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EN
Inventory management’s fundamental problem starts with maintaining equilibrium among the operating efficiency, cost of investment, and other allied costs with extensive inventories to keep the actual conflicts at the minimum while optimizing the inventory holding levels. But, inventory management practices have not been well exploited in various manufacturing industries yet. In this study, inventory management tools, i.e., ABC and VED analysis, have been applied in the manufacturing industry, considering 146 items as raw material for an assembly. A total of 15 items under ‘AV’ class have been identified that consume 82.05 % of the total cost, and these items need strict control and frequent ordering. Sigma level of suppliers is also calculated, which comes out to be 2.36, and it must be improved to reduce the overall inventory cost.
EN
A thriving healthcare system perfectly reflects economic development and contentment amongst the people of any region. With increasing anxiety concering health and growing medical needs, hospitals worldwide face substantial challenge to provide patients with adequate medical facilities under one roof. With a fragile state of the health industry in a developing country like India, there is a need for the hospitals to opt for international standards and comply with other premier health centers of the country. This paper aims to select the hospitals based on incongruous and conflicting criteria involving group decision-making using the Intuitionistic Fuzzy (IF) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The criteria used are concomitant to an insured public health scheme named Ayushman Bharat-National Health Protection Scheme (AB-NHPS) of the Government of India. For each alternative Euclidean distance has been used to calculate the positive and negative separation measure from the ideal solution. The relative closeness to the ideal solution has been used to rank the hospitals. The result is a list of hospitals ranked from best to worst based on the laid criteria. It can aid governing bodies in decision-making under an uncertain environment with multiple complex criteria to analyze.
EN
Background: Predictive analysis is a vital element to operations management as it facilitates real-time decision making and advanced planning on both strategy and performance. This paper identifies predictors to measure distribution performance in the dairy industry and to establish their importance. Methods: A distribution model is developed through exploratory structural equation modelling (SEM) techniques. The key performance predictors are marketing and distribution management, quality management, supply chain coordination, and brand management, which account for 71.5% of the variability in distribution performance. Results and conclusion: The predictors help improving the distribution performance, specifically in quality, order fill rate, and food safety. The outcomes of this research can help dairy professionals in managing their distribution channels, improving traceability, on-time delivery, and shipment accuracy. Consequently, these factors can improve distribution performance. Four predictors are elicited from the data to estimate the distribution performance and the relative importance of predictors is also established.
EN
The agri-food sector contributes significantly to economic and social advancements globally despite numerous challenges such as food safety and security, demand and supply gaps, product quality, traceability, etc. Digital technologies offer effective and sustainable ways to these challenges through reduced human interference and improved data-accuracy. Innovations led by digital transformations in the agri-food supply chains (AFSCs) are the main aim of 'Agri-Food 4.0'. This brings significant transformations in the agri-food sector by reducing food wastage, real-time product monitoring, reducing scalability issues, etc. This paper presents a systematic review of the innovations in the agri-food for digital technologies such as internet-of-things, artificial intelligence, big data, RFID, robotics, blockchain technology, etc. The employment of these technologies from the ‘farm to fork’ along AFSC emphasizes a review of 159 articles solicited from different sources. This paper also highlights digitization in developing smart, sensible, and sustainable agri-food supply chain systems.
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