Materials data is a critical resource for manufacturing organizations seeking to enhance products, processes and, ultimately, profitability. This data describes the properties and processing of the materials that these organization uses - metals, alloys, plastics, composite materials, ceramics, etc. This data may come from a wide range of sources - e.g., materials testing, quality assurance, or measurement of product performance. The process by which manufacturers manage and use such information is one essential 'cog' in the larger machine that is the product lifecycle.
One project that has looked at this issue in-depth is the Material Data Management Consortium (MDMC), a collaboration of leading aerospace, defense, and energy enterprises - organizations such as NASA, Boeing, Rolls-Royce plc, Honeywell, and GE Aviation. The MDMC has identified the problems caused by failures in the materials data management process and investigated how an optimized process can lead to better innovation and quality.
Materials data management Wikipedia
Problems typically relate to productivity and data integrity. They begin with difficulties in consolidating specialized data stored in disparate sources and varied formats. Problems continue with the challenge of controlling and using approved information effectively throughout an organization, often within complex processes. These include:Engineers spending hours finding property data to support analysis or simulation
Materials scientists duplicating existing test results or generating data that goes unused
Design iterations failing due to outdated or inconsistent data
Weeks taken tracing the source of design data for certification, or customers, or to support the design process
This final issue ('traceability') is particularly important in quality and safety-conscious industries (such as aerospace or medical devices) where engineers need to be able to trace the full pedigree for a manufactured component - ideally, not just back to the design, but to all of the raw (materials and other) data used to create the design. This need for traceability has been a key driver for many commercial materials data management projects.
Materials data management is not just about the avoidance of problems and risk. The MDMC reports that best practice materials data management can have very positive effects on innovation and quality. For example, Rolls-Royce Aerospace have described how the ongoing assessment and analysis of all of the materials property information generated across the testing and design process can allow an organization to continually refine the 'allowable' values used in design, leading to improved product performance.
Materials data management practictioners usually emphasize the need for a holistic approach. It is of limited use having a superb means to capture test data if that data disappears into a ‘black hole’ database that no-one accesses. Materials property analysis is a wasted investment if the results generated are not deployed effectively to the engineers who need to use them.
One way to itemize such issues is to examine each stage in the full materials data lifecycle. The MDMC sees this process as having four stages: capture, analyze, deploy, and maintain. Key issues at each stage are:
These issues need to be addressed through a combination of good practice, robust processes, and appropriate information systems. MDMC members use a particular commercial-off-the-shelf (COTS) software solution. Whether an engineering enterprise applies such a solution or builds an in-house system, it needs to account for the issues above and to integrate into its wider product lifecycle management (PLM) systems.