For more on the Enterprise Materials Optimizer method that underlies MI:Optimize, and its use in implementing strategic approaches to materials decisions, see the white paper Optimizing Materials Strategy—can you afford not to?
GRANTA MI:Optimize ensures a consistent approach to optimizing materials and manufacturing choices across an enterprise, while helping to increase the quality of these decisions.
Through a simple web browser interface, designers and engineers can apply powerful 'cost per unit of function' methods to ensure that materials decisions are made in a rational, repeatable manner, combining consideration of both the engineering objectives and cost. The tool can be tuned to a company's 'business rules', making it an effective way to implement corporate materials strategies designed, for example, to improve the quality of material choices, to lower cost, or to meet eco objectives.
The importance of 'cost per unit of function'
Companies have many different drivers for materials strategies, but a common thread is the need to consider the functional requirements of a material in conjunction with the 'cost' of specifying and using that material. 'Cost' may mean, for example, the $ cost of procuring and processing the material, the environmental implications of its use, or a packaging cost such as volume. Frequently, the focus is material cost reduction, targeting both new product development and the evolution of existing products. But the motivation could also be weight reduction (aerospace); volume reduction (miniaturization, nano); process cost reduction; eco-cost reduction; or substitution of ‘retired’ materials.
However cost is defined, the concept of minimizing 'cost per unit of function' is fundamental. GRANTA MI:Optimize embodies this concept.
Guided by a simple-to-use 'wizard' user interface, the user begins by specifying the design objective—for example, to select the best material to minimize the cost of a panel loaded in bending. They can then specify any additional 'must-have' functional requirements, such as thermal or electrical properties. The system will rank all candidate materials with respect to the overall design objective, with further iterations being simple to explore.
There is complete flexibility in defining the objectives, enabling sophisticated studies, while still being user-friendly. One valuable feature is the ability to define an existing material as a benchmark, enabling rapid and straightforward comparisons, for example, when searching for substitute materials.
This functionality is accessed via the GRANTA MI:Viewer web browser user interface. This supports another powerful feature—the ability to promote a consistent approach to materials decisions across the enterprise. Combining materials expertise and purchasing guidelines, your company can create 'business rules', for example, defining preferred materials, or recommending specific approaches to different categories of materials decision. Through the browser interface, MI:Optimize analyses can then be made available to any user in a highly user-friendly manner, with these business rules already defined. Thus MI:Optimize becomes a tool to ensure that decisions are taken consistently and repeatably across the business.
A ready-configured materials database is provided with MI:Optimize. The database provides materials reference data from the MaterialUniverse data module and the ability for you to add your in-house data and business rules. This it fast and easy to implement and configure an MI:Optimize 'materials selection wizard' for your company.
Defining design objectives and ranking materials options
Materials databases typically operate in terms of as-tested materials properties, such as 'Modulus of Elasticity'. But, when designing a component, a designer has an objective for the overall component, such as maximizing the stiffness of a beam in bending. Further, the designer does not have limitless scope in optimizing this stiffness, but will most likely be constrained by some other factor, such as cost. So the design objective becomes 'maximizing the stiffness of a beam in bending, for minimum cost'. Using the performance index methodology pioneered by Professor Mike Ashby, the Enterprise Materials Optimizer enables users to specify not the 'raw' materials properties, but instead these compound design objectives. The system then computes the appropriate performance index and ranks candidate materials according to the index, with the top-ranked materials being those that best meet the objective.
Advanced cost model, including processing costs
Advanced cost models mean that MI:Optimize studies can consider not simply the base cost of the material, but also the cost of processing options. The user can also add cost factors to allow for additional costs that may be incurred by particular materials/process categories.
Using a classification of 'preferred materials'
An important aspect of most companies' materials strategies is the definition of preferred materials and/or suppliers. Materials may be preferred, for example, on cost or availability grounds, or on the capability of the factory to process them. MI:Optimize allows organizations to classify materials in a hierarchy of preferred 'tiers'. In making their choices, designers are initially presented only with 'tier 1' preferred materials. If these are not suitable, options from 'tier 2' are presented. Finally, all materials options are offered. The process provides a rational and systemic process to determine the best choice in line with company strategy.
Reference materials for substitution studies
A number of the use cases of this approach involve comparison to a known existing material. For example, a manufacturer may wish to replace an existing material with a cheaper one, or one that is easier to procure, or one not subject to environmental regulations. Material producers may wish to see how their materials compare to competitors, or to define the market position of a newly developed material. Such use cases, are addressed in MI:Optimize through the definition of a Reference Material. Chosen by the user, this material appears in all materials lists, pass/fail reports, and graphical illustrations of material performance, and the performance indices of all candidate materials are automatically normalized against that of the reference material.
Graphical reporting tools (pictured below) make it easy for users to analyze results—for example, highlighting on a graph cheaper materials that can offer the same performance as a reference material.