Abstract
Whether it is important components of a machine tool itself or various important components processed by the machine tool, many vital quality characteristics mostly belong to the smaller-the-better type. When the process quality levels of these quality characteristics do not attain to the criteria, friction loss may increase during the machine operation, affecting not only the process precision and accuracy but also the lifetime of the product. Therefore, this study applied a smaller-the-better six-sigma quality index simultaneously demonstrating process quality level and process yield. Besides, in coping with statistical process control data, a one-tail confidence-interval-based fuzzy testing method was developed to evaluate process quality. Because this approach is built on the basis of confidence intervals, it can reduce the possibility of misjudgment resulting from sampling errors as well as integrate past experience to enhance the accuracy and precision of the assessment, and then it can grasp the timeliness of improvement.
Highlights
Many studies on process technology and management have indicated that machine tools are assembled from a large number of components mainly used to process a variety of machinery equipment.Machine tools play a critical role in the entire machinery manufacturing industry, so that they are called the “Mother of Machinery” [1,2]
In an attempt to combine the verification of process capability with the accumulated professional knowledge of a team, the confidence-interval-based fuzzy testing method can be applied to evaluate the quality level during the manufacturing process [7,17,18,26]
Chen [29], the fuzzy testing method suggested by this study seems to be more reasonable than statistical inference
Summary
Many studies on process technology and management have indicated that machine tools are assembled from a large number of components mainly used to process a variety of machinery equipment. The six-sigma quality improvement process contains significant implications for industry and is widely applied to manufacturing, aiming to enhance product quality levels as well as lower production defect rates [13,14,15,16]. Both Process Capability Indices and six-sigma quality levels are two significant tools in industry. In an attempt to combine the verification of process capability with the accumulated professional knowledge of a team, the confidence-interval-based fuzzy testing method can be applied to evaluate the quality level during the manufacturing process [7,17,18,26].
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