Job Summary
Digital Enterprise Center (School of Engineering Technology) Post-Doctoral Research Assistant Position
This position will extend previous work in the areas of software development, product and process modeling, and materials development to support data interoperability and persistence in a manufacturing environment. For the last 10 years, Drs. Hartman and Sangid have been developing a methodology and a toolset to support the manufacturing sector’s transition away from technical drawings towards the use of the model-based definition methodology in the design and production of products. Following is a citation for one of the more recent developments with this model framework:
Gopalakrishnan, S., Hartman, N.W. and Sangid, M.D., 2020. Model-based feature information network (MFIN): A digital twin framework to integrate location-specific material behavior within component design, manufacturing, and performance analysis. Integrating Materials and Manufacturing Innovation, 9, pp.394-409.
One of the goals of this work is to develop additional functionality within the existing code base to support the integration of specifications, materials and process definitions, and contextual data from product production and product use in specific phases of the lifecycle. A second goal of this work is to package the code base into a more formalized software tool.
Research areas of particular interest could include:
- Developing descriptive data models and ontologies that enable the integration between the software utility and commercial PLM systems,
- Encouraging the emergence of the digital twin and digital thread as frameworks for deploying the software tool,
- Integration and use of current ASME and ISO technical product data standards into the existing software code base to augment existing integrations, and
- Understanding the cost opportunities of increased data interoperability (or the challenges due to the lack thereof).
Continued job summary
The postdoctoral position will actively work on software development and integration with other commercial software codes, application and extension of existing ASME and ISO model standards, and the ongoing development and assessment of digital twin methodologies. The fellow’s project-related responsibilities will also include gathering data from industry and government organizations to assess their needs and challenges around data interoperability; identifying, implementing, and evaluating digital manufacturing and product lifecycle management (PLM) technologies and methods; collecting and analyzing data as needed, writing articles and reports, and presenting findings at conferences and team meetings.
Qualifications
Applications are encouraged from a variety of fields, including technology, engineering, computer science, information technology, or a closely related field. Applicants must have earned a doctorate in a relevant technical field (e.g., technology, engineering, computer science, or IT) with a demonstrated interest in research, technology development and implementation, manufacturing enterprises, or the effects of digitalization on work. Applicants must have completed all the requirements for the doctorate no later than August 2024, or have received their degree within the last three years. Industrial manufacturing experience is highly valued. Specific technology expertise should include as many of the following as possible:
- Development of software applications (e.g., C++, Python, JavaScript, XML, various data schemas, etc.)
- Geometry creation and scripting within CAD tools (e.g., CATIA, NX, Creo, Solidworks, etc.)
- Configuration of data models, xBOMs, and workflows within PDM /PLM tools (e.g., TeamCenter, ENOVIA, Windchill, Aras, various data standards, etc.)
- xBOM management and workflows within ERP tools (e.g., SAP, Oracle, etc.)
- Process definition and job tasks within MES tools (e.g., TeamCenter Manufacturing, DELMIA, Solumina, etc.)
- CAM tools (e.g., MasterCAM, Gibbs, NX CAM, etc.)
- Programing of PLCs and machine connectivity (e.g., MT Connect, ROS, etc.)
- Knowledge of CNC machining, additive manufacturing, metrology equipment (e.g., G-code, M-code, etc.)
- Cloud computing environments (e.g., MS Azure, AWS, Google Cloud, etc.)
Continued qualifications
Applicants must have technical expertise in an engineering design, manufacturing, IT, software development, or hardware development domain; proposal development skills, and motivation to take initiative to ensure the success of a project. Applicants must be able to develop software applications using formal programming/scripting techniques, and follow a software development process (e.g., waterfall, Agile, spiral, etc.). Applicants must also be able to handle export-controlled data. Preference will be given to candidates who exhibit evidence of research interest and motivation, strong communication skills and professional demeanor, and an interest in the development of technology to enable advanced manufacturing. Applicants must be willing to travel for a few days at a time.