URM GROUP Announces Filing of Manufacturing Optimization Provisional Patent Application

Universal Risk Management Group (URM GROUP), a leading digital twin innovator, today announced that it filed a manufacturing optimization provisional patent application in the United States Patent Office (USPTO) and Japan Patent Office (JPO).

The patent application sets forth a novel mathematical modeling method for manufacturing optimization of production processes. URM GROUP believes the innovation will help manufacturers build and execute strategic plans to achieve environmental and economic performance objectives.

The novel technology creates a representative digital twin of end-to-end manufacturing production processes and performs predictive analysis to find the root cause of inefficiencies, potential risks, and opportunities for improvement. URM GROUP believes these capabilities will allow technology users to analyze multifaceted, time-dependent relationships across production processes and quantify the effects changes will have on profitability, customer service, efficiency, and environmental performance objectives. In addition, URM GROUP believes that this innovative modeling method will introduce important sustainability metrics that accurately quantify the environmental impacts of complex manufacturing processes.

The filing of this provisional patent application directly serves URM GROUP’s goals to provide customers with digital twins and intelligent decision-making tools that cover the intricate and ever-changing interactions, dependencies, and uncertainties arising from dynamic networks’ complex nature. If approved, URM GROUP believes this patent will significantly enhance how manufacturers make informed decisions that prioritize sustainability and optimize performance.

URM GROUP aims to protect the technology, inventions, and improvements that are commercially important to the development of its business through the effective use of intellectual property instruments, such as patents, trademarks, and trade secrets.

URM GROUP has built a portfolio of 22 provisional patent applications with the United States Patent and Trademark Office (USPTO) and the World Intellectual Property Organization (WIPO). To date, 11 patents have been granted by the USPTO and WIPO. The patents are in two main areas: mathematical modeling and decision support metrics, covering X-ACT activities, products, and customer services related to the economy, business operations, information technology, and human health.

Nabil Abu el Ata, Founder and CEO of URM GROUP:

“We expect this novel technique for evaluating manufacturing performance and environmental impacts of dynamically complex production processes to be a promising path forward for manufacturers looking to find the right balance between economic and environmental goals. As an early pioneer of the digital twin industry, I recognize this patent’s significant potential, as it directly addresses key sustainability challenges currently facing nations and manufacturers.”

Digital Twin Innovator URM GROUP Unveils X-ACT Green Supply Chain to Translate Decarbonization Goals into Action

X-ACT Green Supply Chain digital twin and decarbonization decision support tools

Universal Risk Management Group (URM GROUP) today launched X-ACT Green Supply Chain digital twin. Enhanced with new patent-pending sustainability metrics, X-ACT digital twin and intelligent decision-making tools provide supply chain designers, operators, and stakeholders with the trusted insights they need to advance sustainability, net-zero, and decarbonization agendas.

X-ACT Green Supply Chain analyzes dynamic behaviors across value chains to identify inefficiencies or opportunities to achieve energy, carbon, capital, and operational savings. To drive smart, informed decisions that prioritize sustainability and optimize supply chain performance, X-ACT verifies the outcome of any planned changes that would be difficult, costly, or even impossible to test with other digital twin solutions or under real circumstances.

By measuring an organization’s performance and carbon footprint across the supply chain, X‑ACT tests decarbonization options, turns sustainability goals into executable strategies, builds consensus for environmental actions, and reports emissions and carbon footprints.

X-ACT Green Supply Chain includes a repository of digital twins covering all major manufacturing, logistics, and transportation value chain processes, activities, and resources to accelerate time to value. X‑ACT digital twins are fully configurable to achieve model representativeness, accuracy, and predictability despite the complexity of global supply chains. Modifiable parameters include the location of facilities, distribution centers, and warehouses, considering factors like modes of transportation, costs, carbon emissions, and renewable energy availability.

Nabil Abuelata, Chief Research Officer, URM GROUP:

“As companies transition to green and digital supply chains, they need new ways to measure performance and balance competing objectives. When companies want to reduce environmental impacts, cut costs, enhance customer service, and boost efficiency, X-ACT Green Supply Chain empowers supply chain participants to make informed decisions and drive change programs that achieve a smart balance.”

Learn more about X-ACT Green Supply Chain

Find out how X‑ACT® Green Supply Chain digital twin technologies can help you gain confidence in decarbonization decisions and operate high-performing, resilient networks at


URM GROUP delivers the answers executives and operational teams need to consistently deliver value and control risks arising from the complex nature of global business operations. Using a unique combination of digital twin technologies and intelligent decision-making tools, URM GROUP products bring problems into focus and verify which actions should be taken to advance business goals. Leaders within critical infrastructure, manufacturing, transportation, healthcare, and governments use X-ACT® to deliver operational excellence and make informed decisions relating to a wide range of strategic objectives, including optimization, digital transformation, and supply chain management.

Risk Assessment

Risk Rating: Scoring Challenges and Solutions

Risk rating is a complex scoring system, which relies upon previous experiences and foresight to anticipate risks that might impact the smooth functioning of business. When risks are well managed, a business can maximize opportunities and control the impact of disruptive events. Alternatively, if a risk is underestimated—or not anticipated at all—a business can suffer significant economic or reputational damage as a result of this unpreparedness.

What is the Purpose of Risk Rating?

Businesses use risk rating to assess the risks involved in an activity. The goal is to anticipate and classify potential risks as low, medium or high based on the expected impact and the likelihood of such an event occurring in the near future. This allows businesses to adopt control measures that can help cure, mitigate or remove the anticipated impact of the risk.

Risk Rating

In situations where risk cannot be controlled or removed, a business may choose to accept the risk or cancel the activity. This decision depends on the likelihood of the risk event occurring and the expected severity of the impact.

Why is Risk Rating a Challenge?

Experience and historical data are useful references when rating the probability and impact of risks that have happened before and may happen again under the same set of circumstances. The bigger challenge is managing unknown risks. Obvious examples include Covid-19, the economic meltdown of 2007-2008, the Fukushima nuclear accident. Unknown risks typically form through complex interdependencies and dynamics that are not fully understood until the event happens.

Human imagination is limited in such cases. Further, humans have a tendency to underestimate the probability of an outlier event or downplay the expected impacts. Even as the economic events of 2007-2008 were unfolding, the US Fed’s risk model did not predict the scope or severity of the resulting recession. With Covid-19, scientists warned governments and healthcare to prepare for the possibility of a coronavirus pandemic, but most did not have sufficient plans in place to contain the health and economic impacts of the virus.

The unexpected impacts of climate change provide another example of how domino effects can catch entire industries and governments off guard. Extreme weather events are causing slowdowns across major supply chains. And rising temperatures are threatening the safety of water supplies. As the world becomes more globally connected and the pace of change intensifies, it will become even more difficult to anticipate the full range of risks that need to be managed.

How Can a Digital Twin Help Improve Risk Scoring?

A digital twin provides a software representation of a physical asset, system or process designed to detect, prevent, predict and optimize the system being studied through real time analytics. Digital twins created within X-ACT include time dependent behaviors, which is key if you want to accurately model the dynamics of assets that change over time—for instance aging or cyclical changes that may impact performance.

Using the digital twin to perform stress testing and sensitivity analysis allows users to quickly identify any conditions that might cause a physical asset to deviate from its expected behavior or find the root cause of problems. As risks are revealed, fixes or controls can be identified using the digital twin and implemented when needed. Users can also gain confidence in decisions and see how different choices playout under various conditions. This is particularly useful to predict the outcome of scenarios that would be difficult, costly or even impossible to test in the real world.

For example, a digital twin can be used to evaluate the benefit versus risk of deploying innovative technologies, like artificial intelligence, blockchain or Internet of Things. Or even help rate the risk of a new business activity, like funding loans for smart city projects, when there is no historical precedent to reference.

By covering every variable which may directly or indirectly influence risk, digital twin analysis can predictively cover known risks and expose unknown risks. This arms decision makers with the missing risk intelligence they need to successfully navigate the complex dynamics and uncertainty of modern business.


The Value of Digital Twin Technology

Interest in digital twin technology is surging as use cases demonstrate its problem-solving value across diverse applications including operations, manufacturing, supply chains, utilities and enterprise management.

A digital twin is commonly defined as a software representation of a physical asset, system or process designed to detect, prevent, predict and optimize the system being studied through real time analytics. Using the algorithmic capabilities of X-ACT, we extend the definition of digital twin to cover the replication of process dynamics. This means the digital twin created by X-ACT covers time dependent behaviors for complex relationships.

Gain Confidence in Decisions and Control Risks

Digital twins let users understand the present and predict the future. Many industries are applying these capabilities to gain confidence in decisions, maintain better control of risk or find opportunities for improvement. A virtual model can span the full lifecycle of any asset or process, product or service and provides an easy way to build and validate new projects or planned changes.

Once it has been verified that the digital twin produces the same results as the target physical asset, the model can be used to determine what is happening or what could happen in the future. This information is gained within minutes by testing a full range of scenarios—including events that would be difficult, costly or even impossible to test in the real world.

Through stress testing and sensitivity analysis users can quickly identify any conditions that might cause a physical asset to deviate from its expected behavior or find the root cause of problems. As risks are revealed, fixes or controls can be identified using the digital twin and implemented when needed. Users can also gain confidence in decisions and see how different choices playout under various conditions.

For example, a business that wants to move critical applications to the cloud can use a digital twin to see what would happen if transaction volumes unexpectedly double. Or a retailer might use a digital twin to analyze the fallout of a multi-day shutdown of a supplier’s manufacturing plant. A car manufacturer could use a digital twin to help answer, “What will be the realistic cost benefits and performance improvements gained by automating or digitalizing our processes?”

No matter the problem, the information gained from digital twins allow organizations to learn and make decisions faster with more certainty in the outcome. The speed and agility enabled by digital twin technologies is expected to become increasingly important as the complexity and pace of business continues to accelerate.