An expert system for predicting orchard yield and fruit quality and its impact on the Persian lime supply chain

In recent years academics and industrials have shown an interest in agricultural systems and their complex and non-linear nature, aiming to improve production yield in the agricultural field. Innovative strategies and methodological frameworks are thus required to assist farmers in decision making for an efficient and effective resource management. In particular, this research concerns the structural problem of the Persian lime supply chain in Mexico, which still leads to low production yield over short time periods with heterogeneous fruit quality and also to the emergence of excessive middleman businesses arising from a fragmentation between orchard and exporting companies that constitute the first two links in the associated supply chain. Based on the Persian lime production cycle, an Expert System (ES) using Fuzzy Logic involving an inference engine with IF—THEN type rules is presented in this paper. A Mamdani model codifies the decision criteria related to agricultural practices for growing Persian lime in non-irrigated orchards. The ES allows the farmer to boost production in orchards by modeling application scenarios for agricultural practices. A case study based on an exporting company׳s fruit supply is discussed, in which the ES proves to be a useful tool to aid the decision making involved in the application of agricultural practices in the orchard. Results show an increase in production yield and fruit quality in the orchard, as well as a better synchronization between orchard and exporting companies, with a significant impact on inventory levels of fresh fruit in the link Persian lime exporting company

Methodology for Supply Chain Integration: A Case Study in the Artisan Industry of Footwear

The supply chain is a major issue in a global market. The efficient relationship between supplier-producer-retailer conforms the perfect combination to achieve a high level of competitiveness according to the needs of increasingly demanding and changing markets. The difficulty of synchronizing the members within the SC is related to the inherent uncertain factors. This paper proposes a methodology for integrating the supply chain that can be applied in any type of business. To demonstrate its relevance, a case study is performed at a handmade shoe company. An improved demand forecasting, an optimal balanced production line, a proper inventory management of raw materials, and an efficient calculation of the delivery time to the customer represent some of the main results

Multi-Objective Optimal Design of a Hydrogen Supply Chain Powered with Agro-Industrial Wastes from the Sugarcane Industry: A Mexican Case Study

This paper presents an optimization modeling approach to support strategic planning for designing hydrogen supply chain (HSC) networks. The energy source for hydrogen production is proposed to be electricity generated at Mexican sugar factories. This study considers the utilization of existing infrastructure in strategic areas of the country, which brings several advantages in terms of possible solutions. This study aims to evaluate the economic and environmental implications of using biomass wastes for energy generation, and its integration to the national energy grid, where the problem is addressed as a mixed-integer linear program (MILP), adopting maximization of annual profit, and minimization of greenhouse gas emissions as optimization criteria. Input data is provided by sugar companies and the national transport and energy information platform, and were represented by probability distributions to consider variability in key parameters. Independent solutions show similarities in terms of resource utilization, while also significant differences regarding economic and environmental indicators. Multi-objective optimization was performed by a genetic algorithm (GA). The optimal HSC network configuration is selected using a multi-criteria decision technique, i.e., TOPSIS. An uncertainty analysis is performed, and main economic indicators are estimated by investment assessment. Main results show the trade-off interactions between the HSC elements and optimization criteria. The average internal rate of return (IRR) is estimated to be 21.5% and average payback period is 5.02 years