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The surge in e-commerce has significantly altered consumer shopping habits, shifting towards online purchases. This change renders the traditional single-channel supply chain insufficient, often resulting in lost profits. Consequently, many businesses now incorporate an online channel alongside their physical stores. This shift has led to the adoption of dual-channel supply chains by manufacturers, aiming to attract a broader customer base and expand market share. Leasing options are becoming increasingly popular, offering a novel method for consumers to acquire products. However, studies on dual-channel supply chains that include leasing options are scarce and typically focus on single-period pricing. This paper explores a realistic, centralised dual-channel supply chain model that encompasses manufacturing, remanufacturing, refurbishing, distribution, and storage, along with selling, leasing, and repair services. A mathematical model is developed for a multi-period environment. This model simultaneously optimises manufacturing, remanufacturing, distribution strategies, storage costs, service offerings, and pricing for both sold and leased products, considering repair services for defective items. The paper presents numerous numerical analyses to demonstrate how integrating leasing services impacts the supply chain's profitability, the effect of customer preferences on pricing strategies, and how the cost of collecting used products influences remanufacturing decisions over a set time frame. [ABSTRACT FROM AUTHOR]

Background: Optimization approaches and a models can be applied for critical production systems that experience equipment failure, repair delays and product quality control in order to maximize the total profit. We can cite, as an example, flexible manufacturing systems. Methods: Our methodology involves developing a decision model integrated with an information system to coordinate various system operations, ensuring timely response to customer requests. The module of the information system is provided to optimally manage the production flow and parts ordering according to machine availability. The objective is to determine the optimal order thresholds of part batches that maximize the total profit. Results: Numerical results are provided to analyze the influence of system reliability and uncertainty on decision variables, offering insights into the system's performance and robustness. By using our method, the advancement of the flexible production systems is carried out by addressing key operational challenges and optimizing production processes for enhanced efficiency and profitability. Conclusions: To achieve this, an optimization algorithm is employed to identify optimal solutions that enhance profitability. [ABSTRACT FROM AUTHOR]

Several literature works have treated the quality question of the new and remanufactured products and its production cost and if the all returned-used products are remanufacturable. In this context, this study treated the case of returned-used products in the lease contract with/without maintenance monitoring option and its influence on the production and maintenance strategies for a manufacturing/remanufacturing system. A new integrated maintenance to production strategy studies the influence of the new and returned-used products according to its quality on the production cost and the degradation level of the manufacturing and remanufacturing units. Firstly, the objective of this study is to determine the economical production plan of manufacturing and remanufacturing units to satisfy the random demands under a given service level and during a finite horizon. Secondly, by considering the influence of the degradation on the failure and emission rates, we determine the optimal preventive maintenance strategy for each production unit, which minimise the total cost of production, maintenance and carbon emission. Numerical results are provided to show the efficiency of the proposed strategies by studying the impact of different parameters of the proposed model. [ABSTRACT FROM AUTHOR]

This paper proposes an integrated model for multi-machines dynamic lot sizing aiming to produce a single item, considering the energy consumption during the production horizon. The objective is to find, firstly, the optimal lot size as well as the number of machines that satisfy a random demand under given service level and secondly, maintenance plan depended to production planning to minimise the total production, energy and maintenance costs. In fact, the problem of energy consumption is one of the most evoked topics especially with the decision of many governments to reduce theirs (For example France is willing to reduce the total consumption by 20% by 2020). The keys of this study are to consider, firstly, the correlation between the forecasting of demand, the variation of the working machines as well as their production rates under energy constraint and secondly the correlation between the production cadences and the maintenance strategy of all machines. [ABSTRACT FROM AUTHOR]

This article presents a Johansen test assessing the predetermined long-term relationships of datasets from a photovoltaic (PV) plant to predict the power output of an island zone. The goal was to use Johansen's model to predict the PV power generation in the island of Mauritius. In this article, time series using an on-site measurement dataset have been used to design an original prediction model, the Johansen model for PV power output. This model is trained to predict random monthly, weekly, and daily PV power outputs in different seasons and years. The experimental results demonstrate that the Johansen model is a powerful medium-term predicting tool. [ABSTRACT FROM AUTHOR]