REJ603 In February, KPMG China released a report entitled “Racing ahead: Industry Impact Outlook for the 14th Five-Year Plan”. KPMG expects that in the field of industrial manufacturing, China will continue to promote the major goal of “manufacturing power”. Key trends include digital transformation and smart manufacturing; Accelerate the development of core technologies to enhance autonomy, safety and reliability; Strengthen the advantages of integrated supply chain networks and industrial clusters.

REJ603 In addition to industrial manufacturing, the energy sector is also a focus. The same KPMG report pointed out that the 14th Five-Year Plan will focus on building a green and low-carbon economy and developing renewable energy. The main aspects of this new energy plan include: strengthening the development of strategic emerging industries; Accelerate low-carbon development; Promote the safe and efficient use of clean and low-carbon energy; Support places where conditions permit to take the lead in peaking carbon emissions; Formulate an action plan for peaking carbon emissions before 2030.

These plans for industrial manufacturing and energy in China are in line with Aspen’s strategy to drive digital transformation and sustainable development through artificial intelligence.

REJ603 Combine domain expertise with industrial AI to improve overall efficiency

Willie K Chan, Chief Technology Officer at Aspen, highlights the crux of the matter: “Domain expertise is what differentiates industrial AI from more general AI. In the future, industrial AI can guide capital-intensive industries to innovate and improve efficiency.”

REJ603 With the support of industrial AI, the average engineer can take advantage of machine learning without becoming an advanced data expert or a professional engineer. In fact, AI algorithms account for only 5% of software source code, with the remaining 95% coming from domain expertise.

Digital transformation is integral to realizing the vision of a self-optimizing factory, and new technologies that combine AI-based data insights, industry-specific first law models, and domain expertise are key to enabling this vision. The original intention of this technology is clearly to deliver comprehensive business outcomes to meet the needs of capital-intensive industries. Businesses need to ensure that they choose the right AI solution, combined with domain expertise, to deliver measurable value and achieve a faster return on investment (ROI).

Delivering value through digitalization

As we all know, the pandemic has accelerated the need for digitalization in capital-intensive industries. However, it is best for businesses to carefully measure the return on investment to ensure they are getting value from the technology they deploy.

REJ603 Oil and gas giant Bharat Petroleum (BPCL), for example, uses digital twins to track emissions, and the resulting data helps identify trends, correct errors, optimize production, and reduce carbon emissions. The digital twin enables BPCL to save approximately $600,000 per year, achieving sustainability while improving margins.

China Bluestar (Group) is a Chinese chemical enterprise engaged in the development of new materials. The company selected Aspen Mtell and Aspen ProMV Asset Performance management (APM) software to accelerate the digital transformation of more than a dozen production sites around the world. The deployment of these technologies helps Bluestar achieve operational excellence and leverage artificial intelligence and machine learning models. The collaboration has enabled Blueststar to significantly improve production across its specialty chemicals business by conducting predictive and prescriptive analysis of all its key equipment assets to predict process deviations early, avoid product quality issues and reduce unplanned downtime. By accelerating its digital transformation, Bluestar is able to capitalize on global market opportunities in a volatile, uncertain, complex and ambiguous (VUCA) environment.

REJ603 Aspen Mtell mines historical and real-time operational and maintenance data to accurately identify failure indicators before assets degrade and fail, predict failures that do not occur, and prescribe detailed actions to mitigate or resolve problems. Aspen ProMV multivariate analysis creates a model that makes data more visible and easier to interpret, so factories can quickly identify what drives hundreds or thousands of variables in a process. Aspen Mtell and Aspen ProMV work together to help companies achieve their strategic digitalization goals through industrial AI.

Hybrid models will become the new normal

REJ603 Faced with the new normal, enterprises increasingly need to adopt hybrid models that combine mechanistic models and AI-driven models to optimize complex operations more accurately and autonomously, especially energy transition technology solutions. For capital projects, transparency in estimating and project progress can unlock value. To effectively manage project risk, data visualization, benchmarking, and sharing of data are essential to increase speed and certainty. Ultimately, asset design is more agile, smarter, and collaborative, making execution smoother and more predictable.

For example, China Global Engineering Corporation (HQC), a wholly-owned subsidiary of China Petroleum Engineering Corporation, has installed Aspen HYSYS Dynamics software to achieve maximum safety, productivity and profit during the design phase of critical systems. The easy deployment of dynamic process simulation software facilitates the digital transformation of HQC, increasing asset value and improving performance early in the asset lifecycle. By digitally transforming the design phase of the asset lifecycle with aspenONE Engineering software, HQC will strengthen its market leadership position and be more responsive to the needs of its owner-operator customers, aiming to gain a head start in the global engineering and construction industry.

REJ603 A sustainable way forward

By embedding AI capabilities into existing operational technologies (OT) and information technology (IT), businesses will be able to strike a balance between profitability and sustainability. Such companies will be able to more effectively address the twin challenges of the new industry normal: providing adequate resources for a growing population and improving people’s living standards while advancing the Sustainable Development Goals.

In a volatile market, supply chain management is critical, as sustainability and resilience are two sides of the same coin. FP Corporation, Japan’s largest food container manufacturer and logistics provider, is a model in this regard. Japanese company FP promotes environmental improvement by recycling used food containers and PET bottles. With more than 1 billion containers sold each month, selling recycled products needs to become an economically sustainable activity. To this end, the company chose aspenONE Supply Chain Management (SCM) to provide stable and agile food distribution in an efficient, sustainable and environmentally friendly manner.

Industrial AI can help companies navigate increasingly complex supply chain choices and decisions. With cost and carbon footprint reduction high on the agenda and the global carbon reduction landscape changing, the energy transition must be a focus for all of Asia.