Browsing by Author "Maciel, Vinicius Biasutti Pitol"
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- Decision support system to assign food price rebates on the basis of quality declinePublication . Maciel, Vinicius Biasutti Pitol; Matos, Cláudia; Lima, Tânia M.; Gaspar, Pedro Dinis; Santos, Fernando CharruaIn order to reduce food waste, fruits and vegetables in special, in small and medium markets sizes, caused by loss of quality at the end of shelf life, an appropriate pricing method was created to maximize profit of seller. The method it was based on an acquisition of primary data, through questionnaires appropriate to the theme, and, subsequently, these primary data was used for mathematical modeling using a pricing dynamic method. As a last step this work, was development a spreadsheet application, where the seller can found a ideal point of order, size of stock and best price to sell. This way, using the application, the goal of reduction of food waste in fruit products is expected.
- Decision Support System to Assign Price Rebates of Fresh Horticultural Products Based on Quality DecayPublication . Matos, Cláudia; Maciel, Vinicius Biasutti Pitol; Fernandez, Carlos M.; Lima, Tânia M.; Gaspar, Pedro DinisHorticultural products ripeness brings out features like flavor, texture, aroma, skin changes and finally, generates waste due to its spoilage. To avoid or minimize it, many traders as supermarkets, mini-markets and groceriesmake changes in their fruit’s prices just before expiration date. However, customers’ acceptability changes during the products shelf life, which leads to selling decrease along products quality decay and, consequently, profit decrease. This behavior establishes a challenging scenario to manage stock replenishment and pricing strategies. Many studies present inventory management model for perishable food products but considering only physical quantity deterioration whereas some few authors discuss dynamic pricing, considering quantity and quality deterioration simultaneously. Aiming the optimization of profit in traders, this work introduces a decision support system to assign price rebates of fresh horticultural products based on quality decay. To achieve this goal, two methodologies were followed. The first one consists in using experimental test results formodeling purposes, based on Pontryagin’smaximum principle, using apple, banana and strawberry. The former consists in using questionnaire as sensitivity analysis of quality from customers’ perspective, bringing more reliability and criteria for modeling, since quality could be subjective. The result is a computational decision support system to predict the optimum price for a specific fruit during shelf life. The main objective is to extend the applicability of the computational tool in order to overcome challenges related to limitations of logistics, allowing mini-markets and groceries use this software.
- The Synergic Relationship Between Industry 4.0 and Lean Management: Best Practices from the LiteraturePublication . Santos, Beatrice Paiva; Enrique, Daisy V.; Maciel, Vinicius Biasutti Pitol; Lima, Tânia M.; Santos, Fernando Charrua; Walczak, RenataIndustry 4.0 promises to make manufacturing processes more efficient using modern technologies like cyber-physical systems, internet of things, cloud computing and big data analytics. Lean Management (LM) is one of the most widely applied business strategies in recent decades. Thus, implementing Industry 4.0 mostly means integrating technologies in companies that already operate according to LM. However, due to the novelty of the topic, research on how LM and Industry 4.0 can be integrated is still under development. This paper explores the synergic relationship between these two domains by identifying six examples of real cases that address LM-Industry 4.0 integration in the extant literature. The goal is to make explicit the best practices that are being implemented by six distinct industrial sectors such as automotive, paper, furniture, healthcare, apparel, and machine manufacturing.