The evolution of intelligent manufacturing has had a profound and lasting effect on the future of global manufacturing. Industry 4.0 based smart factories merge physical and cyber technologies, making the involved technologies more intricate and accurate; improving the performance, quality, controllability, management, and transparency of manufacturing processes in the era of the internet-of-things (IoT). Advanced low-cost sensor technologies are essential for gathering data and utilizing it for effective performance by manufacturing companies and supply chains. Different types of low power/low cost sensors allow for greatly expanded data collection on different devices across the manufacturing processes. While a lot of research has been carried out with a focus on analyzing the performance, processes, and implementation of smart factories, most firms still lack in-depth insight into the difference between traditional and smart factory systems, as well as the wide set of different sensor technologies associated with Industry 4.0. This paper identifies the different available sensor technologies of Industry 4.0, and identifies the differences between traditional and smart factories. In addition, this paper reviews existing research that has been done on the smart factory; and therefore provides a broad overview of the extant literature on smart factories, summarizes the variations between traditional and smart factories, outlines different types of sensors used in a smart factory, and creates an agenda for future research that encompasses the vigorous evolution of Industry 4.0 based smart factories.
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http://dx.doi.org/10.3390/s20236783 | DOI Listing |
PLoS One
January 2025
Department of Business Administration, College of Business Administration, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.
Improving energy efficiency is crucial for smart factories that want to meet sustainability goals and operational excellence. This study introduces a novel decision-making framework to optimize energy efficiency in smart manufacturing environments, integrating Intuitionistic Fuzzy Sets (IFS) with Multi-Criteria Decision-Making (MCDM) techniques. The proposed approach addresses key challenges, including reducing carbon footprints, managing operating costs, and adhering to stringent environmental standards.
View Article and Find Full Text PDFMicrob Cell Fact
January 2025
Chair of Biochemistry of Microorganisms, Faculty of Life Sciences: Food, Nutrition and Health, University of Bayreuth, 95326, Kulmbach, Germany.
Background: During the last decades, the advancements in synthetic biology opened the doors for a profusion of cost-effective, fast, and ecologically friendly medical applications priorly unimaginable. Following the trend, the genetic engineering of the baker's yeast, Saccharomyces cerevisiae, propelled its status from an instrumental ally in the food industry to a therapy and prophylaxis aid.
Main Text: In this review, we scrutinize the main applications of engineered S.
J Bacteriol
January 2025
Department of Environment and Energy Systems, Graduate School of Science and Technology, Shizuoka University, Shizuoka, Japan.
Nitrification by heterotrophic microorganisms is an important part of the nitrogen cycle in the environment. The enzyme responsible for the core function of heterotrophic nitrification is pyruvic oxime dioxygenase (POD). POD is a non-heme, Fe(II)-dependent enzyme that catalyzes the dioxygenation of pyruvic oxime to produce pyruvate and nitrite.
View Article and Find Full Text PDFPLoS One
December 2024
School of Intelligent Manufacturing, Panzhihua University, Panzhihua, Sichuan, P. R. China.
Plant Commun
December 2024
Biotechnology Research Institute, Chinese Academy of Agricultural Sciences Beijing, 100081, China. Electronic address:
Synthetic biology (SynBio) plays a pivotal role in improving crop traits and increasing bioproduction by using engineering principles that purposefully modify plants through "design, build, test and learn" cycles, ultimately resulting in improved bioproduction based on input genetic circuit (DNA, RNA, and Proteins). Crop synthetic biology is new tool following circular principles to redesign and create innovative biological components, devices, and systems to enhance yields, nutrient absorption, resilience, and nutritional quality. In the digital age, artificial intelligence (AI) has demonstrated great significance in the design and learning.
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