SBIR-STTR Award

The objective of this work is to develop a data-driven analytical framework for assessing the current manufacturing and maintenance systems and propose a roadmap for moving towards an RMS system well aligned with maintenance activities customized to the Air Force ALC environment. Because of the importance of identifying the part families in the design of an RMS system, we propose a systematic approach in identifying part families with respect to aircraft maintenance procedures, and connecting each part family to the maintenance procedure and required resources. The objective is to develop a systematic model to represent the aircraft maintenance system, including critical aircraft products (major system, subsystem, and components), maintenance procedures, machines required for each procedure, and sequences and cycle time needed. The model will be used to represent the aircraft maintenance system, to identify the opportunities to implement the RMS, and to evaluate the improvements and effectiveness of an RMS strategy if it is implemented.

This technology is a digital twin of a manufacturing process with 3D virtual manufacturing environment and integrated manufacturing process simulation. This tool’s data driven models can be used as a platform for a model based smart factory, a key building block in its digital transformation journey, and enable rapid reconfiguration of manufacturing and overhaul lines to adjust to changing requirements and conditions. The solution has been developed with Tecnomatix Plant Simulation, which is compatible with Air Force’s chosen Product Lifecycle Management (PLM) software tools from Siemens. As the Air Force implements and adopts the Siemens PLM tools, this solution can add capabilities by integrating further with Air Force digital engineering systems and data, leveraging additional data and digital engineering assets. Use cases for the technology include: Performance improvement experimentation to understand first and second order effects of process changes and quantitative measurement of predicted outcomes enabling data driven business case analysis for process improvement or capital expenditure initiatives. Benchmarking process statistical process performance against model predictions Virtual commissioning of new machines and equipment prior to arrival and installation Virtual training (AR/VR) on new and existing machines Communication – creating end-to-end visibility of a manufacturing enterprise The outcomes of the phase II research created a significant amount of digital assets of the 402d CMXG manufacturing enterprise, focused on the C-130 propeller blade overhaul process.