Hsinchu, Taiwan – AUO announced that it has been recognized by the Manufacturing Leadership Awards (MLA) in categories of Digital Network Connectivity as well as AI and Machine Learning, and especially honored the High Achiever in Sustainability and the Circular Economy category by the National Association of Manufacturers (NAM) in the US.
Drawing up on its years of experience in smart manufacturing and digital transformation, AUO combined AIoT, digital IoT and data analytics technologies to build a machine doctor for carrying a comprehensive health exam of factories. Appling its wealth of green manufacturing expertise to transform old factories into sustainable smart factories, AUO successfully won the international recognitions.
“AUO drew on the extensive experience in smart manufacturing to actively invest in digital transformation and cultivation of AI talent. The AUO Group also embraced sustainability as our core philosophy and continued to refine our green production process technologies,” said AUO Chairman and CEO Paul SL Peng. “AUO was selected for the Global Lighthouse Network by the World Economic Forum last year and is honored to be recognized by yet another top international award. We will continue to spearhead industry developments and put our corporate philosophy of inclusive sustainability into practice.”
“AUO is truly a champion of sustainability and the goal of a circular economy,” said David R. Brousell, Co-Founder of the Manufacturing Leadership Council and one of the judges in this year’s Manufacturing Leadership Awards competition. “AUO’s accomplishments in water resource management, specifically in water reduction and recycling, should be held high as an example to other companies on what can be achieved when a well thought out and committed strategy is in place. We are pleased to honor AUO with the ‘Sustainability and the Circular Economy’ category award, the only Taiwanese company to be so recognized this year.”
AUO has been an active proponent of digital transformation in recent years. AUO Digital Network Connectivity (AUDNC) was developed to collect equipment data through sensors and transmit them through Wi-Fi base stations deployed throughout the factory. Big data analysis is then carried out by the prognostics and health management platform (PHM platform) to provide early warning and troubleshooting of potential equipment problems to effectively reduce unexpected production line stoppages and improve equipment activation.
AUO was able to use the combination of AUDNC deployment and PHM monitoring to design a machine doctor for conducting AI-powered “visual inspection” and “auscultation” that assess and diagnose the health of machine equipment and their components.
For visual inspection, the “GRAPIC” smart visual recognition software developed by AUO has a wide variety of applications in three areas: factory quality management, equipment maintenance, and personnel safety management. In quality management, smart visual inspection can be used to pick up product flaws, carry out precision measurements of dimensions during production, and monitor operator SOP.
In equipment maintenance, it enables active detection of deviations in machine components, ensures equipment operating at right angles, and reduces scrapping costs from equipment failures. In personnel safety management, it helps verify that factory workers are wearing proper protective gears, and also detect hazardous situations such as mobile phone use within the factory or falls in single-worker zones.
By translating its extensive manufacturing expertise and experience into smart visual detection technologies, AUO was able to develop software that personnel from non-programming backgrounds could use to obtain a “clearer picture” during production and effectively reduce the factory’s operation and maintenance costs.
Auscultation is another important skill that the machine doctor can use for health exams in addition to visual inspection. The “stethoscope” used by clinical physicians inspired the use of “vibration pickups” by AUO to captured equipment sounds. Edge computing technology is then used to analyze the audio data and visualize the results for the PHM platform to help production line personnel track the health of their equipment. By “listening” for equipment anomalies or potential hazards, equipment management and maintenance can be conducted more efficiently.
AUO’s manufacturing experience and domain know-how combined with AI health exams by the machine doctor and PHM monitoring can solve the pain points of old factories with high precision and boost productivity by up to 30%. AUO also transformed its years of internal experience into smart manufacturing solutions offered by its subsidiary AUO Digitech. These solutions provide old factories with an upgrade and the industry with greater impetus for transformation.
