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CENTER FOR SCALABLE AND INTELLIGENT AUTOMATION IN POULTRY PROCESSING (CSIAPP)

Objective

The vision of the Center for Scalable and Intelligent Automation in Poultry Processing (CSI-APP) is to incorporate the advanced technologies in robotics, artificial intelligence, digital sensing, biosensing, and food safety to provide U.S. poultry processing industry scalable and intelligent solutions to meet the rising national and global demand in poultry products. The long-term goal focuses on transforming current mass manufacturing protocols in large, centralized processing plants to "mass customization" scale-neural protocols suitable for processing plants in different scales to overcome the inherent variability associated with raw biological materials and humans, and large-scale individualization can be achieved economically through the integration of digital and physical systems (e.g., "industry 4.0" principles). In pursuit of the vision and the long-term goal, in short-term, CSI-APP will strategically target value creation and technological innovation by performing focused engineering research and extension activities by following four unifying objectives to bond bioproducts, human and sensing/robotics technologies:Objective 1: Scalable poultry manufacturing: lot size of one for robotic processing of chicken carcasses. Specifically, the objective is to create a scalable plant-ready intelligent robotic deboning system capable of performing at parity with (or even exceeding) human deboners for the most skilled task in the plant: shoulder cutting of front-halves. The human benchmark is 35 birds/minute and lost yield of 2% of total yield weight.Objective 2: Virtual reality-based workforce transformation.The objective 2 is to bridge the gap between fully manual and fully autonomous operations by leveraging human intelligence and robotic endurance. To develop and deploy the fully automated system proposed in Objective 1 needs to collect large amounts of human operational data, and requires long-term validation and optimization. To accelerate the data collection and robotic deployment, a VR based human-in-the-loop robotics will be developed in this objective to facilitate necessary steps that will allow for select manual operations within a poultry processing operation to be performed via robots. This VR based robotic system will allow a worker remotely collaborate with robotic devices in order to jointly accomplish processing tasks in a facility. The online human decision making results collected in the VR system will also be used for optimizing the fully automated system in the objective 1.Objective 3: Robots for robots: sensor and robotic-based product evaluation, bio-mapping and decision making in the processing plant to address the new challenges in food quality and safety raised by robotic manufacturing.The goal of Objective 3 is to create new 'robots for robots' protocols to design a new set of robotic and sensor solutions to address the emerging food safety and quality challenges brought by automated meat manufacturing solutions. The related challenges and questions include unknown pathogen transmission patterns, the new requirements of sanitization protocols, potential product quality degradation and the introduction of new FO contaminations. To fill the above gaps, specifically, CSI-APP team proposed a new proactive mobile swab sampling robot platform to collect the environmental surface swab samples with onsite pathogen detection and pathogen transmission pattern visualizations. The outputted quantitative results will also be used for designing and optimizing current sanitization protocols. Additionally, an all-in-one hyperspectral imaging based non-invasive FO contamination detection and food quality evaluation system will be developed and integrated with previous processing lines for online food quality control.Objective 4: Research and extension integration: create an innovation ecosystem through technology development/transfer and workforce education.The Objective 4 is to integrate the research and extension activities and accelerate the technology transformation to better meet the stakeholders needs via activities including interviews, workshops, industry conferences, and demonstration exhibits.

Investigators
Subbiah, J.; Owens, CA, M..; Li, YA, .; Crandall, PH, .; Gibson, KR, .; Hu, AI, .; Usher, CO, TR.; Wang, DO, .; Obe, TO, .; Britton, DO, .; Kuoakou, BR, .; Mcquillan, JU, .; Ahlin, KO, .; Joffe, BE, .; Melkote, SH, .; Park, MI, .
Institution
UNIVERSITY OF ARKANSAS
Start date
2023
End date
2027
Project number
ARK02806
Accession number
1029956
Commodities