Smart Factories and Automation
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 2020, the company has 18 lights-out factories in operation, with more than 500 automation engineers trained, and over 45 industry-academia research projects developed.
Innovative and Breakthrough Methods Adopted in the Creation of Smart Factories
|Inadequate equipment connectivity||
|High complexity of product tracking||
|Lack of local automated equipment supply chains||
|Lack of qualified personnel||
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.
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 2020
|Real-time monitoring of key manufacturing data from production lines||To monitor real-time manufacturing data across all production lines||In collaboration with the sensors installed on all our manufacturing equipment for collecting real-time manufacturing data as well as the set up of an automated optical inspection (AOI) system for automatically detecting defective inventory, our manufacturing execution system (MES) can track and document all of the key data of the work in progress. This enables us to obtain and analyse data real-time and raises productivity immensely.|
|Using robots to automate mold cleaning||In the past, operators had to endure prolonged periods of heat to clean encapsulating molds.||In collaboration with the sensors installed on all our manufacturing equipment for collecting real-time manufacturing data as well as the set up of an automated optical inspection (AOI) system for automatically detecting defective inventory, our manufacturing execution system (MES) can track and document all of the key data of the work in progress. This enables us to obtain and analyse data real-time and raises productivity immensely.|
|Smart Control Center for immediate troubleshooting||To reduce manpower and costs, and minimize disruptions due to machine malfunctions and production halts||Our Smart Control Center monitors our automated production lines in real time and allows us to manage equipment across various production lines in a centralized manner. The control center is equipped with a Robotic Process Automation (RPA) system that enables engineers to re-configure machine software, perform automatic troubleshooting, identity and fix any equipment issues remotely through the use of live video feeds.|
|5G mmWave Smart Factory||To adapt the technology in smart factories that integrates analysis, detection, machine learning and optimization.||