Abstract
Additive manufacturing’s (AM’s) transition to an accepted production technology has led to increasing demands on data requirements. Many of these advances have been made possible by an increase in in-situ sensing and ex-situ measurement devices. These new devices are rapidly increasing the volume, variety, and value of AM data. The number of software tools used to measure, model, simulate, and manage AM material, part, and process is increasing to take advantage of emerging customer needs and market opportunities. However, the capabilities and accessibility of these tools, which are being used by both practitioners and researchers, vary greatly. Software tools for AM users should be able to handle ex-situ needs as well as address emerging in-situ requirements, including 1) process the different types of measured data, 2) understand defect formation, geometric variation, surface roughness, and 3) run fast enough for the layer-by-layer, scanning process. To better understand both the current capabilities and future needs, this paper provides an AM product-lifecycle landscape of software tools. The landscape includes tools for product design, design analysis, process planning, process monitoring, process modeling, process simulation, and production management. A preliminary set of functional requirements are identified, and requirements that if supported will further data analytics capabilities in AM. Furthermore, this paper identifies opportunities to develop new data-analytics tools that can improve product quality and reduce production time.
Research on 3D Visualization Design of Industrial Production Management Software
