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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.

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.

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.

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.

The mechanization of the meat cutting companies has become essential. This paper aims to study the feasibility of cutting operations for beef and boning operations for pork ham. The study aims to enhance industrial robots application by using vision or force control.

The paper opted for an industrial robot‐based cell. The first part of this paper focuses on in‐depth study of operators' expertise, so as to translate their actions into automatable operative tasks and to identify the constraints of robotization. It details more particularly a cutting strategy using a bone as a guide which shows the complexity of the process. The analysis of the cutting and task constraint parameters involves the use of a kinematically redundant robotized cell with force control. Then the cell model is developed, and experimentation is performed.

The paper explains how to solve the problem of the high variability of the size for beef carcass. It gives several ideas to realize the boning of pork ham. It develops the strategies, the sensors and the cell architecture to make this type of operations.

Because of the choice of an existing industrial robot, the tool paths with force control are limited. Therefore, new force control instructions have to be developed to continue this work on more complicated operations.

This study was carried out within the framework of the SRDViand project in cooperation with meat industry partners.

The paper fulfils an identified need to study the beef quartering which is a high‐variability operation and ham deboning which is a high precision operation.

Over the last five years we have successfully researched, designed, developed and commercialised the world’s first lamb and sheep dressing robots. Two have already been sold to commercial concerns. This has caused a paradigm shift in the way automation in meat processing can be viewed. In this paper we describe the lessons we have learned in robotic automation via projects in Y‐cutting, ripdown, brisket clearing, opening cuts, handling of primal cuts and packing bagged meat pieces for lamb and sheep meat. All of these projects have been, or are about to be, trialed in operating plants processing export quality meat. These projects have involved the development of a programmable robot suitable for washdown environments, and of tooling to conduct specific dressing and handling tasks. Latest projects are applying this approach to automating certain beef processing tasks, and a beef processing robot has been constructed and is being installed for trials in an operating plant. The technology behind the robots is described and illustrated in our paper. Also described are the methods we used to ensure commercialisation was an economic success.

The mechanization of the meat cutting companies has become essential due to the lack of skilled workers and to working conditions. This paper deals with the analysis of human gestures in order to improve the performance of a redundant robotic cell. The aim is to define optimization criteria linked to the process and the human gesture analysis to improve the cutting process with a redundant robotic cell.

This paper deals with an optimized path planning of complex tasks based on the human arm analysis. The first part details the operator's manual work. The robotized cutting strategy using bones as a guide associated with an industrial force control leads to the tasks redefinition. Thus, the analysis of the arm during the tasks is presented. With a robotic model, the authors evaluate the relevance of two criteria (kinematic and mechanical) that the operator naturally manages. These criteria are used to improve the robotized cutting process by using redundancy. Simulation work and experimentation are presented to show the enhanced performance.

The paper explains how to define optimization criteria based on human arm analysis to realize cutting operations which require force or dexterity performance. It presents a study on the criteria weighting on a robotic arm model established through human arm analysis. The optimized cutting process clearly shows improvement.

The scalability of the ham implied the definition of iterative trajectories to follow the curvature of the bone. Due to the use of an industrial force control, no online optimization can be achieved. The off-line optimization implies that the boundary of the trajectory space is technically feasible. Nevertheless, more information has to be extracted from the deboning process such as vision data in order to improve cutting quality.

This study was carried out within the framework of several national and European projects (FUI SRDViand, ANR ARMS, FP7 Echord Dexdeb) in collaboration with ADIV (Meat Institute Development Agency). The redundant robotic cell was developed and implemented at ADIV and used for feasibility studies in connection with SME/SMI French sector.

The paper deals with the cutting of soft bodies such as meat and complex human gesture analysis, which constitute an innovative challenge for the coming years in order to help or replace humans in industrial meat companies with difficult working conditions.

Discusses research carried out by the Advanced Manufacturing and Automation Research Centre [AMARC], University of Bristol into the automation of two areas of meat production, the butchery of half carcasses into main joints and the evisceration of whole carcasses. Describes how the robotic butchery process requires sensing, determination of cut‐paths and trajectories for the robot, mechanical cutting using appropriate tools and the ability to transport, manipulate and hold each carcass during cutting and how each of these areas bas been integrated into a practical system. Also describes the system developed for robotic evisceration. Concludes that this research work has led to two industrial demonstrator systems for processing meat carcasses which have had encouraging response from potential customers.

The purpose of this paper is to provide details on implementation of inexpensive and accurate automation solution for performing brisket cutting while the sheep/lamb is hanging by forelegs.

The system developed uses 6 Degree of freedom (DOF) industrial manipulator, custom build tool, sterilizer, and other off the shelf products to create a machine, all the parameters in the system are designed to ensure that the highest levels of safety and hygiene standards are met. The primary system has been developed for sheep/lamb.

It is shown that the system developed enhanced both the productivity and quality of the process, while adhering to the hygiene standard in the meat processing plants.

The process of precise brisket can be very challenging; the system designed uses customised tools to provide a good model for the trajectory planning.

The system developed uses statistical tools to calculate the correct trajectories.

Examines the effectiveness of using expensive robotics equipment in the food industry where profit margins are low and labour is less expensive than in other industries. Looks at the work undertaken at the Silsoe Research Institute into developing appropriate low‐cost technology for basic food applications. Projects discussed include robotic teat cups for milking cows and a robotic mushroom harvesting; both using pneumatic power transmission. Concludes that food production will become an important application for robotics when it is generally accepted as cost effective.

Vision‐based intelligent automation systems have been slow in finding a way to the food industry, mainly due to the conservative nature of the food processing industrial sector, and the unproven maturity of the required vision and automation technologies. Vision‐based systems should be convincingly robust, and fulfil the set performance requirements at a reasonable economic investment.

Practically all salmon fillets produced in Norway are trimmed clean of unwanted fat, bone remnants and other defects according to customer requirements. In today’s modern salmon-processing plants, the trimming operation is performed by a combination of automated trimming machines and manual post-trimming. Manual post-trimming is necessary due to the inability of current trimming machines to obtain satisfactory trimming. The purpose of this paper is to describe the work done so far toward a robotic post-trimming of salmon fillets.

A prototype concept system was developed to explore the possibility of robotic post-trimming. The concept is based on 3D machine vision, a high-speed robot manipulator and a flexible light-weight cutting knife.

The developed prototype demonstrated the feasibility of detecting a pre-defined object to be trimmed in 3D, and performing the specified trimming cut along a 3D cutting trajectory.

The developed prototype system was built and integrated – focusing so far only on a single trimming operation: the tail cut.

The originality in the paper is the description of a prototype integrated system, focused on robotic post-trimming of salmon fillets. The value is in providing a starting point for further development toward a complete robotic post-trimming of salmon fillets.