CMSC 2018 Presentation - CMM Automation and Optimization using Model Based Definition

Publication Details

Abstract

CMM programming is currently a tedious, time consuming, and error prone process which requires the active involvement of a highly skilled quality engineer. The GD&T product requirements need to be manually transcribed into the CMM programming software from the product drawing or model. This takes an enormous amount of time, and involves a high risk of transcription or interpretation errors. A further risk is that the quality of the CMM program created is heavily reliant on the skill, knowledge, and expertise of the CMM operator. The time spent and risks involved in this process add up to enormous unnecessary cost to manufacturing industry.
By leveraging a direct machine-to-machine interface between CAD and CMM software, this process can be automated and optimized. Using semantic PMI in the CAD model, CMM measurement uncertainty simulation, and state-of-the-art CMM programming tools, it is possible to highly automate these tasks. This automation lowers costs by significantly reducing time spent creating CMM programs, and eliminating some of the risks identified previously. It also frees up the skilled engineer to add value to their organization in ways other than data transcription. The results would be a CMM program, created with minimal user assistance, which is optimized according to measurement uncertainty requirements and corporate best practices. Overall benefits are: less time spent, less reliance on unpredictable human-in-the-loop, and greater reliance on encoded organizational processes. 
The time for this technology is now. This presentation will show how, using commercial, off-the-shelf software tools, highly automated CMM workflows are ready for industry. Pilot projects at large manufacturing enterprises will be explained, including comparisons of traditional workflows to this MBE workflow, and estimated cost savings due to process time reduction.