Materials stewardship is an informed approach to materials management that addresses the maintenance of the material during product ownership and the ”second life” of the material after its present use expires. Materials stewardship has been expressed as the four D’s strategies of dematerialization, durability, design for multiple lifecycles, and diversion of waste streams through industrial symbiosis. The framework of materials stewardship provides corporations, government organizations, and their stakeholders a model for preserving and extending the lifetime of materials, thus reducing the rate of materials throughput, cutting waste, and preventing the social, environmental and economic costs due to materials failure. Materials stewardship intersects with the concepts of cradle to cradle and the circular economy. Cradle to cradle is a biomimetic method for product (and system) design that intentionally seeks to harvest materials (and/or energy) at the end of life for future products. The circular economy is a broader view that patterns economic, agricultural and industrial systems around circular lifecycles, in which activities such as product reuse, maintenance, repair, refurbishment, etc. enhance value and reduce waste. In this paper we introduce these concepts, and highlight areas in which an awareness of corrosion management and materials integrity would enhance the viability of these sustainable models.
In a paper entitled ”Corrosion Management in the 20th Century” published in 1995 by the British Corrosion Journal,1 the authors Trethewey and Roberge motivate innovation in the use of smart machine learning systems for corrosion management with the following statement:
”There are growing signs that, if the present levels of economic growth are unsustainable in the next century, new laws will require ever more economic and efficient use of materials and energy.”
The article goes on to highlight how corrosion management involves the intersection of human reliability with corrosion control solutions, and how advances in knowledge elicitation and machine learning/data-driven approaches will help reduce the incidence of corrosion failures due to ”human factors.” In this way, improved corrosion management will be contributing to materials efficiency and preservation of assets in a future where sustainability may become a more critical issue.