On June 5th, SUPCON Global Product Launch Conference 2024, themed "Pioneering Progress, Shaping Tomorrow," was successfully held in Singapore. The Panel Discussion, themed "Embracing AI to Build a Sustainable Future," gathered esteemed guests from various fields to explore development trajectories in the AI era, drawing insights from their collective experience and expertise. The panelists comprised Bob Gill (General Manager, ARC Advisory Group, Southeast Asia), Christian H. Siboro (Independent Commissioner, PGN), Brad Lee (President, EMQ), Cui Shan (Chairman & President, SUPCON), and Kazuhito Yokoi (Solutions Architect, Hitachi Academy). Bob Gill moderated the discussion.

Bob Gill: Currently, new technologies such as the Industrial Internet, Big Data, Digital Twins, and AI are continuously integrated into the process industry. Please share your perspectives on the opportunities and challenges that new technologies, particularly generative AI, bring to the process industry.

Brad Lee: We have seen a lot of buzzwords today for the last two years about generative AI, and I strongly believe that generative AI will definitely go on the path in the future. But to me, there are still many uncertainties in terms of regulatory policies, whether the datasets are ready to run the large language model training, and whether people are fully trained to have the necessary AI skills. Therefore, there is still a lot to explore and choose when adopting generative AI technology correctly in enterprises.

Christian H.Siboro: The advancement of technology will always open up many new opportunities for enterprises. For instance, at PGN, we are currently facing challenges such as long product development cycles, unpredictable emergencies, and high costs due to long processes. AI technology undoubtedly presents an opportunity to address the current dilemmas faced by PGN. Meanwhile, we hope to influence internal employees to change traditional habits and mindsets for adopting these new technologies. And truly facilitate the development of the company from the inside out.

Cui Shan: AI particularly is not really a new thing to the process industry, as many technologies have been using different modeling skills to improve industry performance. However, when the ChatGPT comes, its immense computational power has reinforced the value of data. The full application of AI technology will effectively address many problems faced by traditional industries. The profitability like efficiency and revenue growth will be driven by AI definitely. SUPCON will put all our focus on developing new generative technologies and helping our customers.

Kazuhito Yokoi: In Hitachi, we have already delved into several AI projects. By using generative AI, our factory engineers can develop and generate custom code and obtain final computational results from massive data. Before generative AI era, factory engineers had to request IT engineers to develop the entire system specifically. However, now, factory engineers can create and expand their roles in IT field. Such a transformation can shorten the process and reduce the time cost of innovation.

Bob Gill: The UCS system released by SUPCON is a new type of control system that subverts the traditional physical form of DCS and is defined by software. What new value creation do you think such a completely innovative product can bring to enterprises?

Christian H.Siboro: UCS will definitely solve many of our problems operationally. Currently, in PGN, we still have a lot of physical equipment along our gas pipeline for mentoring and storage. In some cases, we still need manual checking to see whether there is a leak or corrosion, which is definitely not real-time. With UCS, we can monitor factory equipment proactively and in real time, thereby avoiding accidents and reducing costs. Most importantly, anticipated action could be taken with UCS, based on its predictive modeling and the control parameter in the future.

Kazuhito Yokoi: Hitachi has a lot of edge devices, and for us, it is very difficult to manage all of these devices. It is impressive that UCS can accumulate and analyze all the data in single cabinet machine. I believe UCS is a quite useful solution for the majority and capable of enhancing company overall performance.

Cui Shan: It's quite clear that UCS can bring significant cost-reduction value to enterprises. In particular, 80% cost of cables is going to be removed. Furthermore, UCS breaks the wall among traditional OT, IT, and AT. Now with a simple click, all these applications will run automatically in the most optimized operations. The value is not just about optimizing labor costs, it represents a breakthrough innovation for all enterprises. UCS has already been commercialized, and we look forward to supporting more enterprises in digital transformation progress.

Bob Gill: Using the TPT model recently released by SUPCON as an example, what the typical value and application prospects do you think that generative AI technology could bring to your companies and even the industry as a whole?

Brad Lee: EMQ has always spending on how to build a software piece that could connect the physical world and artificial intelligence. Our collaboration with SUPCON on UCS is helping them to transit log data from machine to machine. I’m very optimistic about generative AI, but now it is still on a productivity level. Generative AI as a product itself still needs a lot to explore.

Cui Shan: TPT is undoubtedly pioneering a new path for industrial operations. Firstly, TPT has revolutionized the traditional mode to a new paradigm of “TPT + 1 software” in the plant, helping enterprises save a significant amount of software costs. Secondly, TPT gathers massive data for pre-training, demonstrating strong adaptation capabilities across different units and conditions. It offers higher accuracy and inclusiveness for production optimization. We believe TPT can ultimately solve the unsolved challenges with our partners in the future.

Christian H.Siboro: As a petrochemical company, PGN indeed requires predictive maintenance to secure the stable and safe operation of facilities. Currently, PGN has the time-series data, but these data are merely regarded as a log book and have not been fully utilized. With TPT, our time-series data can be further analyzed, enabling more accurate predictions for all equipment.

Bob Gill: To accelerate the adoption of AI in the future, we must strengthen the ecosystem's foundation across both industry and technology sectors. We invite our esteemed guests to share their insights and experiences on building a thriving AI ecosystem.

Kazuhito Yokoi: The AI ecosystem is similar to the open-source ecosystem to some extent. In open-source ecosystem, we define software architectures and then create code to implement functions. Through daily activities and communication, ecosystem partners cooperate and share new knowledge and features. I believe these experiences can be reused in building AI ecosystem.

Brad Lee: With the coming of the AI era, the majority of software companies seek to reshape and restructure. In this context, EMQ has forged a partnership with SUPCON, which is not supposed to do in the past 10 years. In the AI era, the business operation models, ecosystem running models and the type of partners all require continuous change and development.

Cui Shan: In the AI era, the ecosystem is critical to all of us, and all because of the Eco-cooperation that makes SUPCON run successfully today. Under the AI trend, we are not that powerful to do everything by ourselves. From computational capabilities, data centers, algorithms, modeling, talents, to even government policies, every aspect requires collaborative efforts from partners within the ecosystem to create value for the process industry.

Bob Gill: It is no longer a choice but a necessity to embrace transformative technology such as AI. How do you think that our enterprises and industries can harness the power of AI to create a brighter future?

Brad Lee: Personally, I think artificial intelligence is disruptive and massive, and will fundamentally change the way to run a business. All enterprises should be generally ready for generative AI, involving data government, storage, and management while having real profitable use cases in genuine scenarios.

Christian H.Siboro: There is a symmetric condition between the technology advancement and organization readiness. The internal preparation of data readiness, organization readiness, talent reserve, and mindset should be in sync with technological advancements. There should be a common perception of the use of AI in our organization from top managers to basic operational people.

Cui Shan: In the AI era, talent acquisition is the primary challenge for enterprises. Fresh blood is needed to support innovative development. Secondly is the perception. Lots of changes actually should be happening at the same time with the new product development ongoing. These changes include individual mindsets, organizational structures, and business models. Resource allocation, talent reserve, ecosystem construction, and application scenarios are all necessary preparations for maximizing the value of AI technology.

Generative AI has seamlessly integrated into the industry, evolving from theory to practicality. The Panel Discussion explored the industrial value of AI-driven product innovations and established a platform for future ecosystem construction. SUPCON remains committed to spearheading global industrial AI advancements. Together with ecosystem partners, SUPCON will keep working to foster sustainable industrial development in the AI era.