Smart knife: technological advances towards smart cutting tools in meat industry automation

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.

Obtaining the effective gripper dimensions for a kiwifruit harvesting robot using kinematic calibration procedures

Purpose A harvesting robot is developed as part of kiwifruit industry automation in New Zealand. This kiwifruit harvester is currently not economically viable, as it drops and damages too many kiwifruit in the harvesting task due to the positional inaccuracy of the gripper. This is due to the difficulties in measuring the exact effective dimensions of the gripper from the manipulator. The purpose of this study is to obtain the effective gripper dimensions using kinematic calibration procedures. Design/methodology/approach A setup of a constraint plate with a dial gauge is proposed to acquire the calibration data. The constraint plate is positioned above the robot. The data is obtained by using a dial gauge and a permanent marker. The effective dimensions of the gripper are used as error parameters in the calibration process. Calibration is exercised by minimizing the difference between target positions and measured positions iteratively. Findings The robot with the obtained effective dimensions is tested in the field. It is found that the fruit drops due to positional inaccuracy of the gripper are greatly reduced after calibration. Practical implications The kiwifruit industry in New Zealand is growing rapidly and announced plans in 2017 to double global sales by 2025. This growth will put extra pressure on the labour supply for harvesting. Furthermore, the Covid pandemic and resulting border restrictions have dramatically reduced seasonal imported labour availability. A robotic system is a potential solution to address the labour shortages for harvesting kiwifruit. Originality/value For kiwifruit harvesting, the picking envelope is well above the robot; the experimental data points obtained by placing a constraint plate above the robot are at similar positions to the target positions of kiwifruit. Using this set of data points for calibration yields a good effect of obtaining the effective dimension of the gripper, which reduces the positional inaccuracy as shown in the field test results.

Assessment of the Readiness of Industrial Enterprises for Automation and Digitalization of Business Processes

The purpose of this article is to identify the promising areas of digitalization in the work of industrial enterprises at the national and regional level. The study was conducted on the basis of industrial enterprises of the Republic of Mordovia using the methods of a systematic approach, comparative and strategic analysis, mathematical statistics, etc. As a result, we assessed the impact of the digital transformation of the economy on the development of industrial enterprises in Russia and the Republic of Mordovia, changes in the efficiency of enterprises associated with the expansion of the use IT, the degree of satisfaction of enterprises with the use of specific tools of information and communication technologies, etc. Spearman’s rank linear correlation demonstrates positive and negative effects of ICT using the industrial enterprises. The novelty and practical value of the obtained results consists in the fact that confirmed research hypotheses reflect both specific regional factors and systemic nationwide problems of digitalization of the Russian industry, automation of business process, allow us to outline the priority areas of digital transformation of business models not only of the studied enterprises industry of the region, but also the non-resource sector of the industry in general.

A cloud based 3-tier data security framework for industrial internet of things

<p>The convergence of microelectronics and micromechanical system within a sensing device, the proliferation of wireless communication, and the use of software-driven equipment are already changing the landscape of the manufacturing industries. This situation compels the industries to adopt industrial internet of things (IIoT) systems and processes with the main objective-to improve the processes and increase production. However, it is undeniable that despite IIoT advantages, it posed significant issues on the security and privacy on industry automation especially along data generation and control system. Hence, this paper proposes a cloud based 3-tier data security framework that performs two-level security verification processes. The framework has been tested and validated using an experimental industry automation system and has been found to be functionally effective with an acceptable handoff delay.</p>

Non-Linear Energy Harvesting in RIS-assisted URLLC Networks for Industry Automation

A reconfigurable intelligent surface (RIS)-assisted wireless communication system with non-linear energy harvesting (EH) and ultra-reliable low-latency constraints is considered for its possible applications in industrial automation. A distant data-center (DC) communicates with the multiple destination machines with the help of a full-duplex (FD) server machine (SM) and RIS. Assuming the deficiency of enough transmission power at the FD-SM, the SM is considered in the near vicinity of the destinations in the industry to forward the data received from the distant DC. The reception at SM is assisted by the RIS and a non-linear hybrid power-time splitting (PTS) based EH receiver architecture is adopted to extend the lifespan of SM, thus increasing network lifetime. The scheduling of multiple destinations is done by SM based on the considered selection criteria namely, random (RND) scheduling, absolute (ABS) channel-power-based (CPB) scheduling and normalized (NRM) CPB scheduling. The end-to-end performance of the considered FD RIS-assisted network is analyzed, and the expressions for the block error rate (BLER) for all scheduling schemes are derived. Moreover, the effects of number of RIS elements, packet size, channel uses on the system performance are analyzed for the considered ultra-reliable and low-latency communication (URLLC) network. The scheduling fairness of all the scheduling schemes is also analyzed to study the performance-fairness trade-off. The derived analytical results are verified through Monte-Carlo simulations.

Non-Linear Energy Harvesting in RIS-assisted URLLC Networks for Industry Automation

A reconfigurable intelligent surface (RIS)-assisted wireless communication system with non-linear energy harvesting (EH) and ultra-reliable low-latency constraints is considered for its possible applications in industrial automation. A distant data-center (DC) communicates with the multiple destination machines with the help of a full-duplex (FD) server machine (SM) and RIS. Assuming the deficiency of enough transmission power at the FD-SM, the SM is considered in the near vicinity of the destinations in the industry to forward the data received from the distant DC. The reception at SM is assisted by the RIS and a non-linear hybrid power-time splitting (PTS) based EH receiver architecture is adopted to extend the lifespan of SM, thus increasing network lifetime. The scheduling of multiple destinations is done by SM based on the considered selection criteria namely, random (RND) scheduling, absolute (ABS) channel-power-based (CPB) scheduling and normalized (NRM) CPB scheduling. The end-to-end performance of the considered FD RIS-assisted network is analyzed, and the expressions for the block error rate (BLER) for all scheduling schemes are derived. Moreover, the effects of number of RIS elements, packet size, channel uses on the system performance are analyzed for the considered ultra-reliable and low-latency communication (URLLC) network. The scheduling fairness of all the scheduling schemes is also analyzed to study the performance-fairness trade-off. The derived analytical results are verified through Monte-Carlo simulations.