Special Issue "Intelligent Sensing for Sustainable Production Industries"

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: 15 September 2021.

Special Issue Editors

Dr. Marion McAfee
E-Mail Website
Chief Guest Editor
School of Engineering and Design, Institute of Technology, F91 YW50 Sligo, Ireland
Interests: process monitoring and control - particularly of polymer processes; soft sensors; process spectroscopy; process modelling and optimisation; medical device manufacturing
Dr. Johannes D. Stigter
E-Mail Website
Guest Editor
Wageningen University
Dr. Salem Gharbia
E-Mail Website
Guest Editor
Department of Civil and Construction Engineering, Institute of Technology Sligo, Sligo F91 YW50, Ireland
Interests: Water resources; climate change and integrated environmental systems modelling; environmental interventions using and adapting low-cost and high-end sensing technologies and numerical modelling

Special Issue Information

Dear Colleagues,

Over the last decade, there have been significant advances in intelligent sensing technologies which are having a major impact on the ability of many production industries to accurately monitor and control processes to improve efficiencies, reduce waste, lower environmental impact, improve product quality and to develop new products to improve the quality of life of citizens. Intelligent sensors utilize advanced signal processing, sensor fusion, mathematical models and learning algorithms to gain a better understanding of industrial processes and products and the factors that affect them. Intelligent sensing technologies can allow powerful information to be quickly and easily extracted from sensors such as low cost vision devices and sensors with highly complex responses such as spectroscopic methods which are difficult for human interpretation.

Examples of the transformative potential of intelligent sensing technologies for improving sustainability are rife across production sectors including agriculture, manufacturing, materials and chemical industries, textiles and food production.

This Special Issue will highlight recent and emerging research on concepts, methods, tools, and applications of intelligent sensing technologies for enhancement of sustainability across wide ranging industrial production sectors. This special issue aims to advance and promote the uptake of intelligent sensing approaches as an aid in accelerating the transition to sustainable industry.

Dr. Marion McAfee
Dr. Johannes D. Stigter
Dr. Salem Gharbia
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Signal Processing, Control and Estimation
  • Soft Sensors for sustainable industrial processes
  • Model-based design for sustainable production
  • Intelligent sensing for food production and safety
  • System identification and control for sustainable production
  • Intelligent sensing for low cost sensor networks
  • Information and Sensor Fusion
  • The role of sensing for Sustainable Agriculture

Published Papers (1 paper)

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Research

Article
Multivariate Modeling of Mechanical Properties for Hot Runner Molded Bioplastics and a Recycled Polypropylene Blend
Sustainability 2021, 13(14), 8102; https://doi.org/10.3390/su13148102 - 20 Jul 2021
Cited by 1 | Viewed by 452
Abstract
Four sustainable materials including a recycled polypropylene blend, polybutylene adipate terephthalate, and two grades of polylactic acid are compared to a reference isotactic polypropylene. Tensile specimens were produced using a two-cavity, hot runner mold with fully automatic cycles per standard industrial practices to [...] Read more.
Four sustainable materials including a recycled polypropylene blend, polybutylene adipate terephthalate, and two grades of polylactic acid are compared to a reference isotactic polypropylene. Tensile specimens were produced using a two-cavity, hot runner mold with fully automatic cycles per standard industrial practices to investigate the effect of melt temperature, injection velocity, cycle time, and screw speed on the mechanical properties. Multiple regression and principal component analyses were performed for each of the materials. Results indicated that all the materials were readily processed using a hot runner, and the mechanical properties exhibited minimal variation. To the extent that losses in mechanical properties were observed, the results indicated that the losses were correlated with thermal degradation as independently characterized by thermal gravimetric analysis. Such losses can be minimized by reducing melt temperature and cycle time, leading to a reduction of the environmental impact of injection molding processes. Full article
(This article belongs to the Special Issue Intelligent Sensing for Sustainable Production Industries)
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