Search Results (74)

Aluminium alloy foams have been widely used due to their excellent strength-to-weight ratio, low density, and outstanding properties such as high energy absorption and effective noise and heat insulation. In this study, aluminium machining chips have been used for foam production as a potential recycling method. The process has involved solution heat treatment followed by artificial ageing. Researchers have been analysing the microhardness of both the foam and the bulk material, as well as examining their microstructures. The maximum microhardness value of the bulk material has been found to be 158 ± 2 HV1 at an ageing temperature of 175 ± 1 °C for 2 ± 0.02 h. For the foams, the highest microhardness of 150 ± 2 HV1 has been achieved after ageing at 150 ± 1 °C for 9 ± 0.02 h. Experimental planning has been carried out using Design Expert software. The optimisation process has identified 150 ± 1 °C for 2 ± 0.02 h as the optimum condition for artificial ageing. Full article

This research explores the relationship between Product Lifecycle Management (PLM) and Industry 4.0 (I4.0) technologies with Integrated Information Management Systems (IIMS) and the impact on the Market Performance (MP) of organisations. A survey was conducted with 106 company managers with experience ranging from the strategic to the operational level of IIMS practices. The data were analysed quantitatively through Exploratory Factorial Analysis (EFA), Confirmatory Factorial Analysis (CFA), and Structural Equation Modelling (SEM). The results indicated that integrating IIMS, PLM, and I4.0 is crucial to improving the effectiveness of organisational processes. However, its direct impacts on MP are more moderate. This shows the need for companies to fully integrate IIMS with PLM and I4.0 technologies, taking advantage of the synergies observed between IoT, Automation, and AI to improve operational efficiency and information security. As for practical and sustainability implications, the research discusses the importance of data optimisation and process management, mediating impacts and investment strategies, training and organisational culture, strategic planning, and the efficient and responsible use of resources. The originality of this work is highlighted by its approach, considering the research context broadly and uniquely. SEM made this approach possible, where the structural model is evaluated entirely, resulting in how the constructs behave based on how they are modelled. In addition, the research contributes to expanding theoretical knowledge and studying the practical applications of the results in business policies. Full article

The increasing demand for smaller batch sizes and mass customisation in production poses considerable challenges to logistics and manufacturing efficiency. Conventional methodologies are unable to address the need for expeditious, cost-effective distribution of premium-quality products tailored to individual specifications. Additionally, the reliability and resilience of global logistics chains are increasingly under pressure. Additive manufacturing is regarded as a potentially viable solution to these problems, as it enables on-demand, on-site production, with reduced resource usage in production. Nevertheless, there are still significant challenges to be addressed, including the assurance of product quality and the optimisation of production processes with respect to time and resource efficiency. This article examines the potential of integrating digital twin methodologies to establish a fully digital and efficient process chain for on-site additive manufacturing. This study focuses on wire arc additive manufacturing (WAAM), a technology that has been successfully implemented in the on-site production of naval ship propellers and excavator parts. The proposed approach aims to enhance process planning efficiency, reduce material and energy consumption, and minimise the expertise required for operational deployment by leveraging digital twin methodologies. The present paper details the current state of research in this domain and outlines a vision for a fully virtualised process chain, highlighting the transformative potential of digital twin technologies in advancing on-site additive manufacturing. In this context, various aspects and components of a digital twin framework for wire arc additive manufacturing are examined regarding their necessity and applicability. The overarching objective of this paper is to conduct a preliminary investigation for the implementation and further development of a comprehensive DT framework for WAAM. Utilising a real-world sample, current already available process steps are validated and actual missing technical solutions are pointed out. Full article

Industrial enterprises and their supply chain partners are increasingly seeking methods to optimise production and logistics processes while pursuing sustainable development goals. The complexity and high risk associated with implementing Industry 4.0 technologies calls for structured decision-making support. This study presents a novel multi-criteria evaluation framework that integrates technological, organisational, and sustainability dimensions to support strategic transformation efforts. The proposed model comprises four subspheres of manufacturing, four subspheres of supply chain and logistics, twenty-three emerging technologies, and four sustainability perspectives adapted to industrial contexts. A hybrid MCDM approach combining DEMATEL and PROMETHEE II is applied to identify causal relationships, prioritise technologies, and rank sustainability priorities across different dimensions. The methodology enables companies to determine which technologies should be implemented first and how these relate to broader sustainability objectives. The results provide a structured roadmap for decision-makers, highlighting five key strategic areas for the sustainable implementation of Industry 4.0. In addition to its managerial relevance, the proposed model offers scientific novelty by bridging previously siloed research areas and demonstrating a data-driven approach to transformation planning. Full article

The remanufacturing of end-of-life products is an effective approach to alleviating resource shortages, environmental pollution, and global warming. As the initial step in the remanufacturing process, the quality and efficiency of disassembly have a decisive impact on the entire workflow. However, the complexity of product structures poses numerous challenges to practical disassembly operations. These challenges include not only conventional precedence constraints among disassembly tasks but also sequential dependencies, where interference between tasks due to their execution order can prolong operation times and complicate the formulation of disassembly plans. Additionally, the inherent uncertainties in the disassembly process further affect the practical applicability of disassembly plans. Therefore, developing reliable disassembly plans must fully consider both sequential dependencies and uncertainties. To this end, this paper employs a chance-constrained programming model to characterise uncertain information and constructs a multi-objective sequence-dependent disassembly line balancing (MO-SDDLB) problem model under uncertain environments. The model aims to minimise the hazard index, workstation time variance, and energy consumption, achieving a multi-dimensional optimisation of the disassembly process. To efficiently solve this problem, this paper designs an innovative multi-objective adaptive large neighbourhood search (MO-ALNS) algorithm. The algorithm integrates three destruction and repair operators, combined with simulated annealing, roulette wheel selection, and local search strategies, significantly enhancing solution efficiency and quality. Practical disassembly experiments on a lithium-ion battery validate the effectiveness of the proposed model and algorithm. Moreover, the proposed MO-ALNS demonstrated a superior performance compared to other state-of-the-art methods. On average, against the best competitor results, MO-ALNS improved the number of Pareto solutions (NPS) by approximately 21%, reduced the inverted generational distance (IGD) by about 21%, and increased the hypervolume (HV) by nearly 8%. Furthermore, MO-ALNS exhibited a superior stability, providing a practical and feasible solution for disassembly optimisation. Full article

Photovoltaic (PV) energy production in Western countries increases yearly. Its production can be carried out in a highly distributed manner, not being necessary to use large concentrations of solar panels. As a result of this situation, electricity production through PV has spread to homes and open-field plans. Production varies substantially depending on the panels’ location and weather conditions. However, the integration of PV systems presents a challenge for both grid planning and operation. Furthermore, the predictability of rooftop-installed PV systems can play an essential role in home energy management systems (HEMS) for optimising local self-consumption and integrating small PV systems in the low-voltage grid. In this article, we show a novel methodology used to predict the electrical energy production of a 48 kWp PV system located at the Campus Feuchtwangen, part of Hochschule Ansbach. This methodology involves hybrid time series techniques that include state space models supported by artificial intelligence tools to produce predictions. The results show an accuracy of around 3% on nRMSE for the prediction, depending on the different system orientations. Full article

This paper presents an analysis of energy use and sector coupling in a local energy community using a model based on energy cost centres (ECCs), functional units for decentralised responsibility and optimisation of energy use within defined system boundaries. The ECC model enables structured identification and optimisation of energy and material flows in complex industrial and urban settings. It was applied to a case study involving an energy-intensive steel plant and its integration with the surrounding community. The study assessed the potential for renewable electricity production (7914 MWh annually), green hydrogen generation, battery storage, and the reuse of 11,440 MWh of excess heat. These measures could offset 9598 MWh of grid electricity through local production and savings, reduce natural gas use by 4,116,850 Nm³, and lower CO₂ emissions by 10,984 tonnes per year. The model supports strategic planning by linking sectoral actions to measurable sustainability indicators. It is adaptable to data availability and stakeholder engagement, allowing both high-level overviews and detailed analysis of selected ECCs. Limitations include heterogeneous data sources, uneven stakeholder participation, and the need for refinement of sub-models. Nonetheless, the approach offers a replicable framework for integrated energy planning and supports the transition to sustainable, decentralised energy systems. Full article

This article aims to review the industrial applications of AI-based intelligent system algorithms in the manufacturing sector to find the latest methods used for sustainability and optimisation. In contrast to previous review articles that broadly summarised existing methods, this paper specifically emphasises the most recent techniques, providing a systematic and structured evaluation of their practical applications within the sector. The primary objective of this study is to review the applications of intelligent system algorithms, including metaheuristics, evolutionary algorithms, and learning-based methods within the manufacturing sector, particularly through the lens of optimisation of workflow in the production lines, specifically Job Shop Scheduling Problems (JSSPs). It critically evaluates various algorithms for solving JSSPs, with a particular focus on Flexible Job Shop Scheduling Problems (FJSPs), a more advanced form of JSSPs. The manufacturing process consists of several intricate operations that must be meticulously planned and scheduled to be executed effectively. In this regard, Production scheduling aims to find the best possible schedule to maximise one or more performance parameters. An integral part of production scheduling is JSSP in both traditional and smart manufacturing; however, this research focuses on this concept in general, which pertains to industrial system scheduling and concerns the aim of maximising operational efficiency by reducing production time and costs. A common feature among research studies on optimisation is the lack of consistent and more effective solution algorithms that minimise time and energy consumption, thus accelerating optimisation with minimal resources. Full article

Single- and small-batch production requires flexible production control to maximise machine reliability and minimise delivery delays. Existing planning approaches often do not take into account the dynamic production conditions of these environments, where machine breakdowns, variable order volumes and short-term changes lead to inefficiencies. This paper presents an enhanced job-shop scheduling model that integrates preventive maintenance strategies directly into production control. Using a mixed-integer programming approach, machine allocation and maintenance measures are optimised simultaneously in order to reduce unplanned downtimes and make efficient use of free time slots. The model is implemented in Python with Pyomo (Python 3.13.0 and Pyomo Version: 6.8.0) and validated using a scenario. The results show that an adaptive maintenance strategy contributes significantly to reducing machine downtimes without compromising production output. Visualisations support users in their decision-making by clearly presenting machine availability, maintenance slots and production orders. The approach is specifically designed for production and maintenance planners who need efficient and adaptable scheduling in volatile production environments. Compared to traditional maintenance models, this approach improves schedule adherence and optimises resource utilisation by dynamically linking production control and maintenance planning. Full article

An increasing lack of raw materials, resource depletion, environmental impacts and other concerns have changed the way the population faces garbage disposal and municipalities implement waste management strategies. The aggravated global rise in municipal solid waste (MSW) generation has led to a new stage in full development, with objectives and targets set by the European Union regarding reducing the production of MSW. The targets also include the increasing selective collection, reuse, recycling and recovery (organic and energetic) of the waste produced. At the same time, the European Union has also set caps for the greenhouse gas emissions and for increasing the use of alternative renewable energy sources. In this context, one of the sources of renewable energy that is beginning to be used to produce electricity in our country is biogas. Finally, AD promotes the development of a circular economy. The present study introduces the formalism for a computer application that simulates the technical–economic behaviour of the short-term management of biogas for the conversion of electricity, and the mathematical model is formulated as a mathematical programming problem with constraints. A simulation for a case study of short-term management is given using the real landfill data available. The case study proves the ability of the LandGEM, despite some authors’ support that the Tabasaran–Rettenberger model provided a more reliable estimate, especially when compared to actual landfill data. The present paper is a contribution to the optimisation of the management of electricity from the use of biogas, namely the second phase of the Strategic Plan for Urban Waste. In addition to complying with the legislation in force, the use of biogas to produce electricity is an added value for the concessionaires of waste treatment and final destination units, as this alternative energy source can provide not only self-sufficiency in electricity for these units but also the export of surplus energy to the National Electricity Grid, thus contributing to the self-sustaining management and energy flexibility that is intended for these infrastructures. Full article

People-environment interactions within nature-based solutions (NBS) are not always understood. This has implications for communicating the benefits of NBS and for how we plan cities. We present a framework that highlights a duality in NBS. The NBS as an asset includes both natural capital and human-centred capital, including organisational structures. NBS also exist as a system within which people are able to interact. Temporal and spatial scales moderate the benefits that NBS provide, which in turn are dependent on the scale at which social processes operate. Co-production and equity are central to the interactions among people and institutions in the design, use and management of NBS, and this requires clear communication. Drawing on ideas from culture-based development (CBD), we suggest an approach to communicate the benefits of NBS in a neutral but effective way. We propose guidelines for planning NBS that allow the optimisation of NBS locations and designs for particular outcomes. Full article

This paper is aimed at understanding the possibility of applying ergonomics in the reorganisation of the work environment with the aim to improve working conditions and to increase the productivity of the examined workplace in an industrial company. Due to constant changes in markets, industrial companies are forced to seek new methods and paradigms for planning and managing innovations in order to ensure their competitiveness. An essential part of this process is the emphasis on improving production processes, where various methods with different focuses can be used. These methods not only optimise work processes, but also allow companies to minimise the resources needed for production and increase overall productivity. Another useful tool for industrial enterprises can be ergonomic rationalisation. The importance of ergonomics in improving employee working conditions and production process efficiency has been the subject of studies promoting various concepts. This study focuses in particular on examining the possibility of extending the outputs obtained by the REFA method to outputs obtained through ergonomic analysis. To achieve the objectives of the paper, the case study method was chosen, given that it was necessary to apply the REFA method in combination with ergonomic rationalisation in the specific conditions of the industrial company for the possibility of identifying bottlenecks in the production process from the point of view of its productivity, efficiency, and workforce involvement. Based on the results, it was possible to propose measures to increase the efficiency of the production process while respecting the principles of ergonomics. As part of the solution, the author team concluded that the findings obtained by combining both methods do not show significant differences, but rather complement each other and provide a broader view of the issue under study. At the same time, it can be stated that the solution cannot be considered definitive due to possible dynamic changes in the industrial environment (changes in the composition of the workforce and the scale of production and evolving technology, e.g., AI). The subject of future research will be to adapt the applied combination of methods so that it is universally applicable to any industrial sector, with minimal required adjustments to meet the specifics of individual industries. Full article

Atopic dermatitis is prevalent in humans (hAD) and dogs (cAD) and profoundly impacts the patients’ quality of life. The increasing number of new drugs in development for atopic dermatitis indicates both the need and potential for precision medicine to generate an optimised benefit–risk therapeutic plan. Cannabidiol (CBD), known for its potential anti-inflammatory and antipruritic properties, shows promise in hAD and cAD management, prompting the exploration of cannabinoids (CBs) and CBD as therapeutic tools. In fact, encouraging results on the benefits of using CBD in cAD have been published, along with safety evaluations that reveal that CBD is generally well tolerated in dogs. However, limited placebo-controlled trials and dosage variations in dogs pose barriers that hinder definitive conclusions. Challenges in product stability, inconsistent formulations, and legal ambiguities highlight the need for standardised CBD-based products for both research and commercial uses. The complex legal landscape further complicates accessibility and regulation. Despite these challenges, CBD is emerging as a potential avenue for cAD management, urging further high-quality research, standardised formulations, and legal clarity. This brief review provides valuable insights into the therapeutic potential of CBs and CBD in cAD, compared to hAD, emphasising the importance of rigorous research and unambiguous regulation for successful integration into veterinary dermatology. Full article

Background/Objectives: Many commercial light-emitting diode (LED) devices are available for consumer home usage. The performance characteristics in respect to the dosimetry of many of the devices, currently on direct sale to the public, have not been subject to formal appraisal. In order to ‘bridge the gap’ between the evidence-based photobiomodulation therapy (PBMT) community and other interested parties, an evaluation is made of a selection of torch type hand-held LED PBMT products currently available for home use. Methods: Five randomly chosen intra-oral and hand-held LED PBMT devices were selected. The optical delivery parameters of the devices were measured, including the beam divergence angle, surface area exposure as well as the output power at the level of the LEDs. The surface and sub-surface temperature changes in porcine tissue samples were assessed under standardised conditions. The manufacturer’s patient instructions were correlated to the measured optical parameters. Calculations were made of irradiance and surface radiant exposure. Consumer satisfaction ratings and feedback data were collated, and a relevant statistical analysis conducted. Results: The results were heterogeneous with a wide range of applied wavelengths, output power and irradiance. Power output stability was variable, and, together with a wide beam divergence angle of 74°, the manufacturer’s directions for dosimetry were found to be inconsistent with an accurate dose delivery. Conclusions: The manufacturer’s proposed dosimetry fails to consider the relevance of the beam divergence angle and optical attenuation in view of the scatter and absorption. Appropriate instructions on how best to gain and optimise an acceptable clinical outcome were inconsistent with an evidence-based approach. Subject to validation by well-planned clinical trials, the concept of home PBMT may open interesting new therapeutic approaches. Full article

Most nations are shifting towards renewable energy sources to reduce energy-related emissions and achieve their net zero emissions targets by mid-century. Consequently, many attempts have been made to invest in clean, accessible, inexpensive, sustainable and reliable renewable energy sources while reducing dependency on fossil fuels. Recently, the production of biogas and upgrading it to produce biomethane is considered a sustainable way to reduce emissions from natural gas consumption. However, uncertainties in the biomass supply chain and less attention to decarbonising the natural gas grid have led to fewer investors in biomethane injection projects. Thus, researchers have applied Geographic Information System (GIS) as the best decision-making tool with spatial analytical and optimisation capabilities to address this issue. This study aims to review GIS-based applications on planning and optimising the biomass supply chain. Accordingly, this review covers different GIS-based biomass assessment methods with the evaluation of feedstock types, GIS-based approaches on selecting and optimising bioenergy plant locations and GIS-based applications on facilitating biomethane injection projects. This review identified four major biomass assessment approaches: Administrative division-based, location-based, cluster-based and grid-based. Sustainability criteria involved in site selection were also discussed, along with suitability and optimality techniques. Most of the optimising studies investigated cost optimisation based on a single objective. However, optimising the whole supply chain, including all operational components of the biomass supply chain, is still seldom investigated. Furthermore, it was found that most studies focus on site selection and logistics, neglecting biomethane process optimisation. Full article