Mechanical Components Plant, Thang Long Industrial Zone, Hanoi

This Japanese FDI plant manufactures drivetrain components for industrial forklifts. It operates as a Tier 1–2 supplier within the Sumitomo and Hyster-Yale supply chain, exporting to the United States, Europe, and Southeast Asia.

Before deployment: The plant had no accurate real-time visibility into machine condition. All fault records were logged manually — slow and inconsistent. When a machine stopped, the root cause was unclear and root-cause analysis often took several days. Supervisors received information late, so their responses were correspondingly delayed.

Results after deploying NxFactory:

• 31 machines connected and synchronised with real-time data.
• 90% of manual data-entry tasks eliminated entirely.
• Downtime reduced by 21% within the first six months.
• Supervisors receive instant alerts instead of waiting for end-of-shift reports.

“The biggest change was not the 21% figure — it was that we now know what every machine is doing at any given moment, instead of only finding out when it has already broken down.”

Case 2: Electronics Plant, Bac Ninh

This Korean FDI facility was established in 2012, specialising in precision electronic components for the automotive and smart device sectors. It operates five workshops with 31 automated SMT and assembly lines and approximately 600 workers.

Core problem: Manual maintenance and quality inspection processes were slowing defect detection and extending unnecessary downtime.

Results after deployment:

• Five workshops and 31 lines connected and monitored in real time.
• The system automatically identified the top 10 downtime causes, allowing the maintenance team to prioritise the right areas.
• Smart pre-operation checklists ensured machines were ready before each shift began.
• Downtime fell by 16%, and monthly output increased by more than 3 million units.

Both cases share one important characteristic: results came not from investing in new equipment, but from getting substantially more out of the machines already on the floor.

5. Signs Your Factory Needs to Act Now

If at least three of the following situations apply to your operation, predictive maintenance is no longer a “nice to have” — it is an immediate priority.

• Machine failures are discovered after the stoppage has already occurred, never in advance.
• Downtime reasons are recorded in Excel or on paper, and entries are inconsistent between shifts.
• Preventive maintenance schedules are regularly disrupted because failures occur before the planned service date.
• Product defect rates are rising without a clear explanation, and machine condition is a likely contributing factor.
• It takes a supervisor more than 30 minutes to determine why a machine has stopped.
• Emergency parts purchases represent a significant and recurring share of the monthly maintenance budget.
• The question “What is the OEE of Line X this week?” cannot be answered immediately — it requires time to manually aggregate data from multiple sources.

6. Where to Start — A Practical Roadmap for Factory Managers

Predictive maintenance does not require a full-plant deployment from day one. In practice, most factories in Vietnam follow an incremental rollout path.

Months 1–2: Pilot One Line
Select the line with the highest historical downtime or largest repair costs. Connect the machines and begin collecting baseline data. This phase requires no changes to existing operating procedures.

Months 3–4: Read the Results and Adjust
After six to eight weeks, the system has accumulated enough data to reveal meaningful patterns. This is the phase where the maintenance team learns to read early-warning alerts and act on them — rather than waiting for a failure to force a response.

Months 5–6: Evaluate ROI and Plan Expansion
Compare downtime figures, emergency repair costs, and output volumes before and after. This real-world data becomes the business case to present to management and request budget for broader rollout.

Month 7 Onwards: Scale Across the Plant
Extend connectivity to the remaining lines. Integrate with existing ERP or MES systems where applicable. Establish standardised maintenance KPIs across the entire facility.

Conclusion

Predictive maintenance is not the story of a “factory of the future” — it is happening right now inside FDI plants in Bac Ninh, Thang Long, and Binh Duong. Therefore, the question is no longer whether to adopt it, but where to start and with whom.

If you manage a facility with more than 20 machines, are currently logging maintenance data in Excel, and are facing pressure on OEE and delivery reliability — now is the right time to have a concrete conversation.

→ Explore real case studies from plants like yours, Book a 30-minute demo with the NTQ Factory team