The growing importance of composite materials is illustrated by a statistic from the commercial aerospace industry. The primary serious composite applications were in sports in the 1980s. About 6% of the structure’s weight was composites. Moreover, the composite application curated in Boeing’s new 787 Dreamliner has 50% composite content.

Composites are a key focus for materials innovation and application – for instance , in high-performance engineering applications that need strong, light materials, or where there's a requirement to tailor the properties of the fabric

The growing importance of composite materials is illustrated by a statistic from the commercial aerospace industry. The primary serious composite applications were in sports in the 1980s. About 6% of the structure’s weight was composites. Moreover, the composite application curated in Boeing’s new 787 Dreamliner has 50% composite content.

Composites are a key focus for materials innovation and application – for instance , in high-performance engineering applications that need strong, light materials, or where there's a requirement to tailor the properties of the fabric to the strain field experienced in the application. Additionally to aerospace, big users of composites include: marine engineering, sports equipment, defense, and wind turbines.

A common reason for the utilization of composites is that they deliver outstanding mechanical properties at lower weight in comparison to standard materials – for example, to the aluminum alloys utilized in aerospace. Such property comparisons are essential when selecting materials – or, conversely, when marketing materials for particular applications. These comparisons require the proper property data – not just about technical properties, but about economic and

Environmental properties, and process.

Materials selection is simply one activity that materials and process data (and the associated tools) are important. Perhaps the foremost important application is in detailed product design – for instance, during computer-aided design (CAD) and computer-aided engineering (CAE). The effectiveness of those activities is very hooked in to the accuracy and fitness-for purpose of the materials data that underlies them. And ineffective design and modeling are often very costly,

leading to delays further down the product development cycle, or maybe problems with the ultimate product.

Once a product has been produced, materials data remains vital. Through quality assurance and testing activities, manufacturing organizations seek to ensure that the performance of the fabric in use is as expected, and to refine their data of the fabric. They also continually refine product designs, and will often got to change materials or the way during which they're used (e.g., to substitute obsolete materials, to improve performance, or to optimize cost). Similarly,

composite producers seek to innovate and continually improve the materials themselves. All of those activities require the proper composite data – data that's often complex and in large quantities.

Materials data management – and why composites are different. The need for materials data management is, of course, not unique to composites. Data is typically stored on paper, in assorted spreadsheets, or in generic database systems not designed for materials information. Expert tools that analyze or use materials data tend to be isolated – it's hard to urge data into and out of those tools. Data sources are often scattered across the organization. We concluded that such an approach can cost many dollars in lost productivity, repeated tests, lower product quality, higher risk, and missed opportunities for innovation. Solutions to those challenges are now well-established for conventional materials. An example is that the work of the Material Data Management Consortium.

Yet, until comparatively recently, similar progress has not been made within the case of composites. The problem of overcoming materials data management problems greatly increases for composites, because the information required to explain them is inherently more complex. Composites are often highly anisotropic, they contain relatively complex combinations of materials during which matrix (e.g., polymer resin) and reinforcement (e.g., fiber) properties are both critical to performance. And, as we've seen, their properties are more hooked into geometry and processing routes than many other materials.

Materials pedigree and properties

The challenges of composite data management begin with the foremost basic fact about these materials. They consist of quiet one material. Such structures pose a variety of problems for any systematic materials data management system, the most prominent of which is that they have to store and link to ‘pedigree’ or process history information.

It is vital to stay good pedigree information. Companies might want to make sure ‘traceability’ from any testing or design data back to data about the original batch of fabric. Or they'll simply want it to be possible to seek out all test and production data related to a selected material batch or production run. For example, in aerospace engineering, if a test shows a problem in materials production, engineers will want to quickly find full information about the source for this

material, its processing, and where else it's been used. Regulators or customers may demand similar searches as a matter of routine. Without effective materials data management, these searches can take days, weeks, even months. they ought to take minutes.

Enabling efficient, speedy traceability requires an information system which will capture the info about every batch of fabric, every test, and each analysis in a single, central database, also as automatically linking related items of data, and maintaining those links as data is manipulated or used. This is a difficult information management problem, since the web of connections builds up rapidly as test data is processed, reduced, combined with other data, analyzed to create statistical design data, and eventually applied in design.

For a monolithic material, like a bit of metal, at least the start line may be a single entity with one set of properties.

Best practice composite data management demands that we store and may easily retrieve all of the relationships between the fabric and every of its constituents, and any relationships between constituents establish trends between the ultimate properties of a laminate and, e.g., different fiber sizing.

Composites also require us to store additional data that is not typically required in describing conventional materials. It provides some examples, including specialist property information and extra ‘meta data’ that describes how the components are integrated in the composite.

Anisotropy and therefore the environment

Materials property data is, by its nature, complex and

specialized. The systems used to manage this data must respond to this. For instance , these systems got to handle specialist units and conventions. They have to ‘build in’ the formulae, algorithms, and models that describe and analyze relationships between these properties so as to get useful information for the materials engineer or designer. Much of this data and information is multi-dimensional. A cloth property is usually not described by one number, but by a series of functions or graphs that show its variability with environmental variables like temperature and humidity.

Composites complicate matters further. They add extra dimensions to the info, since composites are invariably anisotropic, exhibiting different properties in several directions.