By Sursha Wu
Introduction
Driven by advancements in technology, smart factories have become a key competitive goal for the manufacturing industry.
Smart factories rely on technologies like AI and IoT to enable data-driven production to achieve higher quality and efficiency. The implementation helps companies respond quickly and accurately to market demands and on the other hand, transforms traditional manufacturing methods.
Explore top smart factory transformation cases.
2025 Smart Factory Trend: Lean Manufacturing
Why smart factory? What drives companies to consider smart factory deployment?
As businesses evolve with the times, when production costs outweigh gross margins, companies will pursue lean production and smart manufacturing transformation.
── Kevin Liang, Technical Account Manager Corporate Strategic Business Development and Alliance, Delta Electronic, Inc.
Watch the full PowerTalk discussion on YouTube: Challenges and Strategies in Smart Factory
The goal of lean manufacturing is to achieve maximum efficiency with minimal input—whether in terms of labor, materials, space, or production time.
In recent years, international politics and the post-pandemic era have caused production and operational costs to exceed product margins, therefore reducing profits. Facing this pressure, many manufacturers are adopting lean manufacturing as a solution.
The essence of smart factory transformation is to achieve the benefits of lean manufacturing. By improving resource utilization, companies can reduce costs, increase profit margins, and ultimately drive revenue growth. However, these goals can no longer be achieved by using these traditional manufacturing methods.
To achieve lean manufacturing, companies can use automation equipment and AI technologies. These tools help optimize production processes and improve quality, management, and efficiency.
Why Smart Factory Matters: Quality, Efficiency, Costs
For manufacturers, adopting smart manufacturing requires significant investment and comprehensive long-term planning. As a result, real operational pressures are often the main reason for companies to transform into smart factories.
The biggest push comes from fundamental production problems: poor quality and higher costs. More importantly, as production environments grow increasingly complex, these challenges can no longer be solved by the use of traditional methods.
Under these conditions, companies are turning to smart manufacturing, using advanced technologies to resolve persistent problems and prepare for future competition.
Case Study 1: Factory in Vietnam Struggling to Meet Quality and Efficiency Goals
Geopolitical factors have led many manufacturers in China to diversify their production strategies to strengthen supply chain resilience.
Southeast Asia, with its geographical advantages and low labor costs, has quickly become the top choice for factory relocation.
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One well-known electronics manufacturer specializing in networking equipment has established a new factory in Vietnam due to this trend.
However, management discovered significant issues with quality and production efficiency after the factory began operations.
According to management, production efficiency in the Vietnam factory lagged behind the factory in China by 20-30%. Despite Vietnamese workers’ salaries are related low, the factory still faced persistent issues with yield rates, quality problems, and production inefficiencies.
The root cause was the instability of the workforce, which led to unexpected production variables.
Here are some common details of challenges:
Operators fail to follow SOPs, reducing yield rates.
Although production engineers had designed detailed SOPs, operators often failed to follow them during actual production.
In some cases, pressure to improve efficiency led to non-compliant practices. For example, operators adjusted screwdriver torque to speed up assembly. While this temporarily increased productivity, it negatively impacted product yield rates.
Download Case Study: AI-powered SOP tracking ensures Poka-Yoke in the process.
Long Learning Curves Lowering Efficiency
Although skilled workers were available to support production, they were typically assigned to critical quality control stations or detailed inspection and cleaning tasks.
Meanwhile, other productions relied on inexperienced operators. Due to their lack of experience, new operators required extensive training to reach standard operational levels, significantly limiting overall production efficiency.
On-Site Demo: Management systems mitigating quality issues caused by inexperienced operators.
Adopting Smart Factory Solutions to Address Anomalies
We want to get the same yield as China factory, but we need a system that provides objective production data to address the root causes.
── Electronics Manufacturer, Vietnam Production Line Engineer
Management finds it difficult to unify solutions for production line issues because different departments have different perspectives.
A production line engineer explained that the lack of objective data makes it hard for management to identify root causes in time. This issue further reduces the efficiency of improvements.
Management wants a system that provides accurate and complete production line data. They also want the system to record previous improvement efforts, which would help expatriate managers optimize processes using past experiences.
PowerArena HOP（Human Operation Platform）supports CLCA
Book a Demo Now: See how the system does CLCA!
Case Study 2: Thai Factory Struggling to Meet Production Targets
See the Success Case: PowerArena helps launch a smart factory within four weeks.
Another well-known power supply manufacturer established a new factory in Thailand in response to policy changes.
The company initially anticipated the Thai factory would surpass the production capacity of its Chinese counterpart, but the outcome did not meet expectations.
Limited Resources Hinder Quality Assurance
Thai factory employs only a few local industrial engineers with limited product experience. While experienced Chinese and Taiwanese managers provide short-term support during business trips, production efficiency and quality would decline once they leave.
The managers told PowerArena that accelerating the learning curve is a critical need for Thai factory.
By adopting PowerArena HOP, the factory aims to introduce best practices and record successful workflows, and share them to other facilities. PowerArena HOP acts as a training tool to reduce the learning curve for local workers, helping them quickly adapt to operational requirements.
Success Case: How to Copy and Paste Model Production Lines?
High Turnover Rates Disrupt Operations
Thai factory faces challenges with high worker turnover. Many employees leave after only a few days, which disrupts operations. Thai workers have a skills gap compared to their counterparts in the Chinese factory. Frequent reliance on inexperienced new hires makes it difficult for the factory to meet the quality standards required by brands.
Some brands have warned that they will cancel orders if quality does not improve. Customers have also begun reviewing the factory’s progress in deploying AI, which has created additional pressure.
The management team uses PowerArena as a remote management tool. This solution could address the lack of transparency in operations and provide senior leadership with clear insights into Thai factory’s performance and operational challenges.
Smart Factory Transformation Strategies
Spend 70% of your focus on your core business and 30% on understanding how global developments relate to it. How decision-makers view and approach new technologies will be the key to successfully transitioning to smart manufacturing.
── Ray Tai, Vice President & Innovation Base Director, Mighty Net
Watch the full interview: Transformation story of a 30-year-old OEM/ODM electronics manufacturer.
Smart factory transformation requires long-term planning and sustained investment. The ideal approach is to maintain ongoing operations while successfully integrating innovative solutions.
Based on insights from smart manufacturing executives, PowerArena summarizes three practical steps for systematically planning a transformation.
Step 1: Identify Production Pain Points
Change should happen step by step. Start by identifying the factory’s pain points, and then find solutions to address them in stages.
── Kevin Liang, Strategic Business Development & Alliance Technology Manager, Delta Electronics
The first step is to identify the key issues impacting production or management. These could include challenges like inefficiencies, quality issues, or a lack of transparency, such as reducing waste in specific materials.
Clear identification of core problems allows businesses to find suitable solutions effectively.
Step 2: Leverage External Expertise
External AI teams can identify the right data, collect and clean it, train AI models, and provide insights—capabilities that are often difficult for in-house teams to achieve.
── Ray Chi, Business Development Manager, Advantech
PowerArena combines leading AI technology with deep expertise in manufacturing operations.
We provide technical support and practical solutions, helping clients quickly identify production line issues. By combining technology with operational knowledge, PowerArena delivers long-term value for production lines.
Our domain-specific expertise in manufacturing ensures rapid implementation and faster results, helping clients quickly achieve their goals.
Further Reading: PowerArena’s Role in AI Deployment: Supporting Manufacturers Every Step of the Way
Step 3: Start Small with Pilot Projects
Talk to our smart manufacturing experts to explore more about smart factory solutions.
Always begin with a small pilot. Use existing cameras or available footage to analyze and identify the best use cases for AI deployment.
── Pieno Lee, Edge Computing Business Development Manager, Lenovo Asia-Pacific
To avoid unnecessary costs without proven benefits, PowerArena offers smart manufacturing consulting services. Through close collaboration and production line evaluations, we design tailored solutions to maximize value and enable efficient smart factory deployment.
