Decision making for additive manufacturing in sustainable defense acquisition/
WATERLOO Tsutsui
Decision making for additive manufacturing in sustainable defense acquisition/ Waterloo, Tsuitsui, Qian (Alex) Shi, Ian Walter [et.al.] - 2023
The research team developed a model-based acquisition decision support tool (i.e. the decision engine) for additive manufacturing materials and technologies selection. In order to develop the framework, the team focused on a use case involving aircraft single-component (i.e., an aileron bellcrank ) design and manufacturing. In the use case, the team identified the key decision factors in considering additive manufacturing alternatives against traditional manufacturing methods. Preliminary findings indicate that the decision engine provides the users with algorithmic view of the variables to make an optimized decision regarding where and how additive manufacturing can have the most impact. To this end, the team designed the user interface in such a way that the decision engine visualizes the relative performance of each alternative considered , thereby assisting a stakeholder in the decision-making process. More specifically, the decision engine provides quantitative information about the usefulness of each alternative relative to others. As a result, the decisions engine supports stakeholders in making informed decisions on additive manufacturing opportunities throughout the mission engineering and sustainment defense acquisition.
DECISION MAKING PROCESS
Decision making for additive manufacturing in sustainable defense acquisition/ Waterloo, Tsuitsui, Qian (Alex) Shi, Ian Walter [et.al.] - 2023
The research team developed a model-based acquisition decision support tool (i.e. the decision engine) for additive manufacturing materials and technologies selection. In order to develop the framework, the team focused on a use case involving aircraft single-component (i.e., an aileron bellcrank ) design and manufacturing. In the use case, the team identified the key decision factors in considering additive manufacturing alternatives against traditional manufacturing methods. Preliminary findings indicate that the decision engine provides the users with algorithmic view of the variables to make an optimized decision regarding where and how additive manufacturing can have the most impact. To this end, the team designed the user interface in such a way that the decision engine visualizes the relative performance of each alternative considered , thereby assisting a stakeholder in the decision-making process. More specifically, the decision engine provides quantitative information about the usefulness of each alternative relative to others. As a result, the decisions engine supports stakeholders in making informed decisions on additive manufacturing opportunities throughout the mission engineering and sustainment defense acquisition.
DECISION MAKING PROCESS