Collaborative Research: Reducing the Burden of Global Materials Manufacture: Enabling Increased Use of Secondary and Renewable Materials in Production Planning

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1133286 Kirchain/1133422 GaustadThis research will produce a systematic mapping of relative performance of deterministic and several forms of uncertainty-aware stochastic batch planning models for a range of production contexts. Specific contexts to be explored include at least three forms of batch quality performance functions (linear, power-law, and logarithmic) and four distributional forms of raw material (RM) quality (Lognormal, Max Extrema, Gamma, or Student's t). Additionally, this research will provide both analytical and quantitative case analysis that supports the economic and resource efficiency value of diversification of interdependence within industrial ecosystems. For three planned industrial case analyses, this research will quantify the distributional nature of RM quality and the current and potential ability to utilize secondary and renewable raw materials (SRRMs) while examining the impact of the number of raw materials attributes. The educational component of this research seeks to develop methods and case studies to incorporate sustainability into engineering education. These course materials will be integrated into graduate and undergraduate courses on industrial ecology and sustainable firm strategy taught by the PIs at MIT and RIT. The ultimate goal is to provide students with the knowledge-base to improve their engineering decisions by understanding how their decisions will impact society. The outcomes of these efforts will be shared with the broader academic community through forums such as the Center for Sustainable Production at RIT and MIT?s OpenCourseWare, a free and accessible web-based publication of much of MIT?s course content. The post-docs employed within this project will receive mentoring through a structured program to improve teaching, presentation, publication, and fund-raising skills. The broader impact of this work stems from the collaborations it necessitates between industry and academia; this collaboration enables real-world implementation tests to ensure that the research leads to actionable methods not just abstract concepts. The outcomes of the work will be widely disseminated to audiences outside of traditional academic communities because of the industrial partnerships employed in the research. Overall, the outcomes of the work are targeted to benefit society by developing tools that seek to reduce the environmental impact of the process industries and create sustainable material systems.1133422 (Gaustad). This research will produce a systematic mapping of relative performance of deterministic and several forms of uncertainty-aware stochastic batch planning models for a range of production contexts. Specific contexts to be explored include at least three forms of batch qualityperformance functions (linear, power-law, and logarithmic) and four distributional forms of raw material (RM) quality (Lognormal, Max Extrema, Gamma, or Student's t). Additionally, this research will provide both analytical and quantitative case analysis that supports the economic and resource efficiency value of diversification of interdependence within industrial ecosystems. For three planned industrial case analyses, this research will quantify the distributional nature of RM quality and the current and potential ability to utilize secondary and renewable raw materials (SRRMs) while examining the impact of the number of raw materials attributes. The educational component of this research seeks to develop methods and case studies to incorporate sustainability into engineering education. These course materials will be integrated into graduate and undergraduate courses on industrial ecology and sustainable firm strategy taught by the PIs at MIT and RIT. The ultimate goal is to provide students with the knowledge-base to improve their engineering decisions by understanding how their decisions will impact society. The outcomes of these efforts will be shared with the broader academic community through forums such as the Center for Sustainable Production at RIT and MIT?s OpenCourseWare, a free and accessible web-based publication of much of MIT?s course content. The post-docs employed within this project will receive mentoring through a structured program to improve teaching, presentation, publication, and fund-raising skills. The broader impact of this work stems from the collaborations it necessitates between industry and academia; this collaboration enables real-world implementation tests to ensure that the research leads to actionable methods not just abstract concepts. The outcomes of the work will be widely disseminated to audiences outside of traditional academic communities because of the industrial partnerships employed in the research. Overall, the outcomes of the work are targeted to benefit society by developing tools that seek to reduce the environmental impact of the process industries and create sustainable material systems.