- By Chris Hutchings
- April 25, 2024
- Feature
Summary
Digital twins, virtual replicas of physical assets, processes or systems, are becoming the cornerstone of any forward-thinking digital ecosystem.
In an era where the pace of technological advancement continues to accelerate, and the complexity of engineering projects reaches new heights, cost engineers face unprecedented challenges. Traditional methods of estimating and managing project costs are increasingly falling short, needing help adapting to the dynamic nature of modern engineering projects. Enter the concept of digital twins—innovative technology poised to redefine the cost engineering landscape.
Digital twins, virtual replicas of physical assets, processes or systems, are becoming the cornerstone of any forward-thinking digital ecosystem. By offering a dynamic and predictive representation of projects, these digital counterparts enable a level of planning and analysis previously unattainable. This article explores the burgeoning wave of digital twin adoption within cost engineering, examining how this technology promises to enhance project management practices and serve as a beacon of innovation in a discipline craving transformation.
From reducing unforeseen expenses to streamlining project execution, introducing digital twins is the precipice of a significant shift in how costs are estimated and managed. By simulating various scenarios and analyzing potential outcomes in a risk-free environment, digital twins provide engineers and project managers with the tools to anticipate and mitigate financial risks before they materialize. This capability to predict and plan with unprecedented accuracy heralds a new era in cost engineering, where data-driven decisions lead to more efficient, cost-effective and successful project outcomes.
A critical advantage of digital twins is their ability to provide real-time, on-demand data on project progress across many key metrics, including costs. This continuous stream of information enables stakeholders to monitor performance metrics, identify trends and detect anomalies promptly. This drives the necessary socio-technological partnership toward real-time insight and informed, defensible decisions regarding cost. Additionally, using digital twins supports continuous improvement, enabling organizations to iteratively refine project plans and processes based on ongoing feedback and insights.
From military to manufacturing processes, there are several use cases for digital twins and how they can be used effectively.
1: Use case: Enhancing military fleet maintenance and operational readiness with digital twins
A naval force comprising various classes of ships and submarines aims to enhance its fleet’s maintenance, operational readiness and cost efficiency. Faced with the challenges of maintaining a high level of readiness while minimizing operational costs, the Navy adopts digital twin technology to create precise virtual replicas of its vessels.
Application and benefits:
- Predictive maintenance: Utilizing digital twins, engineers can predict maintenance needs and potential system failures before they occur. By analyzing sensor data on actual ships and comparing it with the digital twin, the Navy can schedule maintenance more efficiently, reducing downtime and extending the lifespan of critical components.
- Operational planning: The digital twin allows for the simulation of various operational scenarios, including combat simulations and environmental conditions. This enables strategic planners to optimize fleet deployments based on fuel efficiency, potential wear and tear, and mission success rates, ensuring cost-efficient operations.
- Cost-effective upgrades and retrofitting: Before physically modifying vessels, the Navy can use digital twins to test the impact of upgrades or retrofits on performance and costs. This virtual testing environment helps identify the most cost-effective improvements, reducing the risk of expensive or ineffective modifications.
Digital twins offer a powerful tool for military organizations striving to maintain superior capabilities economically, providing a dynamic platform for predictive maintenance, operational planning and cost-effective digital decision-making. However, while digital twins can be incredibly valuable, implementation into the corporate ecosystem brings several challenges, including the initial investment required to develop and deploy digital twins and the need for specialized skills and expertise. Moreover, integrating digital twins into existing project management systems and workflows may require substantial organizational processes and practice changes. This requires effort, a coherent vision and a congruent culture change.
2. Use case: Enhancing manufacturing process efficiency and cost reduction in automotive manufacturing
An automotive manufacturer seeks to enhance the efficiency of its production line and reduce manufacturing costs. The company implements a digital twin of the production process to achieve these objectives, encompassing assembly lines, machinery and workforce.
Application and benefits:
- Process optimization: By simulating the manufacturing process in the digital twin, engineers identify bottlenecks and inefficiencies, allowing them to redesign workflows for optimal efficiency and lower costs.
- Maintenance predictions: The digital twin monitors the condition of equipment in real time, predicting maintenance needs before breakdowns occur. This predictive maintenance approach reduces downtime and maintenance costs, contributing to smoother operations and higher productivity.
- Innovation testing: The company uses the digital twin to test the implementation of new technologies or materials in the manufacturing process in a virtual environment. This allows for assessing the impact on costs and efficiency without disrupting actual production, fostering innovation with minimized financial risk.
The power of digital twins in manufacturing offers a strategic tool for process optimization, predictive maintenance and innovation testing. By providing a detailed virtual model for simulation and analysis, digital twins enable manufacturers to make data-driven decisions that reduce costs and enhance production efficiency.
Digital twins and the future of cost engineering
Digital twins stand at the forefront of revolutionizing project management and cost engineering. They not only offer a transformative solution for navigating the complexities of modern projects through improved cost estimation, progressive risk management and enhanced decision-making but also signal a shift towards more dynamic, data-driven operational strategies. With over two-thirds of companies planning for implementation, digital twins rapidly move from innovative practice to standard procedure. This trend is projected to accelerate as the technology matures and becomes more widely accessible, prompting organizations across various industries to explore its potential for unlocking unprecedented efficiency, innovation and cost-effectiveness.
Digital twins are reshaping cost engineering, providing unmatched insights and capabilities for meticulous project planning, thorough analysis and accurate prediction. By mirroring physical assets and processes in a virtual environment, they empower organizations to simulate scenarios, monitor real-time performance and make informed decisions based on solid data.
Despite the hurdles of initial investment and the need for specialized skills, the substantial benefits of digital twins make them indispensable assets. As more organizations adopt digital twins as a cornerstone of project management, they not only navigate current challenges more effectively but also position themselves to capitalize on new opportunities, securing a competitive edge in an increasingly complex and fast-paced global landscape.
About The Author
Chris Hutchings is vice president global solutions at Galorath Incorporated. Chris joined Galorath in 2004, bringing over 30 years of experience developing, implementing and supporting various value-added solutions. Before joining Galorath, Chris enjoyed careers in the British Civil Service (MOD) and the British Army (REME).
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