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1 – 4 of 4Alex Mason, Dmytro Romanov, L. Eduardo Cordova-Lopez, Steven Ross and Olga Korostynska
Modern meat processing requires automation and robotisation to remain sustainable and adapt to future challenges, including those brought by global infection events. Automation of…
Abstract
Purpose
Modern meat processing requires automation and robotisation to remain sustainable and adapt to future challenges, including those brought by global infection events. Automation of all or many processes is seen as the way forward, with robots performing various tasks instead of people. Meat cutting is one of these tasks. Smart novel solutions, including smart knives, are required, with the smart knife being able to analyse and predict the meat it cuts. This paper aims to review technologies with the potential to be used as a so-called “smart knife” The criteria for a smart knife are also defined.
Design/methodology/approach
This paper reviews various technologies that can be used, either alone or in combination, for developing a future smart knife for robotic meat cutting, with possibilities for their integration into automatic meat processing. Optical methods, Near Infra-Red spectroscopy, electrical impedance spectroscopy, force sensing and electromagnetic wave-based sensing approaches are assessed against the defined criteria for a smart knife.
Findings
Optical methods are well established for meat quality and composition characterisation but lack speed and robustness for real-time use as part of a cutting tool. Combining these methods with artificial intelligence (AI) could improve the performance. Methods, such as electrical impedance measurements and rapid evaporative ionisation mass spectrometry, are invasive and not suitable in meat processing since they damage the meat. One attractive option is using athermal electromagnetic waves, although no commercially developed solutions exist that are readily adaptable to produce a smart knife with proven functionality, robustness or reliability.
Originality/value
This paper critically reviews and assesses a range of sensing technologies with very specific requirements: to be compatible with robotic assisted cutting in the meat industry. The concept of a smart knife that can benefit from these technologies to provide a real-time “feeling feedback” to the robot is at the centre of the discussion.
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Khalil Arshak and Olga Korostynska
Combination of a number of sensors with different response parameters into sensor arrays would enhance the overall performance of the radiation detection system. This paper…
Abstract
Purpose
Combination of a number of sensors with different response parameters into sensor arrays would enhance the overall performance of the radiation detection system. This paper presents a conceptual approach to the development of sensor arrays system with instantaneous dose and dose rate readout. A dynamic selection of multiple sensors with various sensitivity and accuracy range is implemented by applying pattern recognition (PR) analysis, which maximizes measurement accuracy. A number of relevant PR methods are discussed.
Design/methodology/approach
Thick films based on NiO, ZnO, In2O3, CeO2, TiO2, CuO and CdO are the key sensing elements in the proposed approach. Pure and carbon‐doped metal oxides were screen‐printed on Si wafers to form pn‐heterojunctions. All devices were exposed to a disc‐type 137 Cs source with an activity of 370 kBq. The values of radiation damage of pn‐junctions were estimated from changes in their current‐voltage characteristics.
Findings
Sensors showed an increase in the values of current with the increase in radiation dose up to certain levels, exceeding these levels results in unstable dosimetric characteristics.
Originality/value
The sensitivity of metal oxide films to γ‐radiation exposure depends on their composition and thickness. Mixing the oxides in different proportions and the addition of conducting particles, such as carbon, alters films susceptibility to radiation. In particular, sensors based on such films have dose response characteristics with certain level of sensitivity and working dose range, conditioned by particular sensing material properties and the device structure.
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Khalil Arshak, Olga Korostynska and John Henry
Indium oxide (In2O3) and silicon oxide (SiO) mixtures in the form of thick films pn‐junctions were investigated for gamma radiation dosimetry purposes. Polymer pastes of In2O3 and…
Abstract
Indium oxide (In2O3) and silicon oxide (SiO) mixtures in the form of thick films pn‐junctions were investigated for gamma radiation dosimetry purposes. Polymer pastes of In2O3 and SiO mixtures in various proportions were made of 92 wt per cent of functional material and 8 wt per cent of PVB, while ethyleneglycolmonobutylether was used as a solvent. Raman spectroscopy and X‐ray diffraction (XRD) of the films readily endorse the formation of a mixed silicon oxide and indium oxide coating. All devices were exposed to a disc‐type 137Cs source with an activity of 370 kBq. The I‐V characteristics for the samples were measured after each exposure dose. Results show that the current is increased with the increase in radiation dose to a certain level, exceeding this level resulted in unstable dosimetric characteristics and device damage. The performance parameters of the devices, such as sensitivity to γ‐radiation exposure and working dose region, were found to be highly dependant on the composition of the materials used.
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