1,721,139 research outputs found
Technical note on “Inventory management in supply chains with consideration of Logistics, green investment and different carbon emissions policies”
No full textThis study presents an extension of the model proposed by Huang et al. (2020), which investigated the effects of carbon policies and green technologies on the integrated inventory management of a two-echelon supply chain with consideration of carbon emissions during the processes of production, transportation, and storage. Specifically, since the inventory policy impacts on the economic and environmental performances of the supply chain, this study proposes a mathematical model for the integrated inventory management of the single-vendor single-buyer supply chain under a consignment stock policy. The aim is, thus, to highlight advantages and disadvantages of the consignment stock agreement with respect to the traditional policy based on the model proposed by Hill (1999). To compare the results, the same three carbon emissions policies are considered: i.e., limited total carbon emissions, carbon taxation, and cap-and-trade. The proposed model can assist firms in determining their optimal inventory policy (i.e., agreement, production quantity, delivery quantity, and green investment amount) with an aim of minimizing the supply chain costs under different carbon emissions policies
Heating and cooling phase scheduling algorithm for automotive curve glass production
No full textThe need to increase the service level of the automotive supply chain, especially after the COVID-19 pandemic, leads to an increase in the efficiency and effectiveness of the production systems. The use of scheduling techniques and their implementation in Enterprise Resource Planning (ERP)/ Manufacturing Execution System (MES) systems can be a lever towards this improvement, remarkably in particularly constrained production systems. The presented case study stems from an industrial context and focuses on the heating and cooling phases of curved glass used in the automotive sector. In particular, the glass is subjected to a gradual heating process at temperatures between 500 and 600 °C, after which it softens and adheres by force of gravity to a curved mold located on the bottom of the heated room. The cooling phase takes place very slowly, to allow the material to acquire a greater flexural strength than a normal flat glass. The objective of this study is to present a scheduling algorithm to optimize the production of the curve glasses with different technical characteristics and heating and cooling phases. The implementation of this algorithm in the industrial context permits the increase of the ovens’ saturation and the respect of the delivery date of the production orders
Q-Learning for Inventory Management: an application case
No full textThe recent applications of 4.0 technologies are gradually leading to the introduction and development of artificial intelligence in production systems. This study discusses the assessment of a Machine Learning model, based on Reinforcement Learning, that may allow the optimization of the inventory level at the machine level, thus improving the ordering system and inventory management. The model is applied to a real industrial case and the results, compared with those obtained by using the traditional optimization techniques, show an appreciable performance. It can be concluded that the model of Machine Learning developed can be successfully used for improving the order cycle of an enterprise
Il rischio ambientale
No full textIl rischio ambientale chiama in causa il rapporto della società con la natura e la tecnologia. Questo volume mostra in modo puntuale come, di pari passo con l'aumento della potenza distruttiva della tecnologia, si isano venuti afffermando anche importanti strumenti che consentono di contrastarne gli effetti e indica le possibili linee immediate di intervento[...
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Economic production quantity model with learning in production, quality, reliability and energy efficiency
No full textLearning has become essential for many companies whose manufacturing environment, where tasks have increased in complexity, requires a workforce of specific skills. Training of workers and learning-by-doing reduce the unit cost as the production rate speeds and improve product and process quality. Better quality means less rework and machine downtime. All these aspects indirectly influence energy efficiency, which has become a concern for manufacturing companies due to the stringent targets imposed by legislators, the significance of energy costs, and the increasing customers’ awareness about the environment. A company, however, could invest in some alternatives to improve its energy efficiency. This paper, therefore, proposes a lot sizing model for a manufacturing company that includes the relevant learning outcomes, directly and indirectly, affecting its energy efficiency. The main result of the study is to show how learning in production and energy efficiency affects each other and the optimal lot size quantity
Inventory management for aging products with supply chain finance: The warehouse financing option
Full text linkFor businesses specializing in ameliorating goods, such as seasoned cheese, traditional financing models pose unique challenges. Inventory financing relies heavily on past performance, often overlooking the inherent value increase associated with proper aging. This can lead to limited access to capital, hindering growth and operational stability. Warehouse financing emerges as a specialized solution specifically designed for businesses with maturing inventory. Lenders recognize the future value potential of these goods, offering secured loans based on anticipated market appreciation. This approach unlocks immediate cash flow, empowering businesses to cover operational costs, invest in expansion, or manage cash flow fluctuations. This study develops and discusses inventory problems for the specific class of "ameliorating"products, integrated with the warehouse financing technique, to combine the two topics and highlight their main features but above all their scientific and practical importance. The models proposed are focused on a decentralized scenario (single actor perspective) and a centralized scenario (supply chain perspective) to compare the optimal solution in terms of the aging period while maximizing the annual profit. Furthermore, from the supply chain perspective, a multi-supplier single-manufacturer supply chain is proposed with a deteriorating raw material (i.e., fresh milk). While cheese is a prime example, warehouse financing can benefit a diverse range of businesses dealing with ameliorating goods (such as wines, coffee, and aged spirits)
Improving supply chain profit through reverse factoring: A new multi-suppliers single-vendor joint economic lot size model
Full text linkSupply chain finance has been gaining attention in theory and practice. A company’s financial position affects its performance and survivability in dynamic and volatile markets. Those that have weak financial performance are vulnerable when operating in environments that are uncertain and financially unstable. Companies adopt various solutions and techniques to manage, effectively and efficiently, the flow of money to and from its suppliers and buyers. Reverse factoring is an innovative technique in supply chain financing. This paper develops a joint economic lot size model where a vendor coordinates operational and financial decisions with its multiple suppliers through the establishment of a reverse factoring arrangement. The creditworthy vendor systematically informs a financial institution (e.g., bank) of payment obligations to selected suppliers, enabling the latter to borrow against the value of the relevant accounts receivable at low interest (borrowing) rates. The paper also presents a numerical example and a sensitivity analysis to illustrate the behavior of the model and to compare the economic and operational performance of a supply chain with and without a reverse factoring agreement. The results show that the establishment of a reverse factoring agreement within the supply chain improves the economic performance and impacts on the operational decisions
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