The objective to decrease product development costs while improving performance compared to existing composite and metal products is the driving need for development of improved predictive tools and for increasing their use across the industry. Improved predictive simulations can reduce the current practice of overdesigned parts, thus reducing material usage – both waste and the amount of material in the product life-cycle. Industry also needs to respond to the driver of greater stakeholder expectations for environmental improvement of composites, recycling and the general link of greater life-cycle benefit to lower product total costs. Indirect drivers for the use of LCI models include international expectations for environmental product declarations, government policies on purchases and financial institutions’ perception of the benefit of clear environmental profiles.

The widespread adoption of predictive modeling tools faces challenges that include the lack of material data inputs and of a general recognition of the advantages that can be gained from such modeling. Currently, processes rely heavily upon in-house experience and the design-build-test process. The reliance on past experience limits the vision of possibilities for process and part design to what is known from past history. Virtual models can expand the range of possibilities. Also, industry is generally unable to demonstrate and communicate the environmental benefits of new composite products. Both process simulation and LCI tools are hampered by a universal concern over the lack of availability of a standardized material database. Cost and access to training in the proper use of some of the tools is also a concern.

The implementation of demonstration projects and initiatives, which include the use of predictive modeling tools, can educate industry about the capabilities of these tools and show their value in expediting the design of manufacturing processes. Additionally, it is important to expand materials databases to include the properties needed by these simulations. Ideally, a central clearinghouse for the data should be freely available: a collaboration of federal agencies, such as the Department of Energy, the Department of Defense, the Department of Commerce, NASA, the National Transportation Safety Board and/or IACMI would be the obvious groups to underwrite such an initiative.

Life-cycle predictive tools also need further development. The availability of representative, non-proprietary composite life-cycle inventory data for the largest composite end-use product groups is needed. Data is required for the majority of chemical constituents and composite assembly techniques. It is critical to develop life-cycle profiles of composite recycling and benefits in recycled or repurposed composite materials.