Expert System Based on Integrated Fuzzy AHP for Automatic Cutting Tool Selection
Source abstract
Abstract
Cutting tool selection plays an important role in achieving reliable quality and high productivity work, and for controlling the total cost of manufacturing. However, it is complicated for process planners to choose the optimal cutting tool when faced with the choice of multiple cutting tools, multiple conflict criteria, and uncertain information. This paper presents an effective method for automatically selecting a cutting tool based on the machining feature characteristics. The optimal cutting tool type is first selected using a proposed multicriteria decision-making method with integrated fuzzy analytical hierarchy process (AHP). The inputs of this process are the feature dimensions, workpiece stability, feature quality, specific machining type, and tool access direction, which determine the cutting tool type priority after evaluating many criteria, such as the material removal capacity, tool cost, power requirement, and flexibility. Expert judgments on the criteria or attributes are collected to determine their weights. The cutting tool types are ranked in ascending order by priority. Then, the rule-based method is applied to determine other specific characteristics of the cutting tool. Cutting tool data are collected from world-leading cutting tool manufacturer, Sandvik, among others. An expert system is established, and an example is given to describe the method and its effectiveness.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Multi-Criteria Decision Making · Manufacturing Process and Optimization · Industrial Vision Systems and Defect Detection
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Hanoi University of Science and Technology, Hanoi 10000, Vietnam
Shibaura Institute of Technology, Tokyo 135-8548, Japan
References (20)
Show source-provided references
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