What is digital engineering?
Digital engineering is the process of creating digital systems, products, and applications using digital data, modeling, and simulations.
Digital engineering basics
Digital engineering expands beyond the boundaries of traditional engineering, applying modern technologies to generate digital models, prototypes, and other plans and designs that allow engineers to produce digital environments for testing and simulation.
Digital engineering relies on a single source of truth (SSOT) architecture and draws on other technologies and applications, like building information modeling, to create models, real-time simulation, testing, implementation, and analytics for a given project.
In conjunction with product lifecycle management (PLM), digital engineering can help enterprises more efficiently manage the development, launch, promotion, and retirement of products and services.
Benefits of digital engineering
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Improved efficiency and productivity:
Digital engineering allows engineers to rework and iterate designs within a digital environment, as many times as they like. Unhampered by the cost of reconfiguring or reworking physical prototypes, engineers can have more leeway to experiment and test designs before committing to a final model. Once they’ve finalized a model or design, the digital environment allows them to reuse and adapt the model for updated or related projects.
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Increased collaboration across teams:
A digital engineering strategy promotes transparency and visibility across teams. Enterprises can easily grant access to multiple people or groups, helping ensure they have the data and resources necessary to work. Digital engineering promotes manufacturing innovation as teams benefit from streamlined resources, tools, and information.
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Improved data management:
Relying on an SSOT means all workers can find and trust the data on a given project. Digital engineering improves visibility over all data, across every step of a project, providing automatic documentation of updates, changes, and decisions, and allowing workers to store and document all enterprise knowledge in one location.
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Improved safety and risk mitigation:
The robust testing capabilities provided by digital engineering mean that engineers have a larger capacity to test and analyze risky processes or systems prior to launch. Making use of digital twins allows workers to rely on tests and simulations within a digital environment, rather than having to spend time in a high-risk real-world environment. And the ability to assess performance early on in a project allows workers to identify problems, risks, design flaws, and errors before they occur.
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Expanded testing capabilities:
Digital engineers can perform rapid tests in the digital environment immediately, garnering real-time results that can inform enterprise decisions about a product or project. The ability to build out a digital twin means engineering teams can confidently and quickly run tests and study their results while saving time and money.
Digital twin: a model built in a digital environment that mirrors the operations and behaviors of its real-world, physical counterpart. Digital twins can exist in the industrial metaverse, where engineers can better understand complexities and connections that could occur in the real world. Learn more about digital twins.
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Stronger analytics:
Utilizing digital models and simulations lets organizations analyze data outputs immediately, anticipating and responding to problems, issues, and concerns more efficiently. With improved analytics, teams have a fuller picture of a project, allowing them to be more agile and innovative.
PLM software and digital engineering
What is PLM software?
Product lifecycle management (PLM) software tracks a product’s lifecycle state from ideation and development to its removal from the market, capturing and managing data and developments throughout the entire process. PLM software for digitization offers a single repository for a product’s data and pulls in real-time data from technologies like machine learning or AI to provide a digital thread that connects relevant data to an SSOT.
PLM involves:
- Resource planning
- Product design
- Document management
- Workflow management
- Bill of material management
- Product marketing
- Product data management
- Supply chain management
- Customer relationship management
Key features of PLM software include:
- Collaboration tools
- Centralized data repository
- Computer-aided design tools
- Integrated supply chain execution
- Inventory management
- Enterprise resource planning
- Change and configuration management
How do PLM software and digital engineering work together?
PLM software can provide the central platform that digital engineers need to collect and organize data in a single location and build out models and digital twins. Because PLM software collects and manages the data on a given project, it can provide the SSOT necessary for digital engineering, as well as tools and support for updates and changes to models. PLM software can help engineers manage different versions of a product and control which transactions are allowed for particular versions.
Key PLM metrics for success
A strong PLM strategy can generate specific key benefits for your enterprise. Consider the following metrics when evaluating your PLM strategy:
- Increased revenue and quicker time to market: PLM allows enterprises to develop stronger products more quickly, benefiting from a speedier arrival in the market.
- New product cycle: PLM can help enterprises identify opportunities for efficiency and streamline new product processes.
- Improved supply chain management: PLM software can manage, track, source, and potentially suggest substitutions for parts of a given product.
- Increased productivity: By eliminating unnecessary tasks and inefficiencies, PLM strategies and software can free up teams to focus more on their most important tasks.
- Reduced expenses: Collecting data into one transparent platform increases visibility and reduces the risk of duplication.
- Stronger collaboration and innovation: By centralizing a product or service’s data, teams and workers have access to the information they need and can more readily work together on updates and new products and services.
- Streamlined production: Creating standard processes, templates, maps, and other tools means enterprises can reduce production time.
PLM software for digitization
End-to-end manufacturing cloud solutions, like Microsoft Cloud for Manufacturing, provide product lifecycle management support for physical and digital products. Workers can collaborate and communicate easily from anywhere, driving productivity and innovation. Supply chain management capabilities can help enterprises create adaptable, resilient supply chains, allowing them to operate with precision and foresight. IoT platforms like Azure Digital Twins help workers gain insights that drive better products, optimize operations and costs, and create breakthrough customer experiences. Embracing the right PLM strategy for your organization can help you digitally empower your workforce, operate safer and more agile factories, strengthen your supply chains, and unlock innovation.
Frequently asked questions
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Digital engineering is the process of creating digital systems, products, and applications using digital data, modeling, and simulations. Digital engineering expands beyond the boundaries of traditional engineering, applying modern technologies to generate digital models, prototypes, and other plans and designs that allow engineers to produce digital environments for testing and simulation.
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Digital engineering offers a wide range of benefits, including:
- Improved efficiency and productivity
- Improved data management
- Expanded testing capabilities
- Increased collaboration across teams
- Improved safety and risk mitigation
- Stronger analytics
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PLM software supports digital engineering, providing a platform for an SSOT where enterprises can design and develop products within a digital environment.
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An effective PLM strategy should result in the following:
- Increased revenue and quicker time to market
- Simplified new product cycle
- Improved supply chain management
- Increased productivity
- Reduced expenses
- Stronger collaboration and innovation
- Streamlined production
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Drive more efficiency and reduce costs with solutions like Azure high-performance computing (HPC) for manufacturing.
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