Why you need to understand Model-Based Engineering
NIST recently published a report from the Model-Based Enterprise/Technical Data Package summit they hosted last December. You can download a copy of the report at http://dx.doi.org/10.6028/NIST.TN.1753.
You might wonder, why should you care about this subject?
I could explain it, but I think the report does a pretty good job. Take some time to read the following, taken from the report. It’ll be worth it.
Until recently, most engineering and manufacturing activities relied on hardcopy and/or digital documents (including 2D drawings) to convey engineering data and to drive manufacturing processes. With the advent of new manufacturing data format standards and more powerful engineering software, it is now possible to perform all engineering functions using data models. The model-based engineering (MBE) approach uses these models rather than documents as the data source for all engineering activities throughout the product life cycle. The core MBE tenet is that models are used to drive all aspects of the product lifecycle and that data is created once and reused by all downstream data consumers.
A model is a representation or idealization of the structure, behavior, operation, or other characteristics of a real-world system. A model is used to convey design information, simulate real world behavior, or specify a process. Engineers use models to convey product definition or otherwise define a product’s form, fit and function. In MBE, models can be applicable to a wide range of domains (systems, software, electronics, mechanics, human behavior, logistics, and manufacturing). Models can be either computational or descriptive. Computational models are meant for computer interpretation and have a machine-readable format and syntax. Descriptive models are human interpretable and meant for human consumption (symbolic representation and presentation). Core to MBE is the integration of descriptive models with computational models. Computer aided design (CAD) models used in manufacturing are a good example. Early CAD models were meant only for human viewing. Today, CAD models can be directly interpreted by other engineering software applications. A variety of standard interchange formats now exist to enable application-to-application transfer of engineering data.
In the context of manufacturing, model data drives production and quality processes. A product model used in manufacturing is a container not only of the nominal geometry, but also of any additional information needed for production and support. This additional data, known as Product Manufacturing Information (PMI), may include geometric dimensions and tolerances (GD&T), material specifications, component lists, process specifications, and inspection requirements.
Two critical factors give MBE significant advantages over drawing-based or document-based engineering: 1) computer interpretability and 2) data associativity. The primary reason to use a data model in engineering and manufacturing is that a model can be processed directly by engineering software applications. In a document-based environment, humans must interpret the engineering documents and then enter the information into the specific user interface of each engineering application. Whether it is finite element analysis (FEA) or computer aided manufacturing (CAM), each application creates its own internal model. In the past, the only access to this model was through the application’s user interface (keyboard and screen). With MBE, the applications read and write the models directly. This results in fewer errors and a drastic reduction in processing time.
Data associativity is critical to model integrity. Data association within and between documents is very difficult to maintain. Tolerances, material specifications, surface finish, hardness, and other information must be associated with specific features in the model. In analysis models, for example, boundary conditions are associated with the point at which they act. In assembly models, components must be associated with and oriented toward mating components. Data associativity is critical for model interpretation by software applications and is built-in to the model representation formats and data exchange standards. Quintana et al. define a product’s Model-Based Definition (MBD) as a dataset containing the model’s precise 3D geometry and annotations. The annotations specify manufacturing and life cycle support data and may include notes and lists. The model comprises a complete definition of the product, without relying on supplemental documents such as 2D drawings. 2D drawings are not needed when annotations are associated with objects in the model and can be viewed with the model.
Not only do humans have to be able to understand the model, but software applications have to “understand” the model as well. Quintana outlines requirements for engineering models.
- CAD systems must be able to manipulate, import, and export 3D solid models.
- CAM software must be able to define and validate machine-readable instructions for making the model, and must document the process definition.
- Computer Aided Engineering (CAE) software must be able to validate and optimize the product definition.
- Product Lifecycle Management (PLM) software must be able to control access and manage change of the various models and documents associated with the product.
- Applications such as Enterprise Resource Planning and Manufacturing Execution Systems need to extract raw material and component information from product models.
The key to achieve interoperability across software applications is open standards, i.e., those developed by consensus either within a standards development organization or a consortium of stakeholders. No single software tool can perform all of the engineering tasks needed to design and manufacture a product. No single software product can do it all well. Users will mix and match software products according to their business objectives. Standards define an agreed-upon syntax and semantics of 3D modeling constructs and annotation so that users can understand one another’s models. Standards for representing, exchanging, and determining the fidelity of PMI are of particular importance because PMI (includes GD&T annotations) is essential to manufacturing. Driven by industry, standards are adopted nationally and internationally, positively affecting interoperability across software applications.
Open standards are vital for MBE. Unlike industry standards, where the underlying technology is neither open nor democratically managed, no single company can exert an inordinate amount of control over the intellectual property in an open standard. As a result, a company whose product model is based on open standards is less likely to find itself in a situation where it must rely on a competitor’s software in order to “understand” the model or, even worse, support a product whose digital model was created using software and computer hardware that is no longer available. Avoiding the latter scenario is of particular concern for companies such as aerospace manufacturers whose products have lifecycles measured in decades – far longer than the typical lifetime of a CAD software application or computer operating system.
If you’ve made it this far, I’d like to clarify something: The term “model-based engineering” is used by different people to mean different things. Enterprise architects, software engineers, systems engineers, and business analysts all tend to see MBE through the lenses of their own experience. But that’s another article.