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Robust Quality: Powerful Integration of Data Science and Process Engineering

Historically, the term quality was used to measure performance in the context of products, processes and systems. With rapid growth in data;

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Robust Quality

Historically, the term quality was used to measure performance in the context of products, processes and systems. With rapid growth in data;

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Stream of Variation Modeling and Analysis for Multistage Manufacturing Processes

assembles advanced SoV-related topics and the integration of quality and reliability. Introducing a powerful and industry-proven method, this;

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Data Structure and Software Engineering

. This volume presents new approaches and methods to knowledge sharing, brain mapping, data integration, and data storage. The author describes;

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Data Structure and Software Engineering

volume presents new approaches and methods to knowledge sharing, brain mapping, data integration, and data storage. The author describes how to;

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Statistical Robust Design

A UNIQUELY PRACTICAL APPROACH TO ROBUST DESIGN FROM A STATISTICAL AND ENGINEERING PERSPECTIVE Variation in environment, usage conditions;

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Productive and Efficient Data Science with Python

measure the memory footprint and execution speed of machine learning models, quality test a data science pipelines, and modularizing a data;

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Quality of Information and Communications Technology

This book constitutes the refereed proceedings of the 12th International Conference on the Quality of Information and Communications;

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Engineering Methods For Robust Product Design

optimizing cost, quality, and cycle time. It even discusses the relationship of robust design to such other quality processes as Quality Function;

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Getting Data Science Done

, organizational change and integration with IT and engineering. Getting Data Science Done outlines the essential stages in running successful data;

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Optimisation of Manufacturing Processes

variables that determine product quality. Robust design was developed in Japan by G. Taguchi in the early 1950s and its widespread use throughout;

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Towards Sustainable Chemical Processes

economy, energy planning, process integration and sustainability engineering.All chapters throughout answered two fundamental;

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Green Computing and Predictive Analytics for Healthcare

Big data analytics and clustering Machine learning techniques for sudden cardiac death prediction Robust brain tissue;

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Process Integration Approaches to Planning Carbon Management Networks

sets of data. This book is ideal for academic researchers and graduate students interested in carbon-constrained energy planning models and;

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Process Integration Approaches to Planning Carbon Management Networks

sets of data. This book is ideal for academic researchers and graduate students interested in carbon-constrained energy planning models and;

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Advanced Information Systems Engineering

information management; requirements elicitation and management; enterprise data management; model conceptualisation and evolution; process mining;

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Productive and Efficient Data Science with Python

how to measure the memory footprint and execution speed of machine learning models, quality test a data science pipelines, and modularizing a;

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Data-Driven Engineering Design

-stage design. Based on novel combinations of standing design methodology and the emerging data science, the book presents a collection;

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Uncertainty Modelling and Quality Control for Spatial Data

aspects of spatial data quality control. From multidimensional and multi-scale data integration to uncertainties in spatial data mining, this book;

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Uncertainty Modelling and Quality Control for Spatial Data

aspects of spatial data quality control. From multidimensional and multi-scale data integration to uncertainties in spatial data mining, this book;

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Statistical Process Monitoring and Optimization

building, and process optimization. The book covers a range of statistical methods and emphasizes practical applications of quality control systems;

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Quality Management with SAP ERP

essential master data. Once you've covered the basics, you'll learn how QM works with other components in the supply chain, and learn how to use;

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Agile Data Warehousing For The Enterpris

expensive data-conversion programs. Quality assurance advances with not only a stereoscopic top-down and bottom-up planning method, but;

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Taguchi's Quality Engineering Handbook

This book is a great demonstration of this powerful approach and how it can make a meaningful difference in any type of business. It takes;

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Robust Engineering

to any online entitlements included with the product. Powerful and elegantly simple.Achieve higher quality...lower costs...faster;

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Engineering for Business

the more robust quantitative tools and techniques used to facilitate decision-making in business and uses case studies to illustrate their;

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Scala for Data Science

, manipulating, processing, and visualizing data in Scala. Packed with real-world examples and interesting data sets, this book will teach you to ingest;

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