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Introduction to quality engineering : designing quality into products and processes

玄一 田口
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The article was published on 1986-01-01 and is currently open access. It has received 765 citations till now. The article focuses on the topics: Quality assurance & System of systems engineering.

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Robust parameter design in embedded high-variability production processes: an alternative approach to mitigating sources of variability

TL;DR: In this paper, an alternative method for dealing with high process variability is proposed, using the coefficient of variation to identify influential sources of variability between design points, and the proposer proposes an alternative approach to deal with high variability.

Managing quality inside a high-technology project organization

Tauno Jokinen
TL;DR: In this article, the authors address the deployment of total quality management (TQM) principles in a high-technology new product development organization and present a framework supporting the selection of TQM implementation objectives and the planning of a strategy for organisational learning.
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Reliability-Based Optimum Tolerance Design for Industrial Electromagnetic Devices

TL;DR: A new tolerance design named as reliability-based optimum tolerance design is formulated and performed to guarantee the high reliability of the products while maximizing manufacturing tolerances.
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A fuzzy genetic algorithm for the discovery of process parameter settings using knowledge representation

TL;DR: The proposed fuzzy genetic algorithm (Fuzzy-GA) approach is equipped with the ability to take advantage of assessing the loss which is caused by discrepancy with a process target, thereby enabling the identification of the best set of process parameters.
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Tuning the Parameters of a Convolutional Artificial Neural Network by Using Covering Arrays

TL;DR: This work study the use of mixed-level covering arrays to design experiments that help to find the best combinations of parameters and took advantage of the flexibility of the open source software library for machine learning TensorFlow.
References
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Mathematical Statistics with Applications

TL;DR: Step-by-step procedure to solve real problems, making the topic more accessible, and exercises blend theory and modern applications.
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An Instrument for Measuring the Key Factors of Successin Software Process Improvement

TL;DR: The main result is an instrument for measuring the key factors of success in SPI based on data collected from 120 software organizations and the measures were found to have satisfactory psychometric properties.
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Creating Effective Online Customer Experiences

TL;DR: Across 16 experiments, this research investigates how 13 unique design elements shape four dimensions of the online customer experience and thus influence purchase and provides managers with clear strategic guidance on how to build effective web pages.
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A treatise on order in engineering design research

TL;DR: A framework of reasoning was constructed, including source, channel, and sink categories of knowledge and research of engineering design, respectively, which enables a grounded argumentation about the order ofengineering design research, as well as about the articulation of the engineering design knowledge.
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Bayesian Optimization for Adaptive Experimental Design: A Review

TL;DR: This review considers the application of Bayesian optimisation to experimental design, in comparison to existing Design of Experiments (DOE) methods, and surveys for a range of core issues in experimental design.