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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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An exact management method for demand driven, industrial operations

Janne Puikko
TL;DR: In this paper, an operational target setting is based on linear goal programming, streamlined demand driven material flow and specified operating factors according to this study, Forrester effect diagnostics and replenishment models.
Proceedings ArticleDOI

Competitive coevolutionary algorithm for robust multi-objective optimization: The worst case minimization

TL;DR: A coevolutionary approach for robust MOO is introduced, without incorporating robustness measures neither in the objective function nor in the constraints, and two populations compete in the environment, one representing solutions and minimizing the objectives, another representing uncertainties and maximizing the objectives in a worst case scenario.
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A new look at factors influencing total quality management failure: work process control or workforce control?

TL;DR: In this paper, the authors draw on multi-case data to suggest that TQM effectiveness can be viewed as a direct function of the controlling mechanisms that senior managers created prior to the implementation.
References
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Mathematical Statistics with Applications

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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.