Enabling Value Chain Optimization with DX
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At the “Y-NOW 2020: DX Solutions for Tomorrow” event, which took place November 10-12, speakers presented on all aspects of digital transformation. A series of panel discussions provided considerable guidance to participants who are contemplating the digital transformation journey or seeking best practices for their next steps.
Contributors:
Simon Rogers, VP Digital Solutions for Yokogawa
David Parsons, Director, Refinery Models for Valero
Nick Kenaston, Technical Team Leader – Oils Planning, at Chevron
Mike Aylott, Chief Technology Officer for KBC
Value Chain Optimization - Planning for Digital Transformation and Keeping it on Track to Deliver Optimal Outcomes
New business plans require new business processes and work processes to address new market opportunities. In terms of C-suite objectives, the COVID-19 pandemic led to an upheaval in the business climate. However, instead of putting digital transformation projects on hold, it has accelerated that process in most companies.
In a discussion on digital transformation and how it enables optimization across the entire value chain, Simon Rogers, VP Digital Solutions for Yokogawa stated that, in the energy and chemical industries, the biggest challenge is the energy transition.
David Parsons, Director, Refinery Models for Valero observed that reduced demand is leading to overcapacity. “The oil and gas industry has traditionally been in a supply push rather than demand pull business model. But now, as demand for fuels decreases, the industry is shifting to chemicals. The supply push world called for us to find out how to squeeze another barrel out of the process. There was always a market for it. Now, it’s how to fulfill demand in the cheapest possible way.”
Nick Kenaston, Technical Team Leader – Oils Planning, at Chevron, added that there is also a shift to natural gas. “More natural gas use demands natural gas optimization. In addition, new regulations on ways to produce fuels require us to optimize CO2, sulfur, and benzene. Those require new modeling.”
Mike Aylott, Chief Technology Officer for KBC, feels that new technology such as analytics enable digital twins to be up to the task. “The biggest challenge, which had been figuring out how to process massive volumes of data, is turning into the biggest opportunity. Digital transformation, AI, and operations in the Cloud provide insights from analytics that can operate on a massive scale. We’re just starting to realize the opportunities of AI and the computing power offered by the Cloud. For example, ultimately, there will be no need for corporate data centers.”
Nick’s team is embracing data science to improve refinery operations. “Data quality is still a big challenge—but now there are novel ways to fill in data gaps. The convergence of first principles models and MI can help with data gaps. This is a revolutionary approach to solving problems.”
Simon has been working on use of machine learning (ML) to analyze historical data for variances between plan and actual results. “The combination of first principles models and ML is more powerful than either can be alone.”
Nick added that “the speed at which we do things such as switching products or handling varying feedstocks is accelerating. The technology enables more scenario analysis and more sensitivity analysis.”
He has been using linear programming (LP) for optimization and sees how new, digital transformation technologies will help it evolve. “LP must be fast, accurate and robust. Today, we can run scenarios much more quickly. This provides greater accuracy, which increases quality of the outcome. With ML and digital twin technologies, we can continuously run to validate key yields. We can run more cases, in fact, hundreds of thousands of them, with high quality data.
Mike added that convergence of simulation and LP represents a major step. “First principles models such as those used in digital twins can calibrate ML to feed into the LP. This requires a continuous data validation process but builds considerably more agility into the system.”
Realizing Outcomes
Ultimately, it enables the vision of a facility that comprises an asset, plant or refinery-wide optimizer, which is continuously responding to market signals, disturbances such as feed changes and globally optimizing on a minute-by-minute basis. This involves a number of different components—planning, scheduling, APC and first principles simulation.
However, to prevent the siloed situation that often exists today, these must and now can be considered together. The solution can calculate the optimal values for plant independent variables with a high level of accuracy using data through online connections to control systems and plant information management systems. It utilizes rigorous non-linear models to calculate additional inferred properties. Everything can be done quickly within the value chain boundaries and direction utilizing the most accurate data and equations.
The end goal is for assets to operate with no safety incidents, no unplanned outages, rigorous adherence to operating plans, nimble response to market changes and asset disturbances, a motivated and informed workforce, and a culture of profitability. The vision in digital transformation is to enable it with autonomous operations.
Figure - The following practical steps are recommended, amongst others, to embark on a dx journey. Learn more about it in the DX eBook.
For many, digital transformation will be a multi-year journey. Ultimately, the journey is determined by current maturity, desired end goals and the level of urgency to achieve them.
To learn more about DX and value chain optimization, download our eBook about digital transformation in the process industry.
