journal article·2020-09-07Open access

Development of F-N-C-O Taguchi Method for Robust Measurement System Using a Case Study of T-Peel Test on Adhesion Strength

Rozzeta Dolah, Mohamad Zaki Hassan, Santhana Krishnan, Faizir Ramlie, Mohd Fadhil Md Din, Khairur Rijal Jamaludin

Applied Sciences· Volume 10· Issue 18

Abstract

A robust measurement system in the Taguchi Method as a testing method should be explained from the beginning of an experimental design until the application of the optimum condition. Measurement has always been described either by discussing the measurement concepts theoretically or demonstrating a case study on how the data measurement is being done practically. The distance between theory and practical case study that connects the test method used for measurement is always missing. In this paper, a case of T-peel test on strength measurement is used to reflect the robust measurement system, which includes the theory of experimental design together with methods to achieve the optimum condition. Seven control factors, two noise factors with one signal factor are used with orthogonal array L18. Not only the experiment results, but methodology on choosing the control, noise, and signal factors are described intensively. Therefore, the aims are to provide the procedure on evaluating optimum conditions, to analyze variability and optimization of T-peel test when measuring the strength, and to establish a mainstream flow to achieve high-quality experimental design for a robust measurement system. As a result, a robust measurement system that includes variation elimination is developed, which consists of four elements—F (function), N (noise), C (Control), and O (Optimization). The elements of the F-N-C-O system are connected to one another by the Plan-Do-Study-Act; P-D-S-A cycle. The results affect the existing measurement system by enlightening the black box of parameter design behind optimization results in Taguchi Method. Thus, the measurement is more convergent and obtain higher degree of confidence in parameter design.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Industrial Vision Systems and Defect Detection · Manufacturing Process and Optimization · Advanced machining processes and optimization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Engineering, Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, UTM KL, Jalan Sultan Yahya Petra, Kuala Lumpur 54100, Malaysia

Center of Environmental Sustainability and Water Security (IPASA), Research Institute of Sustainable Environment (RISE), Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia

Funding

UNIVERSITI TEKNOLOGI MALAYSIA

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