To be successful in digital transformation, companies need a clear roadmap that aligns with business objectives and pegged to measurable outcomes, and maximise value from current technology and understand the level of maturity in their organisations.
By Dr. Filipe Soares-Pinto, SVP of Sales and Operations, Asia Pacific and Ron Beck, Energy Industry Marketing Director, AspenTech.
According to KPMG, the petrochemical industry in Asia Pacific has been doing well due to favourable economic and demographic trends. In this 2014 report, about two-thirds of the global petrochemical demand will originate from Asia Pacific over the next decade.
Facing slower but targeted growth, China needs to balance the need for innovation, self-sufficiency and environmental sustainability. In North Asia, the petrochemical industry needs to be innovative and adaptable in overcoming challenges, such as global pricing competition, high priced input and low growth. This necessitates the need for flexibility and efficiency, driving companies to be more efficient via digital transformation.
A potentially huge growth market, ASEAN needs to better support local intermediaries and producers by driving down feedstock costs or regional downstream consumers will start looking towards China, the US and Middle East for lower priced raw materials.
Leaders Execute Differently
The overall market outlook for Asia Pacific remains bullish, as economic and demographic growth drive continued demand for petrochemical products. Boston Consulting Group (BCG) highlights a wide gap in total shareholder value between the best performing chemical and refining companies versus the laggards. AspenTech observes that leading companies outperform the market by focusing on operational excellence via strategic investments in digital transformation. Companies need to make significant organisational change, invest and anchor efforts against measurable goals.
Other areas to focus on include improving asset reliability, optimising operations and supply chain, reducing CAPEX while accelerating innovation, as well as continuously improving safety and sustainability. Key digital transformation technologies supporting these goals include artificial intelligence and machine learning, automation of knowledge work, Industrial Internet of Things (IIOT) and system-level thinking.
What Drives Digital Transformation
The process industry in Asia Pacific faces challenges, such as demographic shift towards younger and less experienced knowledge workers, drive towards sustainable production and global economic volatility, as well as the need for flexibility and increased profitability. At the regional level, a burgeoning middle-class population changes the energy use portfolio and shift in consumer demand, from cars to chemical products.
Asset-intensive industries need to improve flexibility and agility in re-purposing extremely high investment capital assets. Companies also need to eliminate production losses caused by unplanned downtime. The resulting increase in asset utilisation results in a single, greatest financial improvement in production operations. ARC highlights that traditional wear and age-based maintenance approaches cannot detect more than 80 percent of the current unplanned downtime. According to the National Association of Manufacturers, the cost of unplanned downtime adds up to US$1.4 trillion. This massive opportunity cost makes it necessary for the industry to detect all kinds of degradation early and enable the necessary decision-making to change the outcome.
At the recent Asian Refining Technology Conference (ARTC), Ashwin Balasubramanian, Associate Partner, McKinsey & Company, challenged the industry to re-examine the entire way of doing business, as digital technology evolves rapidly. Mohd Shahrizal Yang Razalli, Head of the Office of the CEO & EVP Downstream, PETRONAS, presented on digital transformation as the breakthrough opportunity for Asian process manufacturers to democratise business decision-making and become industry leaders.
A major driver behind this industry change includes turnkey solutions, which turn fundamental analytics and data science methods into scalable solutions to address business challenges. For example, advanced machine learning software, packaged as prescriptive maintenance solutions, has demonstrated incredible successes in the early identification of equipment failure and learned behavioural patterns from streams of digital data, produced by sensors on the relevant equipment.
Autonomous in nature, this advanced technology constantly learns and adapts to new signal patterns when operating conditions change. Failure signatures learned on one machine inoculates that specific machine, so the same condition does not recur. Learned signatures readily transfer to similar machines, preventing the same degradation conditions from affecting them. The net result is a disruptive technology that can predict failures 50-70 days in advance to prescribe operating actions and avoid the failures.
Beyond machine learning, other emerging technologies include mobility as a key driver of digital transformation. Mobile devices and applications enable plant workers to make decisions on the go. With social networks, teams can collaborate virtually at any time to solve problems via social networks. Powerful cloud containers can streamline the deployment experience, reduce cost of ownership and increase application scope.
The Industrial Internet of Things (IIOT) connects the plant with model-based sensors on all equipment. Advanced algorithms used in search and pattern recognition automatically detect data-based patterns to predict outcomes and guide optimal responses. Analytics, models and big data enable the exploration of data potential inside the plant fence and across the company. High performance computing provides the necessary computational horsepower to address large issues around asset optimization and advanced metadata sharing across industry for greater efficiency.
A visible outcome in leveraging emerging technologies in a plant can be seen in scalable model applications interfaces that access important plant systems, such as the refinery plan, key personas in simple views. For example, a crude oil trader in viewing the refinery plan can now make fast decisions in split seconds.
Accelerate Operational Excellence
A major driver of digital transformation, asset optimization is a continuous journey that addresses the entire lifecycle to achieve operational excellence. First, customers can maximise uptime through actionable insights. For example, the owner of the most complex refinery in the Mediterranean, SARAS, has increased refining uptime by one- 10 days in a year with Aspen Mtell software. A leading provider of innovative solutions in the fields of polyolefins, base chemicals and fertilisers, Borealis, has achieved warning of failures 27-28 days in advance and improved profit margins with Aspen Mtell software. A global leader in diversified chemicals, SABIC, has minimised CAPEX, while ensuring 99.9 percent uptime with enterprise risk modelling systems by using Aspen Fidelis Reliability software.
Second, with asset optimisation, customers can push the boundaries of what is possible. For example, Kuwait Oil Company has saved US$22 million lifecycle profit per unit via economics knowledge automation. One of the world’s largest manufacturers of chemicals and oil products, INEOS, has saved US$10M revenue per CDU/VDU per year with the deployment of Aspen HYSYS and integrated Exchanger Design and Rating (EDR) models online.
Third, customers can run to the limits of performance. For example, refining and marketing company Irving, added US$10 million a year in incremental margin with the deployment of Aspen GDOT software across multiple APC implementations. Japanese chemical manufacturer, Mitsui Chemicals, achieved a reduction in one percent operating cost with the deployment of Aspen Utility Planner and Aspen DMC software. ESSAR also saved US$10 million a year via feedstock optimisation with Aspen PIMS-AO software.
Smart Companies Transform Digitally
To be successful in digital transformation, companies need a clear roadmap that aligns with business objectives and pegged to measurable outcomes. Companies need to maximise value from current technology and understand the level of maturity in their organisations. It is also necessary to define business drivers, challenges and key success metrics. Workforce skills development should be encouraged. Finally, smart companies with the ability to successfully transform digitally and pursue operational excellence via asset optimisation will be market leaders.