When an automobile production line runs precisely at midnight unattended, when engineers thousands
of miles away adjust equipment parameters through a virtual interface, when factory energy consumption
data is optimized in real time to reduce carbon emissions... These are not science fiction scenes, but industrial
automation solutions are reshaping the reality. It is like the “nerve center” and “intelligent engine” of modern
manufacturing, transforming data flow into productivity, forging unparalleled competitive advantages for
enterprises in the three dimensions of efficiency, quality and resilience.
Pain point breakthrough: automation how to accurately dismantle the
manufacturing problem
The traditional manufacturing industry is facing unprecedented pressure chain: labor costs continue to rise, process
standards are difficult to absolute unity, equipment accidental downtime loss is huge, small batch customization
demand has increased dramatically, the global supply chain fluctuations intensify ... ... Industrial automation solutions
are designed to solve these problems:
Efficiency bottleneck: Manual handling, repetitive testing, and poor process connection eat up valuable time. Automated
production lines to realize 7x24 hours of continuous operation, robots accurately perform highly repetitive tasks, logistics
AGV seamless flow, production efficiency by 30% -50% has become the norm.
Quality fluctuation: Manual operation is prone to fatigue, skill differences lead to poor product consistency. High-precision
machine vision system realizes millimeter-level defect detection, precision robot welding, assembly error is close to the
theoretical limit, data-driven process control makes the goal of “zero defects” within reach.
Cost pressure: Manpower, energy consumption, material waste, equipment maintenance and quality loss constitute a
huge cost black hole. Automation optimizes resource scheduling, reduces waste, and predictive maintenance avoids
unplanned downtime, significantly diluting unit production costs.
Flexibility Challenge: Markets change quickly, orders fluctuate, and traditional production lines are time-consuming and
labor-intensive to switch. Modular automation cells, programmable robots, and flexible conveyor systems enable the
same production line to switch to different products in a very short period of time for quick response to the market.
Core Architecture: The Four Pillars of Building a Smart Factory
A set of mature and implementable industrial automation solutions is not a single point of technology stacking,
but a multi-layered, synergistic organic whole:
Sensing and execution layer (“hand” and “eye”):
Industrial robots: from heavy-duty palletizing to precision electronics assembly, multi-joint, SCARA, and collaborative robots.
Intelligent sensing network: high-precision vision cameras, laser ranging, force sensors, RFID, temperature and humidity
sensors, etc., real-time capture of massive state data on the production line.
Intelligent equipment and actuators: Servo-driven precision robotic arms, intelligent valves, variable-frequency motors,
etc., accurately executing control commands.
Control and network layer (“nerves” and “blood vessels”):
Industrial Control System (ICS): PLC (Programmable Logic Controller) as the field “brain”, real-time processing logic control;
DCS (Distributed Control System) management of large-scale process industries; SCADA (Data Acquisition and Monitoring
System) to provide global visualization and remote control.
Industrial network: Industrial Ethernet (e.g. Profinet, EtherCAT), TSN (Time Sensitive Network), 5G private network, etc., to
ensure high-speed, reliable and low-latency transmission of massive data and support real-time control.
Data and platform layer (“heart” and “think tank”):
Industrial Internet of Things (IIoT) platform: Aggregate equipment, process, energy consumption, quality and other domain
data to achieve unified access, management, storage and analysis.
Edge Computing: Real-time data processing and response near the device end, reducing the burden on the cloud and
meeting millisecond control requirements.
Data center: Cleansing and integrating heterogeneous data from multiple sources to provide high-quality “fuel” for
upper-layer applications.
Intelligent application layer (“brain” and “commander”):
Manufacturing Execution System (MES): Connects the planning layer with the control layer to achieve production scheduling,
process management, quality traceability, and equipment performance (OEE) optimization.
Digital Twin: Build virtual maps of physical plants for simulation optimization, predictive maintenance, remote commissioning
and personnel training.
AI-driven applications: Machine learning algorithms for predicting equipment failures, optimizing process parameters,
intelligent scheduling, automated visual quality inspection, and refined energy management.
Value on the ground: from concept to quantifiable competitive advantage
The core objective of investing in automation solutions is to capture measurable business value:
Efficiency leap: Overall equipment efficiency (OEE) improves by 15%-30%, per capita output increases significantly, and
order delivery cycle time is shortened dramatically.
Quality Leap: 30%-70% reduction in product defect rate, full process quality traceability, sharp reduction in customer
complaints, and improved brand reputation.
Cost optimization: direct labor costs, energy costs, material waste, quality loss costs decreased simultaneously,
comprehensive manufacturing costs effectively reduced.
Enhanced Flexibility: New Product Introduction (NPI) time is shortened, line changeover time is compressed from hourly
to minute, rapid response to individualized orders.
Safety and Sustainability: Workers are liberated from dangerous, heavy and boring positions, and workplace accidents are
reduced; through optimized scheduling and energy management, energy consumption and carbon emissions per unit of
output value are reduced.
The Way to Success: Customization and Continuous Evolution
Industrial automation is not a “one-shot deal”, and successful deployments need to follow key principles:
Demand-oriented, precise planning: In-depth analysis of the core pain points of the enterprise, process flow, existing
infrastructure and investment budget, to develop a clear automation roadmap and milestones.
Open integration and compatibility: Select systems and equipment that support mainstream communication protocols
(e.g. OPC UA) to ensure seamless interoperability between new and old equipment and heterogeneous systems.
Modularization and Expandability: Adopt modular design to facilitate future function expansion, production line adjustment
and technology upgrading, and protect long-term investment.
Human-machine collaboration: Automation is not a complete replacement of human labor, but a combination of human
creativity and decision-making power with the precision and endurance of machines to design an efficient
human-machine collaboration model.
Data-driven, continuous optimization: Establish a data collection and analysis system to continuously optimize production
processes, maintenance strategies and management decisions based on real-time insights.
Partner Selection and Knowledge Transfer: Select partners with deep industry experience, technical strength and
continuous service capability, and emphasize on technical training and capacity building of internal team.
Toward the Future: The Unlimited Possibilities of Intelligent Manufacturing
Industrial automation solutions are accelerating the deep integration with AI, 5G, cloud computing, and big data, and
are evolving in the direction of greater intelligence and autonomy:
More powerful AI empowerment: from predictive maintenance to autonomous process optimization and adaptive control,
AI will be more deeply integrated into the automation core.
Popularization of flexible automation: Easier to program, safer collaborative robots, smarter AGV/AMR, promote the
popularization of flexible automation for small and medium batch, multi-variety production.
Deepening of Cloud-Edge Collaboration: Edge computing handles real-time control and low-latency requirements,
while the cloud provides powerful computing power and AI model training, making the collaborative architecture
more mature.
Sustainability Priority: Automation technology will be more focused on energy efficiency optimization, resource
recycling and low-carbon manufacturing, helping industrial green transformation.
Industrial automation solutions have changed from “optional” to “mandatory” for the survival and development of
manufacturing enterprises. It is not only a tool to improve efficiency, but also a strategic fulcrum for enterprises to
build core competitiveness. Embracing automation means embracing a more efficient, better quality, more flexible
and more sustainable future. When the flood of data rushes in the intelligent network, when the invisible algorithm
accurately directs the tangible equipment, the power of industrial automation is quietly reshaping the competitive
pattern of the global manufacturing industry, driving the next industrial revolution to break the waves forward.