In-Situ Measurement and Dimensional Error Modeling: A Case Study in a Machine Tool Manufacturer

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. Based on data-driven strategies, the present study aimed to improve the dimensional accuracy of clamp levers and grippers manufactured by milling. A case study was stated on the multinational machine tool manufacturer responsible to produce 42 CrMo4 steel clamp levers and grippers. 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 modeling a compensation approach for this phenomenon during machining, according to the number of manufactured components within the tool life. 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.