A Perspective on Advanced Wood Manufacturing: A Decision-Centric Framework for Future Research and Education

For over a century, wood manufacturing has been organized around understanding the material and process and optimizing the product. It established a globally successful industry and enabled efficient production of traditional and engineered wood products. This manufacturing practice is now being challenged by the complexity of resource variability, product diversification, mass customization, and rapid technology integration. This perspective proposes Advanced Wood Manufacturing as a decision-centric smart manufacturing ecosystem that integrates Resource Intelligence, Manufacturing Intelligence, Product Intelligence, and System Intelligence through a unifying Decision Intelligence framework to convert variability into high-value manufacturing decisions. We argue that natural resource variability, while requiring control where necessary for reliable production, can also provide decision-relevant information for adaptive manufacturing and value creation. The product space of wood manufacturing extends far beyond lumber and panels into emerging functional products for energy storage, flexible electronics, and biomedical applications, enabled by artificial intelligence, sensing and digitalization, robotics, computational design, and additive manufacturing. Sustainability, resilience, and human-centricity are positioned not as peripheral considerations but as foundational design principles embedded in manufacturing system architecture. This perspective offers a vision for future research and education and proposes that the field’s next generation of value will come from integration across resource, process, product, and system intelligence rather than from further optimization within existing boundaries.

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Publication Details

Journal
Journal of Manufacturing and Materials Processing
Published
2026-10-14
DOI
https://doi.org/10.3390/jmmp10100430
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
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article

A Perspective on Advanced Wood Manufacturing: A Decision-Centric Framework for Future Research and Education

Vahid Nasir
Journal of Manufacturing and Materials Processing
Digital Transformation in Industry
article

A Perspective on Advanced Wood Manufacturing: A Decision-Centric Framework for Future Research and Education

Vahid Nasir
article en

Abstract

For over a century, wood manufacturing has been organized around understanding the material and process and optimizing the product. It established a globally successful industry and enabled efficient production of traditional and engineered wood products. This manufacturing practice is now being challenged by the complexity of resource variability, product diversification, mass customization, and rapid technology integration. This perspective proposes Advanced Wood Manufacturing as a decision-centric smart manufacturing ecosystem that integrates Resource Intelligence, Manufacturing Intelligence, Product Intelligence, and System Intelligence through a unifying Decision Intelligence framework to convert variability into high-value manufacturing decisions. We argue that natural resource variability, while requiring control where necessary for reliable production, can also provide decision-relevant information for adaptive manufacturing and value creation. The product space of wood manufacturing extends far beyond lumber and panels into emerging functional products for energy storage, flexible electronics, and biomedical applications, enabled by artificial intelligence, sensing and digitalization, robotics, computational design, and additive manufacturing. Sustainability, resilience, and human-centricity are positioned not as peripheral considerations but as foundational design principles embedded in manufacturing system architecture. This perspective offers a vision for future research and education and proposes that the field’s next generation of value will come from integration across resource, process, product, and system intelligence rather than from further optimization within existing boundaries.

Journal of Manufacturing and Materials ProcessingVol. 10(10)
Oregon State University (US)
Responsible consumption and production, Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Digital Transformation in Industry
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