Intelligent Agro-Food Chain Supply

Sharma, Manoj Kumar; Dhaka, Vijaypal Singh; Shekhawat, Rajveer Singh

doi:10.1007/978-981-16-6210-2_4

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…By analysing data from various sources, such as sensors, IoT devices, and supply chain management systems, companies can gain a more comprehensive and accurate understanding of their operations and make informed decisions about how to improve efficiency and reduce costs (Unhelkar et al, 2022). BI can help in (1) Production planning: BI can help organisations track production data and identify patterns and trends that can inform decision‐making around production schedules and quantities (Rejeb et al, 2022; Sharma et al, 2022); (2) Inventory management: BI can help organisations track inventory levels, forecast demand, and optimise stock levels to reduce waste and ensure that customers have access to the products they want (Rejeb et al, 2022; Sharma et al, 2022); (3) Distribution optimisation: BI can help organisations optimise distribution routes and logistics to reduce costs and ensure the timely delivery of products (Rejeb et al, 2022; Sharma et al, 2022).…”

Section: Implementation Of Industry 40 In CM Productionmentioning

confidence: 99%

Industry 4.0 technologies for cultivated meat manufacturing

Kamalapuram,

Choudhury

2024

Food Bioengineering

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Industry 4.0 integrates the physical, digital, and biological realms by applying digital automation in systems, processes, and manufacturing facilities. Industry 4.0 is actively shaping the development of intelligent food processing industries in cultivated meat (CM) sector. This integration plays a crucial role in accelerating progress within the global CM sector, facilitating the achievement of its objectives related to food sustainability, security, human health, environmental concerns, and hygiene. Incorporating Industry 4.0 into CM manufacturing systems empowers upstream and downstream production processes to become more intelligent and capable of self‐optimisation. However, enabling rapid adoption of Industry 4.0 by emerging startups and small to medium‐sized enterprises in the CM industry necessitates a thorough understanding of prerequisites and evaluation of technological and biological limitations. Challenges include the substantial initial costs associated with establishing Industry 4.0 infrastructure, robust cybersecurity measures to ensure effective risk management, and acquiring skilled professionals proficient in both operational and maintenance roles. Integrating Industry 4.0 with the evolving CM sector presents an exciting opportunity to foster business‐to‐business investments across various domains, including local markets, export opportunities, and the broader global consumer ecosystem.

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Section: Implementation Of Industry 40 In CM Productionmentioning

confidence: 99%

Industry 4.0 technologies for cultivated meat manufacturing

Kamalapuram,

Choudhury

2024

Food Bioengineering

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Managing the Supply Chain for the Crops Directed from Agricultural Fields using Blockchains

Kannan

Pattnaik

Karthikeyan³

et al. 2022

2022 International Conference on Electronics and Renewable Systems (ICEARS)

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Sustainable Supplier Selection in Agri-Food Supply Chain Management

Ada

2022

Int J Math, Eng, Manag Sci

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In recent times, sustainability of supply chains becomes the most interested subject by customers, firms, government bodies, academia, and suppliers as the environmental resources reveal as the most valuable and limited asset for human beings. One of the most important elements determining the performance of sustainable agri-food supply chain business is supplier’s commitment. A mainly inspiring feature in this domain is the wide range of factors influencing supplier selection decision-making process in Triple Bottom Line context must be analyzed. However, it is not easy to completely integrate and measure majority of these factors in a simple optimization model. Therefore, this paper starts with a comprehensive review of literature about supplier selection for sustainable supply chains (SSCs) development. Afterwards, a new two-steps hybrid solution method is suggested. In initial step, a set of criteria for supplier selection process is analyzed built on Fuzzy Analytic Network Process (FANP). The result of the first step is fed in to the second step of the analysis to design a model with multiple objectives for selection process of supplier using fuzzy VIKOR. All three dimensions of sustainability; specifically, factors such as weather, water and soil footprint, energy and material consumption, employment, social services and finally financial performance of supply chain are considered concurrently. The suggested approach generates a comprehensive model to help supply chain managers in supplier selection process. Numerical analysis is completed via exploiting data from a Turkish agri-food company case for validating effectiveness, also and success of the proposed solution. Final analytical results of the analysis provide valuable business policy oriented, operational and practical insights on the influence of economic, environmental, and social sustainability for enhanced supplier relationship management module in sustainable supply chain structure. Moreover, by tracking environmental impact indicators such as, emission and pollution rates, footprint rates, against social and cost indicators it would be possible to perform tradeoff analysis for giving more sustainable decisions on new supply chain investments.

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Intelligent Agro-Food Chain Supply

Cited by 3 publications

References 21 publications

Industry 4.0 technologies for cultivated meat manufacturing

Industry 4.0 technologies for cultivated meat manufacturing

Managing the Supply Chain for the Crops Directed from Agricultural Fields using Blockchains

Sustainable Supplier Selection in Agri-Food Supply Chain Management

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