Discover the top priority manufacturing automation processes for businesses embarking on their automation journey, focusing on operational optimization. This article explores the benefits, practical applications, and the development roadmap from RPA to Intelligent Automation and Agentic Automation, helping businesses enhance efficiency and achieve sustainable growth.
In the face of increasingly fierce global competition and relentless pressure for operational efficiency, the manufacturing sector in Vietnam and Southeast Asia is witnessing a strong wave of digital transformation. Businesses clearly recognize that applying advanced technology solutions is key to maintaining a competitive edge and achieving sustainable development. Among these, operational optimization automation emerges as a strategic tool, offering immense potential to improve productivity, reduce costs, enhance quality, and free up resources for more strategic activities.
According to a Gartner report, the Robotic Process Automation (RPA) software market, the initial foundation for operational optimization automation, grew by 19.5% globally in 2023, with an estimated total market value of 3.1 billion USD. The Asia-Pacific region saw even more impressive growth, indicating strong interest and investment in this technology. For the manufacturing industry, a Deloitte study indicates that businesses implementing process automation can achieve average operational cost reductions of 20% to 40% and productivity increases of up to 30%.
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The Roadmap of Operational Optimization Automation in Manufacturing: From RPA to APA
According to experts, the automation journey for businesses typically unfolds in three stages:
- Stage 1: Robotic Process Automation (RPA): This is the initial stage, focusing on automating repetitive, rule-based, and clearly structured tasks. Software robots (bots) mimic human actions on the user interfaces of various applications. Examples include automating data entry, data extraction, sending emails, and generating basic reports. This is a fundamental step in manufacturing automation.
- Stage 2: Intelligent Automation (IA): The next step involves integrating artificial intelligence (AI) technologies such as Machine Learning (ML), Natural Language Processing (NLP), Computer Vision, and Process Mining into RPA. IA enables the automation of more complex processes that require decision-making capabilities, unstructured data processing, and learning from data. Examples include automating complex invoice analysis, predicting machinery maintenance needs, and image-based product quality inspection. This stage significantly boosts operational optimization automation.
- Stage 3: Agentic Process Automation (APA): The final and most advanced stage, APA aims to build intelligent “agents” capable of autonomy, continuous learning, and collaboration to execute complex processes flexibly and efficiently. These agents can make context-based decisions, automatically handle exceptions, and optimize processes in real-time. For example, an agent could autonomously manage the entire procurement process, from identifying needs, finding suppliers, and negotiating prices to tracking orders and payments. This represents the pinnacle of manufacturing automation.
For manufacturing businesses in Vietnam and Southeast Asia just starting, focusing on the RPA stage is a logical step to quickly achieve initial benefits. After gaining experience and building a solid foundation, businesses can gradually progress to the IA and APA stages to fully exploit the potential of automation in optimizing the entire manufacturing value chain.
Why is Operational Optimization Automation an Inevitable Step for the Regional Manufacturing Sector?
The urgency of operational optimization automation in the manufacturing industry in Vietnam and Southeast Asia is clearer than ever, driven by several factors:
- Increased Competitive Pressure: In a globalized market, manufacturing businesses face intense competition from other countries. Automation helps improve operational efficiency, reduce production costs, and offer products at more competitive prices.
- The Human Resources Challenge: Besides rising labor costs (estimated to increase by an average of 5-10% annually in many countries in the region), businesses also face challenges in finding and retaining skilled labor, especially for repetitive and high-precision jobs. Manufacturing automation helps reduce dependence on manual labor and addresses personnel shortages.
- Ever-Increasing Demands for Quality and Speed: Customers increasingly expect higher quality products and faster delivery times. Automation improves the accuracy of manufacturing processes, minimizes errors, and shortens production cycle times. According to one study, applying automation can help reduce product defect rates by up to 90% in some processes.
- Technological Advancements: Automation technologies are becoming more powerful, flexible, and accessible. Modern RPA platforms are equipped with many advanced features and user-friendly interfaces, making it easier for businesses to deploy and manage software robots. This accessibility is crucial for operational optimization automation.
- Impact of Instability Factors: US tariff policies effective from early April 2025 and other uncertainties in the global supply chain have highlighted the importance of building a flexible and resilient manufacturing system. Automation helps minimize disruptions caused by external factors and ensures continuous production operations.
Top 5 Priority Processes for Manufacturing Automation: An Effective Starting Point for Operational Optimization
When embarking on their operational optimization automation journey, manufacturing businesses in Vietnam and Southeast Asia should focus on processes that deliver quick wins, are easy to implement, and have a significant impact on business operations. Here are the top 5 highly-rated priority processes:
Automation of Data Entry and Manufacturing Data Processing (Reducing Data Entry Time by 60%):
- Description: Tasks related to collecting, inputting, and processing data from various sources within the manufacturing process, including data from machinery (e.g., operating parameters, downtime), IoT (Internet of Things) sensors, Quality Management Systems (QMS), manual inspection sheets, and other paper documents.
- Application: Automating daily production output data entry (estimated to consume 20-30% of production staff’s time), quality inspection results (helping reduce waiting time for defect feedback by 15%), and machine parameters into ERP, MES, or other management systems. Automating data extraction from periodic reports (saving 40% of manual report generation time), order emails, and converting them into digital formats for analysis. This is a core component of manufacturing automation.
- Reason for Priority: These tasks often consume a significant amount of employee time, are highly repetitive, and prone to errors due to manual input (estimated manual data entry error rate can be 1-3%). Automation accelerates data processing by up to 60%, ensures near-perfect accuracy, and frees up employees for tasks requiring higher specialized skills. This directly contributes to operational optimization automation.
Order Management and Production Planning Automation (Reducing Order Processing Time by 50%):
- Description: Processes related to receiving customer orders (via email, portal, EDI – Electronic Data Interchange), checking raw material and finished goods inventory levels (often takes several hours to a day manually), creating Manufacturing Orders (MO), scheduling production based on machine capacity and delivery times (a complex, error-prone process), and tracking order fulfillment progress (requires constant updates and communication with relevant departments).
- Application: Automating the extraction of order information from various channels, automatically checking inventory levels (performed in seconds), automatically generating raw material purchase requests (when quantities fall below a set threshold), updating order status in real-time in the system, and automatically sending notifications to customers about delivery progress. In production planning, automation can synthesize data on production capacity (e.g., average machine runtime, setup time), market demand (based on sales forecasts), and delivery times to propose optimal production schedules, minimizing waiting times and maximizing machine utilization (can increase machine utilization by 10-15%). This is a crucial area for operational optimization automation in manufacturing.
- Reason for Priority: Efficient order management and production planning directly impact customer satisfaction and resource utilization. Automation helps reduce average order processing time by 50%, improves the accuracy of production plans (reducing plan deviations by up to 20%), and enhances the ability to respond quickly to changes in market demand.
Warehouse Management and Material Tracking Automation (Reducing Inventory Costs by 30%):
- Description: Tasks related to tracking the exact quantity and location of raw materials, semi-finished goods, and finished products in the warehouse (discrepancies between the system and reality often occur), performing warehouse receipt and issue transactions (requiring accurate recording of time and quantity), conducting periodic inventory counts (time-consuming and resource-intensive), and generating inventory reports (often done manually and with delays).
- Application: Automating the recording of warehouse receipt and issue transactions based on electronic documents (e.g., goods receipt notes, goods issue notes), automatically updating inventory quantities in the Warehouse Management System (WMS) or ERP, generating automatic alerts when inventory levels fall below safety thresholds (helping reduce the risk of material shortages by 15%), and supporting automated warehouse data reconciliation between the system and barcode/RFID scan results. Automation can also support the generation of periodic inventory reports and inventory trend analysis to optimize stock levels (can reduce inventory holding costs by 30%). This is a vital part of manufacturing automation.
- Reason for Priority: Effective warehouse management helps businesses avoid material shortages that cause production disruptions (estimated cost of production disruption can be up to 5-10% of revenue), minimize unnecessary inventory holding costs, and ensure the accuracy of inventory data, thereby supporting optimal purchasing and manufacturing decisions. This is a clear win for operational optimization automation.
Manufacturing Performance Reporting and Analysis Automation (Saving 70% of Report Generation Time)
- Description: The process of collecting data from multiple systems (e.g., MES, ERP, QMS, machine monitoring systems), consolidating, processing, and creating reports on manufacturing performance (e.g., actual vs. planned output, machine downtime and causes, defect rates, Overall Equipment Effectiveness – OEE, energy consumption). This often consumes a lot of time for engineers and production managers (can take several hours to a full day to create a complex report).
- Application: Automating the extraction of data from source systems on a scheduled basis, standardizing data in different formats, performing calculations, and generating visual reports (e.g., interactive dashboards) in the desired format (e.g., Excel, PDF, Power BI). Automation can also send these reports to relevant stakeholders on a schedule or when unusual events occur (e.g., when the defect rate exceeds the allowable threshold). Effective operational optimization automation relies on timely data.
- Reason for Priority: Manual report generation is not only time-consuming but also prone to errors and often delayed, preventing managers from having timely information to make corrective decisions. Automation saves up to 70% of report generation time, provides fast, accurate, and real-time information, allowing managers to effectively monitor manufacturing performance, identify bottlenecks, and make data-driven improvement decisions.
Quality Management and Compliance Automation (Reducing Quality-Related Costs by 25%)
- Description: Processes related to collecting quality inspection data (from measuring devices, manual inspection stations), recording inspection results (often done on paper or spreadsheets), tracking defects and non-conformities (requires consolidation and analysis to find root causes), generating quality reports (on defect rates, defect types, trends), and ensuring compliance with standards and regulations (e.g., ISO 9001, GMP).
- Application: Automating data collection from automatic measuring devices and quality inspection systems (e.g., computer vision systems), automatically inputting inspection results into the QMS, generating automatic alerts when defects exceeding permissible thresholds are detected (helping to react quickly to quality issues), automating the generation of periodic quality reports, and tracking Corrective and Preventive Actions (CAPA). Manufacturing automation can also support the creation of compliance documents and ensure consistency in performing standardized processes.
- Reason for Priority: Ensuring product quality and regulatory compliance is vital for the reputation and sustainable development of manufacturing enterprises. Automation enhances the consistency and accuracy of quality inspection processes (minimizing inspection errors), reduces response time to quality issues (helping minimize waste due to defective products), and ensures strict adherence to standards and regulations, thereby potentially reducing quality-related costs (including rework, warranty, recall costs) by up to 25%. This is a significant benefit of operational optimization automation.
Moving Towards the Future: Intelligent Automation and Autonomy in Manufacturing
The journey of operational optimization automation in the manufacturing industry doesn’t stop at replacing manual tasks with software robots. With the continuous advancement of artificial intelligence, we are witnessing a strong shift towards Intelligent Automation, where automated systems are capable of learning, adapting, and making more complex decisions. In the near future, Agentic Process Automation (APA) promises to deliver intelligent “agents” capable of complete autonomy in managing and optimizing manufacturing processes.
For manufacturing businesses in Vietnam and Southeast Asia, grasping this trend and building a methodical automation roadmap – from RPA to IA and further to APA – will be crucial for maintaining a competitive edge in the Industry 4.0 era. Investing in manufacturing automation technology now not only helps solve current challenges but also builds a solid foundation for a smarter, more flexible, and more efficient manufacturing future. Start your automation journey today to seize the opportunity to lead in this promising market.
