Digital Twins: Predict Problems Before They Appear
Nikola Sretenovic, CSCP
Senior Supply Chain Professional | Specializing in Cost Reduction & Process Optimization | CSCP & Lean Six Sigma Black Belt | Energy Sector
Predicting and preventing problems before they happen is now possible with Digital Twins. Businesses everywhere are leveraging these virtual replicas of real-world equipment, processes, and systems to test scenarios, foresee challenges, and fine-tune performance.
Digital twins empower organizations to stay ahead by enabling precise simulations and risk-free experiments.
They help companies avoid costly downtime, reduce maintenance expenses, and enhance overall operational efficiency through real-time monitoring and predictive analytics.
So, What's a Digital Twin Exactly?
A Digital Twin is a precise virtual model of a real-world asset, process, or system. It mirrors reality so accurately that you can predict issues, test scenarios, and optimize performance, all without touching the physical counterpart.
Originally, Digital Twins were pioneered in aerospace because a plane falling from the sky is the definition of a high-stakes problem.
Today, industries from manufacturing to healthcare and supply chains are leveraging this technology to gain competitive advantage.
How Do They Work?
Think of Digital Twins as your proactive maintenance superheroes, powered by real-time data.
Here’s how it works:
Digital Twins in Supply Chains: Healing Complexity
Supply chains today face unprecedented pressures: rapid shifts in demand, rising customer expectations for fast deliveries, increasing operational complexity, and unpredictable disruptions like pandemics or economic shocks.
Digital twins step in here as game-changers. They simulate entire supply chain processes, from manufacturing and warehousing to distribution and returns, helping organizations predict scenarios and optimize decisions dynamically.
When paired with predictive AI, digital twins become self-monitoring and self-healing, offering granular insights for every SKU, fulfillment center, and even transportation methods.
Companies utilizing digital twins in their supply chains report impressive outcomes, such as 20% improvement in customer delivery accuracy, 10% reduction in labor costs, and up to 5% increase in revenue.
Why Businesses are Obsessed with Digital Twins
Digital twins offer substantial financial savings by drastically cutting maintenance and repair costs. They predict potential issues before they occur, preventing expensive breakdowns and costly downtime. Organizations can anticipate equipment failures, schedule maintenance proactively, and allocate resources efficiently, leading to smoother operations and increased productivity.
Safety is significantly enhanced as digital twins allow companies to simulate risky scenarios safely. Whether testing how a car performs in a crash or evaluating industrial processes under extreme conditions, digital twins provide critical insights without endangering human lives or physical assets.
Environmental sustainability also receives a substantial boost from digital twins. By accurately modeling and optimizing processes, organizations reduce waste, minimize emissions, and maximize resource efficiency. Digital twins enable precise adjustments to production and operational processes, making operations cleaner, more sustainable, and compliant with environmental regulations.
Building Your Digital Twin: The Three Key Ingredients
Creating an effective digital twin begins with sophisticated modeling and simulation. The virtual representation must be detailed enough to reflect all relevant aspects of the real-world asset or system accurately. This precise modeling ensures reliability when running simulations and predicting outcomes.
Next, capturing real-time data is crucial. Sensors embedded in the physical assets continuously feed the digital twin with live updates. This ongoing flow of data ensures the twin accurately mirrors current conditions, allowing businesses to respond immediately to changes or irregularities.
Finally, the data collected needs advanced analytics to become actionable. This involves applying sophisticated algorithms and artificial intelligence to analyze data, identify patterns, forecast potential issues, and recommend corrective actions. By leveraging analytics, digital twins turn raw data into strategic insights, enabling proactive decision-making and ongoing optimization.
Real-World Magic: How Leading Companies Use Digital Twins
Companies across sectors have embraced digital twins with remarkable results. SpaceX, for example, utilizes digital twins to closely monitor spacecraft during missions, enabling them to anticipate and address issues in real-time, significantly enhancing mission safety and success.
Mercedes-Benz employs digital twins to streamline vehicle development. By creating virtual vehicle models, Mercedes-Benz drastically reduces the time and cost associated with physical prototyping. This allows rapid iteration of designs, enhancing innovation and product quality.
Challenges in Adopting Digital Twins
Adopting digital twins, however, comes with its own set of challenges. High initial investments in technology, infrastructure, and staff training can be significant barriers, especially for smaller or resource-constrained companies.
Change management is another hurdle, as employees accustomed to traditional processes might resist adopting new technologies. Effective leadership, clear communication of benefits, and strategic change management practices are essential for successful implementation.
The complexity of digital twin technology itself demands strong project management skills, technical expertise, and strategic oversight. Organizations must methodically build their capabilities, recruit or train experts, and cultivate internal buy-in to overcome these obstacles successfully.
Starting small is often the most effective approach. Choose one critical asset or component, demonstrate success, and gradually scale your digital twin strategy.