Profet AI

With over 30 years of experience in manufacturing and maintaining machinery, Asia Giant Engineering Co, a well-known Taiwanese traditional manufacturing equipment manufacturer, primarily serves listed chemical companies in Taiwan. In recent years, faced with the dual pressure of challenges in recruiting new talents and the retirement of senior staff, the company has been actively embracing smart manufacturing. Using AI to propagate the experience from senior craftsmen into data, making the equipment smarter, and significantly increased the maintenance and service revenue. Furthermore, the company has integrated intelligent monitoring services into the manufacturing equipment, becoming a pioneer in the application of AI in traditional chemical industries.

Paul Hsu, COO of Asia Giant, is the key pusher of the implementation of AI to the industry. As a second-generation leader of the company, he encountered a wave of retirements among senior technical staff when he took over in 2020. “In the past, our senior craftsmen would rely on accumulated experience and their ‘hearing’ or ‘intuition’ to judge where equipment might have issues or which parts might be damaged. There was no data to support their assessments,” realizing that the experience of their senior craftsmen could not be preserved through mere qualitative or oral methods, he began exploring how to turn this experience into data through business AI, so as to use AI to propagate experience and technology.

No Need to Learn Additional Programming – Easy Adoption of AI Applications

After implementing the AI platform, Hsu began researching relevant solutions available in the market. With thorough consideration, he chose to adopt the AutoML (Automated Machine Learning) platform from Profet AI, which is based on core AutoML technology and known for its quick installation and user-friendly interface.

“The biggest incentive is not having to learn additional programming,” admits Hsu. He points out that with Profet AI products, there is no need to learn any extra programming. You can directly import data from Excel files into Profet AI’s AutoML Platform to obtain the main key factors behind the problems. This is particularly beneficial for traditional industries, as it saves a significant amount of time that would otherwise be spent on learning programming languages to get the answers needed in a short amount of time.

Furthermore, Profet AI’s consultants are exceptionally dedicated. In addition to sharing fundamental AI concepts, they assist in identifying data that can be analyzed behind the issues and help model the data to find directions for improvement and optimization. They also share valuable insights on how traditional mechanical equipment can be enhanced through AI and IoT integration to improve equipment reliability and efficiency. This collaborative approach has significantly reduced the exploring phase for Asia Giant during the AI implementation process. Even now, Profet AI’s consultants continue to hold frequent meetings with Asia Giant to discuss the next steps in AI application direction.

Implementing the Profet AI AutoML Platform has Resulted in a Remarkable Increase in Efficiency and Revenue of Over 30% in Asia Giant’s Maintenance Operations

While the core business revolves around equipment development, manufacturing, and sales, Asia Giant embarked on its AI journey by focusing on equipment maintenance.

Initially, Asia Giant installed sensors on their manufacturing equipment. Profet AI AutoML Platform utilized extensive data collection and continuous data modeling to identify anomalies in data trends, such as significant fluctuations, sudden spikes, or sharp declines. Subsequently, experienced technicians were consulted to identify the source of the issue or the damaged components. As similar data trends reappeared, AI autonomously learned and issued advance warnings. For instance, if there is a sudden downward curve in the data trends, it could indicate that the bearings are nearing failure. In this scenario, the AI system can proactively halt the equipment’s operation, allowing for maintenance, repair, or replacement of components in advance. If waiting until the equipment actually breaks down before performing maintenance, the cost of wasted chemical raw materials and waste disposal could amount to several million or even tens of millions of dollars.

“Relying on people is a passive approach,” said Hsu. When equipment breaks down, and personnel are dispatched for inspection or emergency handling, the last-minute manpower adjustments not only strain the manpower but also result in time-consuming procurement and replacement of lost materials and damaged components. The inability to immediately repair the equipment and restore normal operation for the production lines means that these waiting periods represent a waste of both manpower and time.

After implementing Profet AI AutoML Platform, Asia Giant’s maintenance services have significantly improved in efficiency and quality. The system not only enables advance warnings to clients, notifying them of the need to halt operations next month for preemptive replacement or repair of potentially damaged components, but also facilitates efficient manpower allocation and component readiness. This approach helps clients avoid unnecessary chemical raw material wastage. Hsu estimates that one year after adopting AI, the efficiency of Asia Giant’s maintenance personnel has increased by 50%, resulting in a 30% boost in the overall revenue of their maintenance business.

The Integration of Equipment with AI Intelligent Monitoring Systems Saw a Significant Growth of 40% in Equipment Orders

After witnessing the comprehensive benefits of introducing AI into maintenance and repair services, Asia Giant began integrating intelligent monitoring systems into other equipment. In May 2022, during the “Kaohsiung Automation Industrial Exhibition and Kaohsiung International Instrumentation & Chemical Engineering Exhibition,” they unveiled their first piece of equipment that combined the Profet AI system – the “Smart Vertical Agitation Machinery.”

According to Hsu, this innovative equipment is constructed through the integration of core components with sensors, forming an intelligent monitoring system. It allows for real-time monitoring of the agitation process, tracking the wear and tear of components. The system proactively issues alerts when detecting abnormal data. Asia Giant promptly provides “customized” maintenance and repair services, significantly reducing the manpower and time costs associated with handling unexpected events and enhancing production efficiency for their customers.

The “Smart Vertical Agitation Machinery” later became a catalyst for AI applications in the chemical industry. Not only did Asia Giant’s long-term clients inquire about the possibility of retrofitting the intelligent monitoring system to their existing equipment, but also many pharmaceutical companies expressed a keen interest. They hoped to integrate the intelligent monitoring system into their equipment, allowing them to remotely monitor parameters like temperature, pressure, and volatile organic compound (VOC) emissions, checking for any abnormalities in real-time. According to statistics, in 2023, Asia Giant witnessed a substantial 40% growth in equipment orders with integrated AI intelligent monitoring systems compared to the previous year.

To facilitate the transformation of more manufacturing equipment into smart devices and expedite the integration of AI in both hardware and software, Asia Giant has established an Application Services Division this year. According to Hsu, the company’s future vision includes the recruitment of additional AI experts. This move aims to position Asia Giant as a prominent integration hub for AI applications within Taiwan’s chemical industry. They aspire to function as guardians of AI applications and solutions for their clients, facilitating the seamless entry of an increasing number of traditional chemical industry players into the realm of smart manufacturing.

As the artificial intelligence (AI) wave rages on, other than overseas technology leaders pumping in investments, more and more enterprises in Taiwan have followed the trend, bringing changes and new opportunities to Taiwan’s multitude of industries and playing a pivotal role in unleashing the next wave of industrial upgrading. ACON, which has been established for over 36 years and specializes in the design, manufacturing, and sales of IT, digital home appliances and handheld electronic components, has also proactively introduced reformative AI initiatives in recent years and established the strategy of the first year of digital transformation last year. Grand Kuo, Senior Special Assistant to ACON President’s Staff Offic, pointed out that everyone in the Group must attend the digital transformation channel course every Thursday morning from 11am to 12pm to enable the enterprise to keep up with industry trends.

In the past, electronic component businesses such as connectors depended on Taiwan’s strongest customer base in the telecommunications industry. In recent years, the rise of non-3C fields such as electric vehicles, green energy, smart healthcare, AIOT industry, 5G and high-speed telecommunications also saw the demand for new applications of electronic components in these fields, creating high value-added business opportunities for enterprises, many of which are the main business lines of ACON.

Deep entrenchment in digitalization, where it all started from production processes in the early years

Grand Kuo said that ACON began to introduce application program interfaces (APIs) as early as 12 years ago to improve production and optimize processes. From 2016 to 2018, industrial upgrading was carried out through automated testing and manufacturing.

In the past two years, under the leadership of General Manager Frank Chen, a Digital Transformation Committee was established so that automation can be refined through the accumulation of data, further deepening digitalization efforts and improving the efficiency and quality of the workflow holistically to the extent of establishing new business models. The Company also introduced AI applications at this stage.

In view of the success of digital transformation, Frank Chen believes that there are four key attributing factors, the first being embedding it in the organizational culture, turning digital transformation into an ideology, a habit, and integrating it into work fully. The second is whether the supervisor attaches importance to it and the level of commitment, taking on a top-down approach to, in turn, drive the entire organization. The third is to leverage internal and external resources, identify tools that can be used directly to facilitate a faster and more effective pace of promotion. The final factor being implementing digital transformation using PDCA management methodology. Each department needs to define relevant tasks, identify specific low hanging fruits and establish a positive environment through reward system and mutual learning.

Internalizing digital transformation into an innate culture

James Chan, Innovation Consultant at ACON, commented that ACON executives have always been very supportive of digital transformation, believing that new tools can drive new thinking. In the process of transformation, unlike the top-down policy of typical enterprises, ACON adopted the sandwich approach where junior talent must also spearhead digital projects, so that both high and low-ranked employees can have a common digital language. A Digital Star Transformation Competition is also held every quarter.

Dr. Chan shared one of the most memorable projects in the process – Virtual Measurement. It was precisely because of virtual measurement that an opportunity arose to achieve Digital Twin, bringing digital plants and virtual production lines into fruition to enable rapid replication of plant technologies to other plants. While precision manufacturing is reliable, such AI tool applications can greatly widen the gap with competitors.

Simple steps, five management areas of enterprise for comprehensive digitization

In the past, when driving digitization, ACON encountered challenges such as poor application of tools and difficulties in mastering statistics and software, which became the main obstacle to driving digital transformation. In the second half of 2022, ACON started collaborating with Profet AI to conduct two Profet AI AutoML workshops, starting nurturing management associates and key business talent, with the goal of equipping 1,000 digital transformation talent within 3 years.

The results of this digital transformation have been commendable. In less than a year, the company has implemented 677 digital projects, of which 470 have been implemented through the Profet AI No-code AutoML platform, accounting for more than 70%. In addition, with the assistance of Profet AI’s consultants, ACON has trained more than 240 agile digital team members, including production, marketing, human resources, R&D, and finance of the five management areas of enterprise management to achieve holistic digitalization among employees.

Jonathan Yu, General Manager of Sales at Profet AI, commented that Profet AI AutoML platform provides machine learning algorithms commonly used in the manufacturing industry, allowing users to operate online quickly. Personnel without experience or IT background can quickly get the hang of things, communicate in the same language, and complete the operation in just five steps. For ACON, on top of optimizing production, the new industrial model of introducing AI also improved management quality.

Dr. Chan remarked that the introduction of new tools in the past took time and experience to slowly refine. While high-tech automation has accelerated due to the lack of accumulation of scientific data in automation, the use of mathematical models in the past had not been easy and largely, at best, were capable of categorization. However, after introducing Profet AI’s AutoML system, the company was able to quickly attain the original goal, achieving improvements on competitiveness.

General Manager Frank Chen stressed that in order for the company to be competitive and sustainable, it needs to carry out digital transformation on a more extensive and deeper scale. In the industry, over and above numerous process changes, business models also undergo rapid transformation. Therefore, enterprises must leverage various tools comprehensively to achieve digital transformation and boost their competitiveness. ACON’s use of AI is not to go with the flow, but to aspire to do better than others.