Eventos Anais de eventos
COBEF 2023
12th Brazilian Congress on Manufacturing Engineering
In-situ measurement and dimensional error modeling: a case study in a machine tool manufacturer
Submission Author:
Amanda Rossi de Oliveira , SP
Co-Authors:
Amanda Rossi de Oliveira, Thiago Cannabrava, Thiago Silva, Erik del Conte
Presenter: Amanda Rossi de Oliveira
doi://10.26678/ABCM.COBEF2023.COF23-0026
Abstract
Quality assurance in manufacturing processes is an issue that will require new strategies to follow the evolution guided by Industry 4.0. Thus, considering the data relevance for this new revolution, it is crucial to understand how inspection and measurement techniques can make the most of the process's information to make quality more manageable and avoid rework. In this sense, based on data-driven strategies, the present study aimed to improve the dimensional accuracy of clamp levers and grippers manufactured by milling. To achieve this purpose, a case study was stated on the multinational machine tool manufacturer responsible for 42 CrMo4 steel clamp levers and grippers production. Starting with a root causes mapping, it was possible to identify critical internal operations for dimensional accuracy variations in the products that require some enhancements. Hence, machined clamp levers and grippers' critical dimensions measured with a coordinate measuring machine (CMM) used in the quality department were compared to those measured with an in-situ measurement probe to improve the online equipment accuracy. Regarding the systematic error evaluation for two critical dimensions in the products, this approach found about 0.019 mm and 0.009 mm absolute corrections to enhance the measurement probe method. Also, cutting tool wear experiments contributed to identifying tool wear values higher than the maximum tolerances near the tool life limit. As a result, a proposed tool wear modeling supported a compensation approach for this phenomenon during machining, according to the number of manufactured components within the tool life. It defined ways to use manufacturing operations data, which were experimentally and statistically analyzed, allowing new opportunities to meet the tight tolerances of the clamp levers and grippers, and facilitating the assembling stage, considering possible adjustments in the machining programming. Finally, the proposed human-based data-driven methodologies contribute to defining the first step of measurement and inspection evolutions through the 4.0 Industry structure in an entire manufacturing system.
Keywords
Metrology, machining, in-situ measurement, error modeling, Dimensional Accuracy, tool wear
