Profitability and sustainability may have once been at odds for process manufacturers, but now, the two are intertwined like never before.
Have you ever thought about the folks who control the Perseverance Mars rover? Driving the rover is one of the most complex and time-consuming activities of the entire exploration mission. The contrast between what it takes these NASA engineers to drive to work each morning — done almost without thinking — and the diligence and collective attention required to navigate the rover with a top speed of under 0.5 mph is remarkable.
So, what does driving the Mars rover have to do with the sustainability and profitability of your business?
Many manufacturing organizations manage their operations in a similar manner to NASA engineers controlling Perseverance. In both circumstances, real-time information alone is insufficient for teams to base their decisions on because it is unreliable and/or untimely. Instead, they work through a process of collecting relevant historical and contextual data, validating it, defining immediate objectives, crafting longer-term plans, and staging these plans for execution without direct oversight or the ability to intervene in the moment if issues arise.
By deploying modern, advanced analytics software, organizations in the process industries can make the shift from interplanetary to in-the-moment business operations.
Given the inherent time-delay and bandwidth challenge associated with interplanetary communications, there is no feasible alternative to Perseverance’s control scheme. But imagine what it would mean to your business if you could drive sustainability the way you drive your car without thinking, rather than treating it like it operates on another planet.
By deploying modern, advanced analytics software, organizations in the process industries can realize the potential of their investments in digitalization, making the shift from interplanetary to in-the-moment business operations. Particularly in the realm of sustainability initiatives, this transition provides a critical step towards more circular production systems, and it also helps innovative manufacturers drive sustainable practices, differentiating themselves from the competition.
Key sustainability initiatives
Modern industrial analytics can help global manufacturers achieve key sustainability milestones, including net-zero pledges, regulatory reporting goals, and energy, water, and materials reduction. By leveraging self-service, advanced analytics applications in process manufacturing, companies can overcome many challenges and barriers to achieving these sorts of measurable gains.
The sustainability-driven activities that support these top initiatives fall into one of three broad categories:
- Measurement and validation: Relevant key performance indicators (KPIs) have primarily been developed around greenhouse gas (GHG) and carbon emissions, but organizations are increasingly adding new ones, such as water usage and NOx emissions, driven by the need to meet regulatory and fiscal requirements.
- Improving existing operations: Increasing operational efficiency and minimizing environmental impact.
- Scope 3 and circular enablement: Fundamental changes to supply chain, sourcing, and manufacturing processes focusing on Scope 3 impact and enabling circularity concepts.
1 Measurement and validation
The notion “you can’t improve what you don’t measure” is highly applicable to sustainability initiatives. Measurement was historically retrospective and infrequent, hampered because calculations, visualization, and validations were performed manually in spreadsheets, often by offsite production accounting groups or corporate sustainability teams with access to few local resources.
By leveraging advanced analytics software, teams gain visibility into current emissions levels at each production facility, helping process manufacturers reverse the old dynamic. This empowers local operational teams to identify excursions and respond in a timely manner to make tangible impacts when issues occur.
For example, advanced analytics applications enable subject matter experts (SMEs) to identify relationships among environmental KPIs and process parameters. When these relationships are understood, entire processes can be continuously monitored to identify and mitigate environmental excursions. This continuous monitoring ensures rapid reaction to events, while facilitating root cause analysis by SMEs.
An ever-widening variety of techniques to validate these runtime measurements and adjust for known disturbances, such as fuel gas composition changes and combustion efficiencies, are under development. This provides the confidence audit trail for the generation of enterprise-level reports through the aggregation of multiple runtime measurements rather than top-down allocations as is common practice today.
Responsible operators want to improve, but they lack the means to track progress without a method of measurement.
More challenging are those emissions that, by their nature, cannot be measured directly — for example, fugitive emissions of storage and transmission systems, which form a significant proportion of total emissions in some sectors. Responsible operators want to improve, but they lack the means to track progress without a method of measurement. With advanced analytics, organizations can overcome this obstacle.
Improving leak detection and mitigation
Oil and gas operators have difficulty pinpointing methane leaks. While methane data is available from a variety of satellite providers, the data is sparse, with measurements typically available just once each day. Additionally, integrating this satellite data with other information of interest — such as weather or process data — poses a challenge. As a result, it is difficult to quantify past events, and nearly impossible to identify events in real-time or detect developing issues.
Using advanced analytics software, SMEs can review satellite, weather, and process data in a single location. The satellite data can pinpoint when an event occurs, and the weather data can help characterize a dispersion model for the event. Meanwhile, an analysis of the process data can pinpoint the source of the leak and quantify the event duration and quantity emitted.
Overlaying data from all sources yields greater insight into emissions events, specifically the duration of an event, amount emitted, and dispersion of the plume. These insights can be leveraged to characterize process conditions leading up to emissions events so users can proactively spot issues as they arise, or even identify early indicators and avert an event altogether.
2 Improve efficiency and impact of existing operations
All the effort expended identifying opportunities for environmental improvement are meaningless unless something changes as a result. Most organizations focus first on existing operations, striving to run optimally as much of the time as possible. This raises two questions: 1) how well can the existing facilities run, and 2) how can this be quantified?
The latter question is the more difficult to answer, as few, if any, sustainability-related KPIs are calculated and monitored with sufficient granularity and timeliness for operations teams to take informed action. Even after runtime visibility issues have been addressed, labelling what “good” looks like can be quite challenging, particularly in operations with variable feedstocks, product slates, and energy sources.
The ability to certify sustainability credentials of individual facilities, product lines, and product deliveries creates opportunities for differentiation and competitive advantage.
Intra- and inter-company benchmarking is invaluable for this identification, and in some cases, performance targets must be derived during runtime from plant models, simulators, and optimizers. Runtime visibility, implemented on a common, enterprise-wide platform, is the only viable way of implementing this.
One of the greatest intangible benefits reported by process manufacturing organizations that use advanced analytics software is the power of a single platform to enable company-wide learning and best practice dissemination. Equipped with live data connectivity, these types of applications provide simplified data-cleansing tools and contextualization, empowering SMEs to derive meaningful and reliable insights across all available data quickly.
Justifying an idle boiler
Wasted energy is one of the largest contributors to carbon emissions, and utilities providers frequently comprise the largest source of energy waste. Manufacturers need ways to identify the time periods of wasteful operation — which come in the forms of vented steam, excessive electricity consumption, and others — and quantify the waste as a financial loss or CO2 emissions equivalent. These quantities provide a common benchmark for comparing alternative operating strategies.
A major U.S. refiner leveraged advanced analytics to justify the idling of a single boiler in a dual boiler operation during the warm months of the year. A team of SMEs configured the software to identify time periods when the dual boiler system was operating at minimum firing rates while venting steam. Then, these time periods were studied to aggregate potential annualized steam savings.
Next, the team analyzed historical data to understand the probability of a boiler trip, which could have a significant financial impact in a single boiler operation, and the potential steam cost and energy savings were weighed against the risk — probability of failure times financial consequence — of running a single boiler.
This analysis provided the data required to make the decision of idling one boiler during prolonged periods of warm ambient weather, saving the refiner an average of $500,000 per year in vented steam costs. This operational change also reduced the operation’s carbon footprint by decreasing energy input to the boiler system.
3 Scope 3 and circular enablement
Analysis can point out significant opportunities for operational optimization, but there will always be inherent limitations imposed by the production systems used today. Every individual plays a role in a larger value chain, and multiple value chains make-up highly integrated and interdependent economic systems. By working together, multiple organizations can keep progress going in the right direction.
This concerted action is underpinned by two key concepts: Scope 3 awareness and reporting, and production system circularization. The practical viability for each of these topics is dependent on the same concept of runtime visibility. Without runtime visibility, process manufacturers are limited to using typical or standard emissions data from suppliers — especially feedstock and energy — in the effort to understand and define Scope 3 performance.
These near real-time carbon intensity estimates provided the organization the opportunity to make data-driven decisions to target carbon reduction on an ongoing basis.
As runtime visibility is improved up and down the value chain, it becomes increasingly straightforward to communicate actual performance metrics in real-time, or on a material-by-material and batch-by-batch basis. This is already commonplace for other quality and compliance-based metrics in many sectors, including polymers, pharmaceuticals, and liquid fuels.
Reducing carbon emissions
A global chemical manufacturer recently pledged to cut its carbon intensity in half by 2030. The first step it took toward reduction was understanding the current state of its operations. Previously, such an analysis was only conducted once per year because it was so cumbersome, but this carbon intensity calculation is critical to understanding the overall carbon footprint of the manufacturer’s process.
Site engineers leveraged an advanced analytics software application to provide near real-time awareness of the carbon intensity of site utility streams. This application converted process sensor data into carbon mass equivalents so SMEs could easily compare the current carbon intensity with a target for a given production quantity. Breaking the carbon footprint into individual utility streams empowered the operations teams to understand the largest contributors, along with the levers to combat them.
These near real-time carbon intensity estimates provided the organization the opportunity to make data-driven decisions to target carbon reduction on an ongoing basis, making measurable progress towards their 2030 reduction goal. Following this approach, Scope 3 measurement simply becomes the addition of individual run-time metrics up and down the value chain. And as more members of the value chain actively participate, this approach will continue to become more accurate, informative, and meaningful.
Economic returns and competitive differentiation
There is no doubt that sustainability initiatives will continue to drive incremental and transformational change. The adoption of runtime measurement and validation facilitates movement toward increasingly proactive production systems, which help establish dynamic mitigation and preemptive detection of emission events.
The actions of individual companies benefit every member of the value chain. Furthermore, the ability to certify sustainability credentials of individual facilities, product lines, and product deliveries creates opportunities for differentiation and competitive advantage — especially in the areas traditionally considered commodity markets.
In a time not long ago, operating a global manufacturing business often felt a bit like trying to maneuver an intricate and complex vehicle by remote control from a planet away, but that no longer must be the narrative. With digital technologies and modern industrial analytics tools, runtime visibility is plausible and common, empowering organizations to drive in runtime, instead of faintly issuing commands with the hope of execution as intended.
Getting organizations behind the wheel is the only way we will collectively impact the sustainability and long-term viability of the industries we work in. As process manufacturers increasingly come on board, we are beginning to achieve levels of efficiency never previously imagined. M
About the authors:
Chris Hamlin is Director, Capability Development at Seeq Corporation