# Meat 4.0: Principles and Applications of Industry 4.0 Technologies in the Meat Industry
## 3 Industry 4.0 Technologies Applied for Meat Processing and Preservation  
The need for sustainable food systems calls for innovative plans that secure the global food supply and minimize food losses and waste throughout the supply chain. Here, the use of IR 4.0 technologies in the processing chain and during meat preservation is of special importance as it could prevent food losses. Among the tools that could help minimize waste and maintain adequate production are robotics and automation IR 4.0 systems, since they favour rapid processing by minimizing sources of contamination, and therefore increasing the shelf life of the meat. However, on account of peculiarity of animal carcasses and the locations obtained from them, robotization and automation processes are a challenge for Meat 4.0. Despite this initial complexity, the development and implementation of robotization and automation are of special interest because the slaughter tasks and the secondary processing of the carcasses are labours that currently involve most of the manual work, which is repetitive and must be done at high speed [32]. Although it is true that in the case of slaughterhouses many processing operations (stunning, bleeding, scalding, plucking, skinning, evisceration, splitting, and cooling) are already successfully automated [57], in the secondary processing of meat, hardware and software must be developed so that robots can offer a flexible, scalable, compact, and profitable alternative in the production line [32]. Cutting and boning operations are among the most labour-intensive due to the skill and sense required during processing. In this field, there are some automation systems that use detection units based on vision scanners in order to define the path and depth of the meat cuts in the primary and secondary meat processing stages (Table 1). On this matter, in automation for cutting, the use of laser lines that allow 3D scanning is common. A very prominent example of automation in the meat industry is the AiRA Robotics set, developed by the Frontmatec Company for employ in the clean line of pork slaughterhouses. Among this set, it is worth highlighting the presence of the robot designed to vacuum and remove the plugs from the carcass rectum (_AiRA RBD Bung Dropper_); the aitch bone cutter (_AiRA RHC Aitch Bone Cutter_); the breast and belly cutter (_AiRA RBO Breast and Belly Opener_); the head clipper (_AiRA RNC Neck Clipper_); and the carcass splitter (_AiRA Splitters_). The technology developed by Frontmatec has both the robot and saw combination (_AiRA RPS-S Splitter with Saw_), as well as a robot and knife (_AiRA RPS-H Splitter with Knives_) and even has a pair of robotic arms (_AiRA RPS-D Dual Arm Splitter with Saw_) [57]. Also in pork meat, there are currently different IR 4.0 technologies that allow deboning (femur and tibia removal) the back legs through robotic systems. _Hamdas-RX_[58] and _SRDViand project_[59] are two of these IR 4.0 technologies, which allow deboning through X-ray and 3D images, respectively, to calculate the cutting path to be followed by the robotic equipment. Other similar robotic technologies are also available for lamb and beef carcasses. Thus, in the case of lambs, we find the _SCOTT Automated Boning Room_, which is an intelligent system that uses 3D scanners and X-rays to predict the best cutting route and achieve the deboning of certain parts of the lamb, such as the back legs [57]. On the other hand, for beef carcasses, there is the _SRDViand project_ technology that allows to operate half carcasses. Specifically, the _SRDViand project_ has a vision system (currently operational) capable of extracting information to count the ribs and identify the dorsal spine and a robotic arm that makes the appropriate Z-cut [59; 61]. The vision system (namely \"eye-to-hand\") consists of a camera and a projector that performs a 3D reconstruction by triangulation, through which the ribs and the dorsal spine are counted and identified, respectively.