Search Results (46)

Driven by growing environmental awareness and supportive regulatory frameworks, electric vehicles (EVs) are witnessing accelerating market penetration. However, a key consumer concern remains: the economic impact of battery degradation, manifesting as vehicle depreciation and diminished driving range. To alleviate this concern, EV manufacturers commonly offer performance-guaranteed free-replacement warranties, under which batteries are replaced at no cost if capacity falls below a specified threshold within the warranty period. This paper develops a symmetry-informed analytical framework to forecast time-varying aggregate warranty replacement demand (AWRD) and to design optimal battery inventory strategies. By coupling stochastic EV sales dynamics with battery performance degradation thresholds, we construct a demand forecasting model that presents structural symmetry over time. Based on this, two inventory optimization models are proposed: the Service-Level Symmetry Model (SLSM), which prioritizes reliability and customer satisfaction, and the Cost-Efficiency Symmetry Model (CESM), which focuses on economic balance and inventory cost minimization. Comparative analysis demonstrates that CESM achieves superior cost performance, reducing total cost by 20.3% while maintaining operational stability. Moreover, incorporating CESM-derived strategies into SLSM yields a hybrid solution that preserves service-level guarantees and achieves a 3.9% cost reduction. Finally, the applicability and robustness of the AWRD forecasting framework and both symmetry-based inventory models are validated using real-world numerical data and Monte Carlo simulations. This research offers a structured and symmetrical perspective on EV battery warranty management and inventory control, aligning with the core principles of symmetry in complex system optimization. Full article

Vehicle owners often use certified service centers throughout the warranty period, which usually extends for five years after buying. Nonetheless, after this timeframe concludes, a large number of owners turn to unapproved service providers, mainly motivated by financial factors. This change signifies a significant drop in income for automakers and their certified service networks. To tackle this issue, manufacturers utilize customer relationship management (CRM) strategies to enhance customer loyalty, usually depending on segmentation methods to pinpoint potential clients. However, conventional approaches frequently do not successfully forecast which clients are most likely to need or utilize maintenance services. This research introduces a machine learning-driven framework aimed at forecasting the probability of monthly maintenance attendance for customers by utilizing an extensive historical dataset that includes information about both customers and vehicles. Additionally, this predictive approach supports workforce planning and scheduling within after-sales service centers, aligning with AI-driven labor optimization frameworks such as those explored in the AI4LABOUR project. Four algorithms in machine learning—Decision Tree, Random Forest, LightGBM (LGBM), and Extreme Gradient Boosting (XGBoost)—were assessed for their forecasting capabilities. Of these, XGBoost showed greater accuracy and reliability in recognizing high-probability customers. In this study, we propose a machine learning framework to predict vehicle maintenance visits for after-sales services, leading to significant operational improvements. Furthermore, the integration of AI-driven workforce allocation strategies, as studied within the AI4LABOUR (reshaping labor force participation with artificial intelligence) project, has contributed to more efficient service personnel deployment, reducing idle time and improving customer experience. By implementing this approach, we achieved a 20% reduction in information delivery times during service operations. Additionally, survey completion times were reduced from 5 min to 4 min per survey, resulting in total time savings of approximately 5906 h by May 2024. The enhanced service appointment scheduling, combined with timely vehicle maintenance, also contributed to reducing potential accident risks. Moreover, the transition from a rule-based maintenance prediction system to a machine learning approach improved efficiency and accuracy. As a result of this transition, individual customer service visit rates increased by 30%, while corporate customer visits rose by 37%. This study contributes to ongoing research on AI-driven workforce planning and service optimization, particularly within the scope of the AI4LABOUR project. Full article

The long-term usage of polymer products necessitates addressing the appropriate preservation of their low oxidation state that extends the warranty period. The addition of pertinent stabilization components into the composite formulations (synthesis and natural antioxidants, pristine and doped oxides, clays or couples of them) produces an improvement in the kinetic parameters characterizing the accelerated degradation that occurs during high-energy exposures. The competition between the material ageing and the mitigation of oxidation is controlled by the protection efficiency. In this paper, the main advantages of inorganic structures in comparison to classical organic antioxidants are emphasized. A significant improvement in stability, simultaneously associated with the enhancing of functional characteristics, the lack of migration, low cost and easy accessibility, make the reevaluation of certain fillers as stabilizers appropriate. The correlation between the functional properties and the filler nature in polymer materials may be reconsidered for the assessment of the participation capability of inorganic structures in the inhibition of oxidation by the inactivation of free radicals. The lifetimes of degradation intermediates extended by the activities of inorganic compounds are increased by means of electrical interactions involving the unpaired electrons of molecular fragments. These physical contributions are reflected in chemical stability. An essential feature for the presented inorganic options is a strong impact on the recycling technologies of polymers by radiation processing. Plastic products, including all categories of macromolecular materials, can gain an increased durability through the inorganic alternative of protection. Full article

Driven by the trend of integrating monitored data into reliability management to explore innovative and practical approaches for managing reliability, researchers in the industry–university–research community have proposed random warranties. Existing random warranties use the limited mission cycle as a warranty-expiry limit instead of a measurement tool for controlling costs. This either shortens the warranty period for consumers or increases costs for manufacturers. To tackle these issues, this paper integrates mission cycles into the reliability management during the warranty stage and defines and models a renewal repair–replacement warranty with random charge (RRRW-RC) to manage the warranty-stage reliability of products. In the RRRW-RC, the limited mission cycles, acting as a usage limit, are used as a measurement tool to recover the fractional replacement cost within the warranty stage. This is designed to compensate manufacturers for replacement losses without shorting the warranty period, thus achieving the goal of reducing the warranty costs and not shortening the warranty period. The RRRW-RC can classify the usage habits of consumers into the heavy usage type and light usage type. Therefore, based on the usage classification results generated by the RRRW-RC, this paper also customizes two random maintenance policies to manage the post-warranty reliability of products. The first policy includes preventive/corrective replacement and “whichever occurs first,” and is thus referred to as customized bivariate random maintenance first (CBRMF). By revising “whichever occurs first” to “whichever occurs last,” the second policy is similarly represented and is called customized bivariate random maintenance last (CBRML). The policies defined above are modeled in terms of cost and time measures or cost rates, and their derivative policies are presented and modeled by setting parameter values. Numerical investigations are carried out to explore the management insights hidden in the proposed policies. Numerical investigations reveal that, by setting the failure number at an appropriate value, the warranty cost of the RRRW-RC can be minimized and its warranty period can be extended. Full article

This research investigated the real-world operational performance of five purposely designed and built net-zero-energy houses in Melbourne, Australia. The embodied energy and carbon emissions of these houses were calculated based on their architectural and engineering drawings, as well as the relevant databases of embodied energy and emission factors. Operational data, including solar production, consumption, end uses, battery usage, grid import, and grid export, were measured using the appropriate IoT devices from May 2023 to April 2024. The results showed that all the studied houses achieved net-zero energy and net-zero carbon status for operation, exporting between 3 to 37 times more energy than they consumed to the grid (except for house 2, where the consumption from the grid was zero). The embodied carbon of each case study house was calculated as 13.1 tons of CO₂-e, which could be paid back within 4 to 9 years depending on the operational carbon. Achieving net-zero cost status, however, was found to be difficult due to the higher electricity purchase price, daily connection charge, and lower feed-in tariff. Only house 2 was close to achieving net zero cost with only AUD 37 out-of-pocket cost. Increasing the energy exported to the grid and storing the generated solar energy may help achieve net-zero cost. The installation of batteries did not affect the net-zero energy or emission status but had a significant impact on net-zero operational costs. However, the calculated payback period for the batteries installed in these five houses ranged from 43 to 112 years, making them impractical at this stage compared to the typical 10-year warranty period of the batteries. With rising electricity purchase prices, decreasing feed-in tariffs (potentially to zero in the future/already the case in some areas), and government incentives for battery installation, the payback period could be reduced, justifying their adoption. Moreover, the installed 13.5 kWh Tesla battery was too big for households with lower energy consumption like houses 2 and 5, which used only 25% of their total battery capacity most of the year. Therefore, selecting an appropriately sized battery based on household consumption could further help reduce the payback period. Full article

Numerous attempts have been made to create a secure system that meets the criteria and requirements of the automotive vehicle development life cycle. However, a critical gap exists in the secure development lifecycle, particularly concerning the development and maintenance of software after the vehicle has been sold by the manufacturer. This step is often overlooked by original equipment manufacturers (OEMs), especially after the expiration of the vehicle warranty period, given the cost that it will require to update and test the software in their vehicles. This paper addresses the issues that affect current and future vehicle cybersecurity, during the maintenance of cybersecurity, and how the neglect of it could end up creating hazards for the vehicle owner or other road users. To accomplish this, we will employ the technology adoption model (TAM) as a theoretical framework, which is used to understand and predict how organizations adopt technology. Thus, through qualitative and quantitative research, including text mining, we identify the challenges in the adoption and diffusion of cybersecurity maintenance in the automotive sector and its supply chain. In addition, we propose possible solutions on how to maintain a level of security that will benefit road users, OEMs and regulators, covering the cybersecurity needs for the vehicle’s usable life, taking into account the vehicle’s heterogeneity of components and technology, connectivity, environmental impact and cost of production and maintenance of a vehicle. Full article

Extended warranty services have become increasingly important for both manufacturers and retailers, offering avenues for new profit sources and growth opportunities. Focusing on the multiple effects of product quality, this study develops a two-period supply chain decision model to analyze the effects of product quality, pricing, and inventory management in the context of extended warranty services. Using a Stackelberg dynamic game model, this study examines the interaction between a manufacturer and a dominant retailer who provides extended warranties. The results indicate significant differences in optimal decisions between centralized and decentralized supply chains, especially concerning pricing and inventory control. Introducing a “quality cost-sharing” contract enhances product quality and improves coordination, leading to increased profits for both the manufacturer and the retailer. Numerical simulations confirm that the cost-sharing contract effectively balances product quality improvements with supply chain profitability. Full article

As more renewable energy sources are integrated into the United Kingdom’s power grid, flexibility services are becoming integral to ensuring energy security. This has encouraged the proliferation of Lithium-ion battery storage systems, with 85 GW in development. However, battery degradation impacts both system lifespan and the economic viability of large-scale projects. With rising commodity costs and supply chain issues, maximising the value of energy storage is critical. Traditional methods of mitigating battery ageing rely on static limits based on inflexible warranties, which do not fully account for the complexity of battery degradation. This study examined an alternative, degradation-aware current derating strategy to improve system performance. Using an optimisation model simulating UK energy trading, combined with an electro-thermal and semi-empirical battery model, we assessed the impact of this approach. Interviews with industry leaders validated the modelled parameters and the relevance of the alternative strategy. Results show the degradation-aware strategy can extend battery lifetime by 5–8 years and improve net present value and internal rate of return over a 15-year period compared with traditional methods. These findings highlight the economic benefits of flexible, degradation-aware operational strategies and suggest that more adaptive warranties could accelerate renewable energy integration and lower costs for storage operators. Full article

Despite stiff competition in the construction industry, housing quality remains a problem. From the consumer’s perspective, these quality problems are called defects. Homeowners experience inconvenience and suffering due to home defects, and developers and builders also experience severe damage in time, costs, and reputation due to defect repairs. In Korea, lawsuits are increasing due to the rise in housing defects, and the cost of repairing defects determined by lawsuits is of great concern. Litigation is a burden to consumers and producers, requiring a hefty court fee, as well as attorneys and specialist firms, and takes some years. Suppose it is possible to predict the repair costs based on the outcome of a lawsuit and present it as objective supporting data. In that case, it can be of great help in bringing a settlement between consumers and producers. According to previous studies on housing repair costs, linear regression models were mainly used. Accordingly, in this study, a linear regression model was adopted as a method to predict housing repair costs. We analyzed the defect repair costs in 100 cases in which lawsuits were filed and the verdict was finalized for housing complexes in Korea. Previous studies investigated using the following independent variables: elapsed period, litigation period, claim amount, home warranty deposit, total floor area, households, and main building’s quantity, construction cost, region, and highest floor. Among these, the floor area, elapsed period, and litigation period were determined to be valid independent variables. In addition, the construction period was discovered as a valid independent variable. The present research model, which combines these independent variables, was compared with previous research models. The results showed that the earlier research model was found to have a multicollinearity issue among some independent variables. Also, the coefficients of some independent variables were not statistically significant. This research model did not have a multicollinearity problem; all independent variables’ coefficients were statistically significant, and the coefficient of determination was higher than other linear research models. Our proposed regression model, which accounts for the interaction of each independent variable, is a significant step forward in our research. This model, using the number of households multiplied by the construction period, the construction period multiplied by the litigation period, and the litigation period multiplied by the litigation period as independent variables, has been rigorously tested and found to have no multicollinearity issue. The coefficients of all independent variables are statistically significant, further bolstering the model’s reliability. Additionally, the explanatory power of this model is comparable to the previous model, suggesting its potential to be used in conjunction with the existing model. Therefore, the linear regression model predicting the repair cost of housing defects following litigation in this study was considered the best. Utilizing the model proposed in this study is expected to play a major role in reconciling disputes between consumers and producers over housing defects. Full article

In the supply chain management of electronic products, asymmetric cost information is a prevalent issue that can lead manufacturer to misreport costs, thereby exacerbating supply chain imbalances. This study focuses on the electronic product supply chain with an extended warranty service, where the manufacturer bears the after-sales responsibility during the extended warranty period. It explores the decision-making (DM) issues within the supply chain under different information environments and power structures. The Stackelberg game theory is employed to solve and analyze these models, and the main findings are as follows: (1) When supply chain information is symmetrical, centralized DM is the best choice. However, in cases where the supply chain adopts decentralized DM, it is more beneficial for the retailer and the supply chain if the retailer assumes the role of DM leader. Additionally, when the retail price sensitivity coefficient is low, the manufacturer will compete with the retailer for DM priority. Conversely, when the retail price sensitivity coefficient is higher, the manufacturer is better off as a follower in DM; (2) When the supply chain information is asymmetric, the manufacturer may engage in misreporting, which benefits the manufacturer but is detrimental to both the supply chain and the retailer. Moreover, if the price sensitivity coefficient is low, the manufacturer should lead the supply chain DM. Otherwise, the retailer should take the lead in supply chain DM. Adopting such a flexible strategy will prove advantageous for all parties involved in the supply chain. (3) The strategy of “reducing the retail price and increasing the extended warranty price” is a favorable strategy for the supply chain. Full article

Battery systems enable the sustainable use of energy from renewable energy installations that are characterized by variable time availability. The present study investigated the benefits of implementing an electrical energy storage system to a photovoltaic (PV) installation in the Polish climatic conditions. The impact of such a system on increasing profits from energy sales was verified. The use of storage allows for shifting the process of feeding energy into the grid to later hours when it is more expensive. The production volume and timing of energy generation were considered using the example of a 5 kWp research installation located in the Laboratory of Renewable Energy. The yields and energy prices were analyzed on an hourly basis for the year 2023. The considered system is additionally equipped with a battery with a capacity of 15 kWh. Analyses have shown that this system covers 55.6% of days in a year where the entire daily production from the PV installation can be stored. Additionally, the feasibility of using different energy storage capacities to shift the sale of the maximum energy volume was examined. Also the payback period of investments was considered for four scenarios (from the most expensive devices to the cheapest ones with subsidies). Prices were compared with profits resulting from the use of storage systems of a given capacity, as well as with the lengths of warranties covering the devices. Full article

The leasing of various types of equipment plays a significant role in reducing resource consumption, reducing the need for frequent replacements, and lessening the environmental impact of equipment manufacturing and disposal. This paper examines a maintenance policy for equipment that is leased multiple times throughout its lifespan. If the equipment fails to perform as expected within the basic and extended warranty durations, the lessor makes minimal repairs at its own expense. Once the warranty period has elapsed, the lessor is still responsible for carrying out any necessary repairs, but the lessee is required to pay for them. The warranty periods are not uniform. To reduce the frequency of breakdowns, the lessor carries out preventive maintenance (PM) between successive lease periods, with the aim of reducing the age of the equipment to some extent. The costs associated with PM depend on the set of actions to be performed and their associated efficiency in terms of age reduction. A mathematical model is proposed to simultaneously find the optimal efficiency levels of PM to be carried out between successive lease periods and the optimal extended warranty periods to be offered to lessees in order to maximize the lessor’s expected total profit throughout the equipment’s lifecycle. To demonstrate the use of the developed model, a numerical example and a sensitivity study are discussed. Our model demonstrates its ability to provide valuable insights and facilitate decision-making in the establishment of leasing contracts. Full article

Rooftop photovoltaic (RPV) systems are valuable clean-energy-efficient technology that facilitates the transition toward energy sustainability in residential buildings. Hence, the government in Jordan implemented the feed-in-tariffs (FiT) policy to motivate residents’ willingness to install RPV systems. However, the quality of RPV products and services is a key determinant of social acceptance to install RPV systems. Hence, manufacturers and suppliers are working closely with adopters to design and manufacture RPV systems that meet or exceed their expectations. Still, there is a need to develop a quantitative assessment to examine the effects of this FiT policy and the quality of RPV systems on energy security. This study, therefore, develops a system dynamics model to examine the effects of the FiT policy and the quality of RPV products and services on social acceptance to install RPV systems. To achieve this objective, several hypotheses were established related to the main model factors, including the quality of services, complaint reduction, performance ratio, payback period and warranty, and FiT price, with a willingness to install RPV systems. Then, a system dynamics model was constructed. The simulation results reveal the significant factor that impacts energy goals. Moreover, from the end of the year 2030 to the end of 2050, RPV installations, generated power, and CO₂ emission reductions are expected to increase from 0.681 GW to 72.83 GW, from 1.07 to 125.74 TWh, and from 0.680 to 79.59 million tons of CO₂, respectively. Optimization was performed to maximize the three objectives under the uncertainty of key model variables. The optimal factor values can significantly increase the current energy goals by about 20%. In conclusion, collecting, analyzing, and evaluating adopter input and feedback on RPV systems regarding their design and technology and manufacturing and the post-services of RPV systems significantly influence energy sustainability in residential buildings. In addition, government support through investing in the FiT policy can boost RPV installations in residential buildings. Full article

To support the bankability of PV projects, PV manufacturers have been offering one of the longest warranties in the world, typically in the range of 25–30 years. During the warranty period, PV manufacturers guarantee that the degradation of PV modules will not exceed 0.4–0.6% each year, or the buyer can at any time make a claim to the manufacturer for replacement or compensation for the shortfall. Due to its popularity, the performance warranty terms have become more and more competitive each year. However, long-term PV operating data have been very limited and bankruptcy of PV manufacturers has been quite common. Without a proper methodology to assess the adequacy of PV manufacturer’s warranty fund (WF) reserve, the 25-year performance warranty can become empty promises. To ensure sustainable development of the PV industry, this study develops a probability-weighted expected value method to determine the necessary WF reserve based on benchmark field degradation data and prevailing degradation cap of 0.55% per year. The simulation result shows that, unless the manufacturer’s degradation pattern is significantly better than the benchmark degradation profile, 1.302% of the sales value is required for the WF reserve. To the best of our knowledge, this is the first study that provides WF reserve requirement estimation for 25-year PV performance warranty. The result will provide transparency for PV investors and motivation for PV manufacturers for continuous quality improvement as all such achievement can now be reflected in manufacturers’ annual report result. Full article

Nowadays, a car’s engine oil change interval is an essential factor in reducing wear. The correct choice depends on various factors. This study analyzes the changes in the composition of three different engine oils (0W30, 5W30, and 5W40) during the generally accepted oil change interval (15,000 km) in gasoline and diesel cars during the post-warranty period. Commercially available low-level biofuel blends (B7 and E10) were used to power test vehicles in a field test. Engine oil samples were taken every 3000 km for more detailed analysis and tested in an accredited laboratory. The contaminants in the engine oil were determined using several testing methods: spectrometric analysis, gas chromatography, etc. Studies have shown that all used cars have an increase in the number of iron particles, an increased concentration of silicon, and also an increase in the number of nickel particles above 12,000 km. Tests also showed a sharp drop of molybdenum anti-friction additives 4.5 times and a gradual increase in fuel concentration for the Opel Insignia over 12,000 km, but over 9000 km, a significant increase in the concentration of chromium particles. Based on this research results, it is preferable to choose a maintenance interval of no more than 12,000 km for cars during the post-warranty period. In this way, the intensity of engine wear can be reduced due to the loss of adequate protective properties of the engine oil. Full article