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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.
Create master structure Summation of the relationships of the items (parts, subassemblies, assemblies) resembles in a master structure. Documenting: Link product definition: Documents that describe the parts are pointed out from the product structure. This allows the user to easily find a document of the correct revision. Define product ...
With the emergence of the Internet, the capability of MDBs increased. Web-enabled MDBs provide a more centralized management and conservation of Materials data. Finding and accessing the required data is faster than to search for them in a traditional manner, e.g. from handbooks or Microsoft Excel files.
A configuration item type (or CI type) is the data type of the element or configuration item an enterprise wishes to store within the CMDB. At a minimum, all software, hardware, network, and storage CI types are stored and tracked in a CMDB.
Material requirements planning (MRP) is a production planning, scheduling, and inventory control system used to manage manufacturing processes. Most MRP systems are software -based, but it is possible to conduct MRP by hand as well.
Product data management (PDM) is the name of a business function within product lifecycle management (PLM) that denotes the management and publication of product data. [1] In software engineering, this is known as version control. The goals of product data management include ensuring all stakeholders share a common understanding, that confusion ...
Master data management (MDM) is a discipline in which business and information technology collaborate to ensure the uniformity, accuracy, stewardship, semantic consistency, and accountability of the enterprise's official shared master data assets.
Materials informatics is at the convergence of these concepts, but also transcends them and has the potential to achieve greater insights and deeper understanding by applying lessons learned from data gathered on one type of material to others. By gathering appropriate meta data, the value of each individual data point can be greatly expanded.