Optimization of workflow in 3D laser scanning operations

Abstract

This thesis explores the optimization of 3D laser scan data processing by comparing single-instance and multi-instance software workflows in an industrial context. The study was conducted at SolidComp Oy, a company specializing in 3D scanning services. As the demand for faster and more scalable processing increases, the aim was to evaluate whether a multi-instance approach could significantly reduce processing time without the need for additional hardware or software investments. An experimental research design was used, applying a deductive, quantitative methodology. The same scanning project was processed on two different workstations using both single and multiple software instances. Time measurements for various processing stages were recorded and analyzed to determine efficiency gains. The results showed that multi-instance processing led to a 38.7% reduction in processing time on the first workstation and a 48.7% reduction on the second, more powerful workstation. In addition to time savings, the study demonstrated improved scalability, elimination of workflow bottlenecks, and more efficient use of existing resources. These findings support the adoption of a multi-instance workflow as a cost-effective and practical solution for handling large-scale projects. Moreover, the research contributes to the field of digital workflow optimization and offers practical recommendations for industries seeking to enhance productivity using existing technological infrastructure.