Robotics for a Quality-Driven Post-harvest Supply Chain

Chauhan, Aneesh; Brouwer, Bastiaan; Westra, E.H.

doi:10.1007/s43154-022-00075-8

Cited by 14 publications

(5 citation statements)

References 49 publications

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“…12. Use of AI globally in manufacturing and supply chains [26] The supply chain AI adoption by worldwide businesses and industries is shown in the above graph. Grey indicates an infinite adoption of AI in businesses, orange indicates a plotting use case for AI, yellow indicates a widespread adoption of AI and ML, and blue with 11 % indicates that businesses view AI and ML are essential.…”

Section: With Ai Rolls Royce Reimagines Freight Transportation Safety...mentioning

confidence: 99%

Integration of robotics and automation in supply chain: a comprehensive review

Mohan Banur,

Patle,

Pawar

2024

Robot. syst., appl.

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Robotics and automation have developed as key technologies for supply chain management as a result of the increased demand for quicker and more effective supply chains. Robotics and automation improve supply chain management by lowering long-haul expenses, boosting work and usage strength, reducing errors, declining repetitive stock checks, updating orchestrating, taking care of times, and assembling induction to the problematic and hazardous places. Robotics aids in design, creation, etc. Automation helps to do tasks that are often done by people through the use of self-operating physical machines, computer software, and other technology. Despite being widely accepted as a tool to aid in decision-making, supply chain management (SCM) has very seldom used AI and ML. This article investigates several AI and ML sub-fields that are best suited for resolving real-world SCM-related issues in order to fully realize the potential benefits of AI and Ml for SCM. In doing so, this article examines the track record of successful AI and ML applications to supply chain management and highlights the most fruitful SCM domains to apply AI and ML. And also find out the how robotics and automations helps in warehouse management. The most recent developments in robotics and automation for supply chain management are thoroughly reviewed in this paper. We first give a general overview of the difficulties that supply chain management faces before going over the many ways that robotics and automation are used at various points along the supply chain. Additionally, we go over the advantages of robots and automation in supply chain management, including higher efficiency, accuracy, lower costs, and improved safety. Lastly, we discuss some of the present drawbacks and difficulties associated with robots and automation in supply chain management and suggest some possible directions for further investigation.

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Section: With Ai Rolls Royce Reimagines Freight Transportation Safety...mentioning

confidence: 99%

Integration of robotics and automation in supply chain: a comprehensive review

Mohan Banur,

Patle,

Pawar

2024

Robot. syst., appl.

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“…These machines can also collect information on soil and water quality, and plant or animal growth, which provides technical support for the implementation of precision agriculture and better breeding choices (Xu et al, 2022). Robots can perform many tasks along the post-harvest supply chain, such as sorting, storing, picking and packing, and shipping (Chauhan et al, 2022). Current robotic development is focused on replacing manual operations in food handling and processing, food packaging, food delivery, and other operations along the food supply chain (Duong et al, 2020;Sulaiman et al, 2021).…”

Section: Robotics and Smart Machinerymentioning

confidence: 99%

“…The most common robotic systems in the food industry do "pick and place, " i.e., they handle a specific type of object presented in a consistent, pre-defined orientation. Any variation in the object's shape and size can lead to failure to complete the pick and place task, making precise handling of irregular, naturally varying objects, such as vegetables and fruit, a greater challenge (Bader and Rahimifard, 2020;Chauhan et al, 2022). Soft robotics technology, soft grippers, and machine learning techniques have shown the potential to practically address the handling of irregular and naturally varying objects with low cost (Navas et al, 2021;.…”

Section: Digital Technologies For Smart Factoriesmentioning

confidence: 99%

Digital transformation in the agri-food industry: recent applications and the role of the COVID-19 pandemic

Hassoun

Marvin²,

Bouzembrak

et al. 2023

Front. Sustain. Food Syst.

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Providing food has become more complex because of climate change and other environmental and societal stressors, such as political instability, the growth in the world population, and outbreaks of new diseases, especially the COVID-19 pandemic. In response to these challenges, the agri-food industry has increased its efforts to shift to using more digital tools and other advanced technologies. The transition toward digital has been part of the fourth industrial revolution (called Industry 4.0) innovations that have and are reshaping most industries. This literature review discusses the potential of implementing digital technologies in the agri-food industry, focusing heavily on the role of the COVID-19 pandemic in fostering the adoption of greater digitalization of food supply chains. Examples of the use of these digital innovations for various food applications, and the barriers and challenges will be highlighted. The trend toward digital solutions has gained momentum since the advent of Industry 4.0 and implementations of these solutions have been accelerated by the outbreak of the COVID-19 pandemic. Important digital technology enablers that have high potential for mitigating the negative effects of both the current global health pandemic and the environmental crisis on food systems include artificial intelligence, big data, the Internet of Things, blockchain, smart sensors, robotics, digital twins, and virtual and augmented reality. However, much remains to be done to fully harness the power of Industry 4.0 technologies and achieve widespread implementation of digitalization in the agriculture and food industries.

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“…Moreover, the implementation of these technologies contributes to improved health and safety conditions for staff working in distribution centers. By utilizing equipment capable of lifting heavy pallets of crops, technologies create less hazardous working environments [32]. Additionally, advanced artificial intelligence models can assist in scheduling transportation and avoiding traffic congestion during distribution, ultimately reducing workload and enhancing the wellbeing of distribution center personnel [28].…”

Section: Disruptive Technologies Applied In the Agricultural Supply C...mentioning

confidence: 99%

Diversified Impacts of Enabling a Technology-Intensified Agricultural Supply Chain on the Quality of Life in Hinterland Communities

Lubag,

Bonifacio,

Tan

et al. 2023

Sustainability

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The agricultural supply chain (ASC) in the hinterland refers to the entire post-harvest process of processing and distributing agricultural products in rural or secluded areas to be brought to big city markets. This scheme involves various stakeholders (farmers, trading centers, consumers), processes (logistics, storage, monitoring), and infrastructure (traffic and road systems, negative environmental emissions) to ensure the efficient flow of agricultural products from farms to consumers. The quality of life (QoL) in the hinterland can improve with the introduction of disruptive technologies, but no comprehensive studies have explored the QoL of individuals involved in the ASC–socioeconomic system of hinterland communities. This study elucidated and compared the diversified impacts of disruptive technologies brought by the Industrial Revolution 4.0 to the agricultural supply chain and their impacts on food security, sustainability, and climate change mitigation through the analysis of the related literature. This study also mapped out the role of disruptive technologies in the QoL of hinterland communities, particularly with respect to the farmers, trading center workers, and consumers. Points of discussion emerged with respect to precision agriculture, the Artificially Intelligent Internet of Things, big data analytics, blockchain, artificial intelligence, cyber-physical systems, robotics, automation, and e-commerce, and how these enabling technologies enhance fresh food supply and distribution and deliberately affect stakeholders’ life quality indexes through the analysis of situational case studies in India, South America, Malaysia, China, and Europe. The identification of these points of discussion was also achieved purely based on research performed on the related literature. The positive impacts of these technologies, such as the boosting of efficiency and the ensuring of a steady supply of fresh produce, ultimately improve the overall QoL. The technical insights from the studies were synthesized to develop new frameworks for QoL anchored in the agricultural supply chain (AgQoL) in the hinterland, and a six-dimensional network emphasizing the two trifectas of techno-socioenvironmental needs was established. Food-producing communities with a relatively high AgQoL should support food security in the region.

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Robotics for a Quality-Driven Post-harvest Supply Chain

Cited by 14 publications

References 49 publications

Integration of robotics and automation in supply chain: a comprehensive review

Integration of robotics and automation in supply chain: a comprehensive review

Digital transformation in the agri-food industry: recent applications and the role of the COVID-19 pandemic

Diversified Impacts of Enabling a Technology-Intensified Agricultural Supply Chain on the Quality of Life in Hinterland Communities

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