Abstract

PurposeModern 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/approachThis 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.FindingsOptical 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/valueThis 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.

Highlights

  • A butcher uses a combination of both the eye-vision and handfeeling to analyse the material being cut, to differentiate between the layers in the complex medium and make instant decisions

  • Meat cutting is one of these tasks and many advancements have been made in mechanical approaches to this, the smart cutting tool, or smart knife, is still not a commercially available option

  • Meat cutting is one of these tasks and many advancements have been made in mechanical approaches to this, the smart cutting tool or smart knife, is still not a commercially available option

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Summary

Introduction

A butcher uses a combination of both the eye-vision and handfeeling to analyse the material being cut, to differentiate between the layers in the complex medium (e.g. a carcass) and make instant decisions. A wide range of techniques, from low frequency, high frequency electrical impedance measurement, microwaves, NMR, IR and UV light, to X-rays, involves a wide range of physical interactions between the sensing method and the sample Not all these approaches are suitable for real-time haptics-cut feedback during actual meat cutting. Those that offer an instantaneous response and a non-destructive interaction mechanism, are considered in this paper as potentially feasible options to advance and customise meat industry automation. These methods should not affect the meat itself (Egelandsdal et al, 2019) in a way that could change product properties (Muradov et al, 2020), or even render some parts of it unsuitable for consumption.

Electrical impedance measurements
Force sensing
Optical methods
Other spectroscopic measuring options
Electromagnetic wave-based sensing
Critical comparison of technologies for smart knife
Findings
Conclusion
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