Investigating Human Expertise in Manufacturing to Enhance Knowledge Preservation and Transfer Practices

In the US, the machining industry is a vital part of the economy, employing over 290,000 skilled machinists and over 89,000 mechanical engineers. Whilst employment figures for engineers in this crucial sector has been fairly steady, a rapid decline in machinist workforce has been observed in the last decade, along with retirement of aging expert machinists and engineers, creating workforce shortages and loss of valuable manufacturing knowledge inherent to those highly skilled and experienced individuals. As engineering design and manufacturing knowledge are closely intertwined, so is the knowledge pertaining to practical aspects of machining and design of components that are optimal in terms of manufacturing. Effective preservation of this valuable knowledge and effectively addressing the issues associated with shrinking and aging workforces necessitates exploring new approaches to knowledge collection, transfers and use of novel instructional methods in machinist and engineering workforce development. In this work, novel approaches to investigating, describing and preserving human knowledge in machinist and engineering design occupations were proposed and deployed. A case study and a comparison study were conducted with the use of a proprietary research method to observe trainee actions, behavior and obtain a deeper understanding of their learning processes. Results have shown high applicability of intensive hands-on training procedures on conventional machine tools in machinist workforce development, signifying the importance of training in immersive workplace environments and learning by iteratively performing hands-on tasks. Studies concerning human capabilities for intuitive evaluation of component design manufacturability and the role of experiential knowledge in Design for Manufacturing have shown the importance of practical experience and hands-on background in education of design and manufacturing engineers. An original knowledge elicitation method was conceptualized, proposed and employed in human subjects trials, showing high accuracy and good applicability. Results of performed research have been utilized to develop a software solution for education in manufacturing workforce development, providing a practical application of collected results for use in engineering education.