Search Results (11)

Background: The service life and availability of electronic components are steadily declining, whereas the operational lifespan of industrial devices that incorporate such components often extends over several decades. This disparity creates a mismatch between the durability of individual components and the longevity of the overall systems in which they are embedded. Obsolescence Management (OM) addresses this issue by establishing a structured and controlled process aimed at anticipating and mitigating the impacts of component and product obsolescence. As defined by the international standard International Electrotechnical Commission [IEC] 62402:2019, obsolescence refers to the transition of an (electronic) item from availability to unavailability by the manufacturer, in accordance with the original specification. To implement proactive OM, obsolescence managers require data that are comprehensible, accurate, complete, trustworthy, secure, and discoverable. In this context, Data Governance (DG) offers a promising approach to enhance data literacy and intelligence within OM. Methods: This study employed a sequential mixed-methods design, integrating qualitative and quantitative approaches including a Systematic Literature Review (SLR), Expert Interviews (EIs), Focus Groups (FGs), Content Analysis (CA), and Workshops (WKSHs), within a case study informed by Design Science Research (DSR). Results: This paper proposes a DG structure tailored to support OM through data integration and business intelligence methods, drawing on established DG reference frameworks within an SME. The proposed structure encompasses a set of processes and knowledge domains recognized as best practices in the field. Furthermore, we present a model designed to facilitate the implementation of DG in OM and to assess the quality of the data required. This enables more reliable obsolescence processes across key functional areas such as product management, procurement, and product development, ultimately supporting data-driven and accurate decision-making. Full article

Educational institutions are massive consumers of computing technologies, often replacing their computing infrastructure in a 3-to-5-year timeframe. Once decommissioned, many components of computing technologies are no longer useable and become electronic waste. Replacing computer infrastructure within these short timeframes is a significant e-waste sustainability issue that educational institutions need to address. This article aims to introduce and provoke new thinking regarding e-waste management and its implications for education. The authors introduce the term sustainable device literacy to conceptualise how educators and educational institutions can take an educative approach to refreshing computing technologies beyond their presumed obsolescence. Two example case studies that demonstrate the upgrade of a laptop from 2012 and a desktop computer from 2015 are included to provoke new discussions regarding e-waste and education. Using benchmarking tools, the findings from the case studies show that computing technologies that may be considered obsolete can be upgraded to include much of the functionality of current computers. The broader implications for sustainability are discussed. Full article

An e-textile system was developed, allowing USB reprogramming of miniature, flexible, integrated microcontroller circuits which allows for easier development of complex and configurable e-textile circuits. This prototype consisted of a series of five exposed pads on the edge of the PCB and a corresponding clip connector. Mounted onto the clip are a micro-USB port and necessary additional components to facilitate USB programming meaning that no additional components are required on the microcontroller board thus increasing flexibility. This system has the potential to make software development and reconfiguration of the e-textile easier while the small size and flexibility of the connector allow improved textile integration. This work provides a platform for future e-textile system development and increases the operational lifetime, thus reducing waste due to product obsolescence. Full article

This paper proposes a comprehensive procedure to assess the condition of gas insulated switchgear (GIS) equipment by using the conventional weight and score method and introducing a conditional factor to improve the accuracy of the health index evaluation. Generally, the inspection and testing of GIS components are conducted according to manufacturer recommendations and guidelines in the international standards. However, this raw data has not been simplified and systematically processed for condition assessment. The score and weight technique are applied to transform the physical condition according to visible and measurable aging to numerical values in terms of component and bay health index values. The accuracy of the obtained health index has been improved by a conditional factor, which considers invisible aging factors, such as age, number of switching operations, degree of satisfactory operation, obsolescence, and adequacy of the interrupting rating. Here, a condition evaluation procedure has been developed and compared with the fuzzy logic method and the health index dominant score technique with satisfactory results. Subsequently, the proposed procedure has been developed as web application software to evaluate 175 bays of GIS in both 115 and 230 kV networks of an independent power producer supplying electricity of 3094 MW to a large industrial estate in Thailand. Eight GIS bays showed moderate or poor condition and the proper actions were assigned to prevent their failure. The software is in use in practice as a decision support tool to effectively manage the maintenance tasks and to improve supply reliability. Full article

Companies building products with a usage phase of 25 years and more, have suffered from obsolescence for decades. Software and hardware components inside of the supporting systems, such as avionics test benches, are particularly affected. They consist of components built for 3–7 years but expected to operate for decades. The lack of standardized, open and modular systems for special timing constraints increase the pressure and impede the interoperability in this field. Industry 4.0 systems offer exactly this, but do not support aviation standards. The research in this article aims to show that it is possible to use widespread Industry 4.0 standards and technology at the field level to achieve transferability and maintainability in the operation of test benches. This article describes an implemented and evaluated proof of concept of the implementation of an industrial ethernet standard EtherCAT for the ARINC 429 I/O for an aviation test bench. As a baseline, market available EtherCAT components were evaluated and selected. For the client development, standard components for the EtherCAT logic and ARINC 429 were used. Additionally, the full interoperability at the syntax level, was achieved by implementing a configuration approach of the I/O, in order to encode and decode the messages. The evaluation was performed using an Airbus A350-1000 test bench for secondary flight controls—namely the HighLift system. Full article

Product obsolescence occurs in the manufacturing industry as new products with better performance or improved cost-effectiveness are developed. A proactive strategy for predicting component obsolescence can reduce manufacturing losses and lead to customer satisfaction. In this study, we propose a machine learning algorithm for a proactive strategy based on an adaptive data selection method to forecast the obsolescence of electronic diodes. Typical machine learning algorithms construct a single model for a dataset. By contrast, the proposed algorithm first determines a mathematical cover of the dataset via unsupervised clustering and subsequently constructs multiple models, each of which is trained with the data in one cover. For each data point in the test dataset, an optimal model is selected for regression. Results of empirical experiments show that the proposed method improves the obsolescence prediction accuracy and accelerates the training procedure. A novelty of this study is that it demonstrates the effectiveness of unsupervised clustering methods for improving supervised regression algorithms. Full article

Product obsolescence occurs in every production line in the industry as better-performance or cost-effective products become available. A proactive strategy for obsolescence allows firms to prepare for such events and reduces the manufacturing loss, which eventually leads to positive customer satisfaction. We propose a machine learning-based algorithm to forecast the obsolescence date of electronic diodes, which has a limitation on the amount of data available. The proposed algorithm overcomes these limitations in two ways. First, an unsupervised clustering algorithm is applied to group the data based on their similarity and build independent machine-learning models specialized for each group. Second, a hybrid method including several reliable techniques is constructed to improve the prediction accuracy and overcome the limitation of the lack of data. It is empirically confirmed that the prediction accuracy of the obsolescence date for the electrical component data is improved through the proposed clustering-based hybrid method. Full article

The abandonment of the built heritage, as a result of functional or technological obsolescence or as a consequence of cultural, social, and economic trends, is steadily increasing. This great number of buildings, worldwide spread, offers a huge opportunity to reduce the environmental impacts related to the construction industry. Nonetheless, the recovery and reuse interventions that require the implementation of residual technological performance, to accommodate new uses, are not always environmentally neutral. Therefore, a new design approach needs to be developed so as to improve the buildings’ technological performance and enhance resources and energy already incorporated in buildings. The circular economy principles in the building sector, performance-based building design together with downcycling and upcycling theories are applied to develop a methodology aiming to reduce the environmental impacts within the rehabilitation and refurbishment design process. Starting from the building analysis phase (historical, material, construction) residual performance is evaluated; then the design phase demonstrates that, according to downcycling and upcycling design strategies applied on building components and materials, it is possible improving the building to the required new uses while minimizing transformations and effectively reducing related environmental impacts. The reduction of environmental impacts depends on a careful assessment of the residual technological and structural performance that the building still provides, by involving limited performance implementations to balance rehabilitation needs and environmental protection goals. Full article

Parts obsolescence has an important impact on the product life cycle, the manufacturing system and the environment leading to operational, logistical, reliability and cost implications. While current resolution models are cost-oriented, multiple studies have revealed that technological obsolescence is strongly involved in the electronic waste problem. In this study, based on academic literature and expert opinions, a sustainable decision framework for obsolescence resolution strategy (ORS) selection is proposed. It consists of economic, environmental, social and technological dimensions, integrating a total of fifteen criteria. Multicriteria decision-making (MCDM) methods are suggested to select the most sustainable solution. A case study was performed where the criteria weights and the alternatives performance were judged by five experts from the fields of environment, economy, human resources and obsolescence and operations management. Results from different MCDM methods were compared to the actual decision to evaluate their effectiveness. Using the suggested framework improved the decision process as integrating sustainability had a drastic impact on the selected strategy and consequently on the company’s performance. In addition to its managerial insights, this paper provides a new research perspective to sustainable and robust obsolescence management to effectively handle the increasing number and severity of obsolete components. Full article

Insurance is a growing economic activity within the construction sector. Homes and buildings are perhaps the most important investment an individual makes in his/her lifetime. Nevertheless, the market for insurance coverage policies applied to the building envelope is in an embryonic stage, mainly due to the lack of knowledge in terms of risk and costs associated to the failure of these elements. This study provides an innovative and methodological approach to the development of an insurance product that targets the obsolescence of building components. In defining a structured approach to the design of insurance policies for buildings, the use of the service life prediction models proposed in this study allows establishing different types of insurance policies with different risk premiums and evaluating different losses and risks accepted by the owners, thus promoting the increase of the patrimonial value of the asset and reducing the risk of premature failure and the uncertainty of the costs of maintenance during its life cycle. Full article

The insurance market deliberately excludes the buildings’ envelope from their insurance policies, neglecting all the damage that can be caused by the degradation process or ageing of the materials. This stance is mainly due to the lack of knowledge in terms of risk and costs associated to the failure of these elements. Even though the building and its elements are the most valuable asset of any owner, most often homeowners do not adopt effective preventive measures to mitigate the deterioration and obsolescence of their assets. This study proposes an innovative methodology for the design of insurance policies for buildings’ envelopes, applied to natural stone facade claddings. The insurance product is defined based on deterministic and stochastic service life prediction models, established through the past degradation history of 142 natural stone claddings analyzed in service conditions in Portugal. Single-parameter (only analyzing the cladding’s age) and multiparameter (encompassing the relevant variables) models are applied in the calculation of the insurance premium. The expected claims are related with the performance of maintenance actions and established according to three degradation levels. The results obtained reveal that an increased knowledge about the insured cladding leads to a reduction of the risk margin and consequently, to a lower annual value of commercial premium paid by a household. This study proposes an innovative solution for tailoring the insurance products, in terms of the risk of failure of the buildings components, as well as the financial charges related with the maintenance of these elements, channeling the risks to the market. Full article