Article
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Preserved in Portico This version is not peer-reviewed
Biologicalization of Smart Manufacturing using DNA-Based Computing
Version 1
: Received: 24 October 2023 / Approved: 24 October 2023 / Online: 25 October 2023 (11:46:25 CEST)
A peer-reviewed article of this Preprint also exists.
Ura, S.; Zaman, L. Biologicalization of Smart Manufacturing Using DNA-Based Computing. Biomimetics 2023, 8, 620. Ura, S.; Zaman, L. Biologicalization of Smart Manufacturing Using DNA-Based Computing. Biomimetics 2023, 8, 620.
Abstract
This article provides a general overview of the bio-inspired computing method called DNA-Based Computing (DBC), including its theory and applications. The main theme of DBC is the central dogma of molecular biology (once information of DNA/RNA has got into a protein, it can’t get out again), i.e., DNA to RNA (sequences of four types of nucleotides) and DNA/RNA to protein (sequence of twenty types of amino acids) are allowed, not the reverse ones. Thus, DBC transfers few-element information (DNA/RAN-like) to many-element information (protein-like), solving a given cognitive problem. DBC can take many forms; this article elucidates two main forms, denoted as DBC-1 and DBC-2. Using arbitrary numerical examples, it is shown that DBC-1 can solve the following cognitive problems: “similarity indexing between seemingly different but inherently identical objects” and “recognizing regions of an image separated by a complex boundary.” DBC-2 can solve the following cognitive problem: “pattern recognition when the relevant information is insufficient.” Smart manufacturing-based systems (digital twins and big data analytics) must solve the abovementioned problems to make the manufacturing enablers (machine tools and monitoring systems) more self-reliant and autonomous. Consequently, DBC can improve the cognitive problem-solving ability of smart manufacturing-relevant systems and, thereby, can enhance its biologicalization.
Keywords
central dogma of molecular biology; DNA-based computing; smart manufacturing, biologicalization of manufacturing; image processing; pattern recognition; sensor signals
Subject
Engineering, Industrial and Manufacturing Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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