Research Directions for Merging Geospatial Technologies with Smart Manufacturing Systems
Johannes Schulz, William Z. Bernstein, Rafael Radkowski
As industrial internet of things (IoT) concepts and technologies continue to be retro-fitted onto existing manufacturing infrastructure, geospatial considerations, such as asset localization, registration, and tracking, become more critical to ensure better flexibility, capability understanding, and agility. In response, there have been efforts to merge state-of-the-art Geographical Information Systems and Smart Manufacturing Systems in production environments. However, these solutions are often product- or platform-centric and proprietary, such as (i) computer vision technologies embedded on an automatic guided vehicle and (ii) point cloud translation post 3D scan within a Product Lifecycle Management solution. Standards exist for various steps and functions within these computer-supported pipelines, but little work exists that test their scalability and robustness. This paper aims to critically evaluate the current state of the integration of Smart Manufacturing Systems and Geographic Information Science \& Technology, and identifies the potential overlap between the two fields and lists opportunities for a further collaboration. The methodological approach of this paper is two fold: a) we utilize a survey with experts in both fields and b) an algorithmic literature meta-analysis. The results reveal that both fields have concepts that could mutually support each other, and that Smart Manufacturing could benefit from Geographic Information technologies - especially from a standardized representation of indoor environments. The results show a great number of potential overlaps and thus presents a preliminary roadmap to foster the integration.
, Bernstein, W.
and Radkowski, R.
Research Directions for Merging Geospatial Technologies with Smart Manufacturing Systems, Smart and Sustainable Manufacturing Systems, [online], https://doi.org/10.1520/SSMS20220004, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=933060
(Accessed May 30, 2023)