
Smart Factories and Automation
Smart Factories
To enhance factory efficiency, improve manufacturing process quality and meet customer delivery time demands, ASEH began to invest in automated, lights-out factories in 2015. Automation, heterogeneous integration in machine and production systems, and heterogeneous integration in systems-in-package (SiP) are 3 major forces driving smart factories and digital transformation at ASEH. In 2011, ASE established the ASE CIM Committee comprising of automation teams from various business units (lead frame packaging, ball-grid array packaging, flip chip packaging, wafer-level packaging, SiP packaging and test services) and the Information Management Center. By 2021, the company has 25 lights-out factories in operation, with more than 600 automation engineers trained, and over 45 industry-academia research projects developed.
Innovative and Breakthrough Methods Adopted in the Creation of Smart Factories
Challenge | Problems encountered | Solution |
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Inadequate equipment connectivity |
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High complexity of product tracking |
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Lack of local automated equipment supply chains |
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Lack of qualified personnel |
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Smart Factory Milestones
Introduced the recipe management system (RMS)
As a control measure before mass production, the EAP transfers data to equipment through SECS/GEM, ensuring data validity and improving overall equipment efficiency (OEE).
Inhouse-developed Semiconductor Equipment Communications Standard (SECS) equipment automation program (EAP)
To overcome challenges in equipment connection program development, we designed a development platform for standardized equipment connection programs, solving process design problems, lowering program development complexity, and increasing human-machine ratios and operation time.
Implemented the fault detection and classification (FDC) system
By collecting equipment production parameters in real-time, systems are able to report equipment status immediately and check formal functions automatically so that warning signals are issued when malfunctions occur, thereby preventing the repeated manufacturing of defective products and ensuring that reporting mechanisms are in place to detect malfunctions in real time.
Introduced robotic arms and automated guided vehicles (AGVs)
AGVs and robotic arms were integrated to introduce the autonomous mobile robot (AMR) that can support transport operations, thus reducing manpower on the floor and maximizing packaging capacity.
Ushering in the era of AI
Applying AI powered detection technology to identify and intercept any malfunctioning equipment that may compromise information security and prevent any information security incidents. The inhouse developed technology helps mitigate information security risks and reduce investment costs.
Incorporated the predictive maintenance system (PdM) (Predictive Maintenance, PdM)
A predictive maintenance system helps determine equipment that is likely to require maintenance and predicts equipment component failures and malfunctions in advance. The system allows early notification of maintenance personnel to service the equipment, thereby lowering equipment failure time.
Launched the world’s first 5G mmWave smart factory
The 5G mmWave smart factory was a collaborative effort between ASE, Chunghwa Telecom and Qualcomm, showcasing the future of automation and smart factories. 3 use cases were developed to demonstrate the use of 5G mmWave in smart factories - automated production line inspection using AI+AGV, remote AR maintenance and the AR experience at the ASE green technology center.
Build an IAI platform to promote widespread application of AI
In 2018, ASE ushered in the era of AI. In addition to actively cultivating AI technology talent, we began to build the IAI platform to create an AI no code environment and promote widespread application of AI throughout the company.
Sustainable Impact of Smart Factories
Our smart factory concept began with a strong foundation in automation, and the heterogeneous integration of customers, suppliers and production processes, to drive the semiconductor industry onto a higher value chain and accelerate technology advancements. Smart factories represent the next leap for the semiconductor packaging and test industry to play an enabling role beyond More than Moore.
Automation technologies introduced in 2021
Introduce the popularization of AI platform
The IAI (Industrial AI) platform hopes to quickly introduce AI learning, pass on experience through AI, and create a company culture of national AI. As long as data is provided, different prediction models can be built to achieve the purpose of production capacity, quality, and process prediction.
RPA (Robotic Process Automation)
RPA is a software bot uses a combination of automation, computer vision and machine learning to carry out a ton of mundane and repetitive computer-based tasks at error-free, high volume and speed that are previously handled by humans.
RTD (Real Time Dispatcher)
RTD (Real Time Dispatcher) aims at maximizing efficiency and output, considering various production conditions, using powerful computers and big data to develop intelligent dispatching systems and automatic dispatching systems to shorten the production cycle.