Article
Version 1
Preserved in Portico This version is not peer-reviewed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.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
