£102.47

The Digital Transformation of Product Formulation: Concepts, Challenges, and Applications for Accelerated Innovation

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Last 282 days • 282 data points (No recent data available)

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£102.47 £82.20 £86.62 £91.04 £95.47 £99.89 £104.31 01 April 2025 10 June 2025 19 August 2025 28 October 2025 07 January 2026

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Price distribution over 282 days • 9 price levels

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9 days 30 days 29 days 18 days 6 days 18 days 7 days 4 days 161 days · current 0 40 81 121 161 £84 £86 £87 £88 £89 £90 £93 £97 £102 Days at Price

Price Analysis

Most common price: £102 (161 days, 57.1%)

Price range: £84 - £102

Price levels: 9 different prices over 282 days

Description

In competitive manufacturing industries, organizations embrace product development as a continuous investment strategy since both market share and profit margin stand to benefit. Formulating new or improved products has traditionally involved lengthy and expensive experimentation in laboratory or pilot plant settings. However, recent advancements in areas from data acquisition to analytics are synergizing to transform workflows and increase the pace of research and innovation. The Digital Transformation of Product Formulation offers practical guidance on how to implement data-driven, accelerated product development through concepts, challenges, and applications. In this book, you will read a variety of industrial, academic, and consulting perspectives on how to go about transforming your materials product design from a twentieth-century art to a twenty-first-century science. Presents a futuristic vision for digitally enabled product development, the role of data and predictive modeling, and how to avoid project pitfalls to maximize probability of success Discusses data-driven materials design issues and solutions applicable to a variety of industries, including chemicals, polymers, pharmaceuticals, oil and gas, and food and beverages Addresses common characteristics of experimental datasets, challenges in using this data for predictive modeling, and effective strategies for enhancing a dataset with advanced formulation information and ingredient characterization Covers a wide variety of approaches to developing predictive models on formulation data, including multivariate analysis and machine learning methods Discusses formulation optimization and inverse design as natural extensions to predictive modeling for materials discovery and manufacturing design space definition Features case studies and special topics, including AI-guided retrosynthesis, real-time statistical process monitoring, developing multivariate specifications regions for raw material quality properties, and enabling a digital-savvy and analytics-literate workforce This book provides students and professionals from engineering and science disciplines with practical know-how in data-driven product development in the context of chemical products across the entire modeling lifecycle.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
14 August 2024
Listed Since
14 February 2024

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