Abstract
In this paper, we describe the needs and specific requirements of the aerospace industry in the field of metal machining; specifically, the concept of an edge-computing-based production supervision system for the aerospace industry using a tool and cutting process condition monitoring system. The new concept was developed based on experience gained during the implementation of research projects in Poland’s Aviation Valley at aerospace plants such as Pratt & Whitney and Lockheed Martin. Commercial tool condition monitoring (TCM) and production monitoring systems do not effectively meet the requirements and specificity of the aerospace industry. The main objective of the system is real-time diagnostics and sharing of data, knowledge, and system configurations among technologists, line bosses, machine tool operators, and quality control. The concept presented in this paper is a special tool condition monitoring system comprising a three-stage (natural wear, accelerated wear, and catastrophic tool failure) set of diagnostic algorithms designed for short-run machining and aimed at protecting the workpiece from damage by a damaged or worn tool.
Highlights
Rapid digitization is changing societies around the world, including how we communicate, what we buy, how we live, and how the production system works
The concept of a production supervision system based on edge-computing technology, as presented in this paper, and using a three-level algorithm of the tool estimating gradual tool wear (GTW) and detecting Accelerated tool wear (ATW) and catastrophic tool failure (CTF), would avoid production shortages and increase productivity while maintaining the required production quality
It is tailored to the requirements of the aviation industry, with a focus on minimizing defects in machining of expensive parts made with hard-to-machine materials and high precision requirements, as well as to the specificity of aviation production in which there are small series production and limited operations per one tool life
Summary
Rapid digitization is changing societies around the world, including how we communicate, what we buy, how we live, and how the production system works. Machine tool operators have been known to stop using these systems precisely because of the complicated operation and, in this case, most academic solutions are based on custom solutions and not optimized for ease of use; often user interfaces are not developed, only signal processing software These academic strategies are based on advanced signal processing methods, and often on artificial intelligence methods, which require the selection of many different parameters for their operation. The TCM system transmits to the process engineer diagnostic signals, work progress reports, and results of machining process supervision on a given cell (e.g., date/time of execution of individual operations, operator’s name, tool wear values after execution of individual operations, and information on occurrence of emergency situations (collisions and catastrophic tool failures). The TCM system can send suggestions to quality control about measuremen7tosfa1t3 a site, such as when there is high tool wear
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