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The purpose of this paper is to cut down energy consumption and eliminate production waste on mixed-model assembly lines. Therefore, a supermarket integrated dynamic cyclic kitting system with the application of electric vehicles (EVs) is introduced. The system resorts to just-in-time (JIT) and segmented sub-line assignment strategies, with the objectives of minimizing line-side inventory and energy consumption.

Hybrid opposition-based learning and variable neighborhood search (HOVMQPSO), a multi-objective meta-heuristics algorithm based on quantum particle swarm optimization is proposed, which hybridizes opposition-based learning methodology as well as a variable neighborhood search mechanism. Such algorithm extends the search space and is capable of obtaining more high-quality solutions.

Computational experiments demonstrated the outstanding performance of HOVQMPSO in solving the proposed part-feeding problem over the two benchmark algorithms non-dominated sorting genetic algorithm-II and quantum-behaved multi-objective particle swarm optimization. Additionally, using modified real-life assembly data, case studies are carried out, which imply HOVQMPSO of having good stability and great competitiveness in scheduling problems.

The feeding problem is based on static settings in a stable manufacturing system with determined material requirements, without considering the occurrence of uncertain incidents. Current study contributes to assembly line feeding with EV assignment and could be modified to allow cooperation between EVs.

The dynamic cyclic kitting problem with sub-line assignment applying EVs and supermarkets is solved by an innovative HOVMQPSO, providing both novel part-feeding strategy and effective intelligent algorithm for industrial engineering.

The research aims to investigate the impact of thermo-mechanical aging on SBR under cyclic-loading. By conducting experimental analyses and developing a 3D finite element analysis (FEA) model, it seeks to understand chemical and physical changes during aging processes. This research provides insights into nonlinear mechanical behavior, stress softening and microstructural alterations in SBR compounds, improving material performance and guiding future strategies.

This study combines experimental analyses, including cyclic tensile loading, attenuated total reflection (ATR), spectroscopy and energy-dispersive X-ray spectroscopy (EDS) line scans, to investigate the effects of thermo-mechanical aging (TMA) on carbon-black (CB) reinforced styrene-butadiene rubber (SBR). It employs a 3D FEA model using the Abaqus/Implicit code to comprehend the nonlinear behavior and stress softening response, offering a holistic understanding of aging processes and mechanical behavior under cyclic-loading.

This study reveals significant insights into SBR behavior during thermo-mechanical aging. Findings include surface roughness variations, chemical alterations and microstructural changes. Notably, a partial recovery of stiffness was observed as a function of CB volume fraction. The developed 3D FEA model accurately depicts nonlinear behavior, stress softening and strain fields around CB particles in unstressed states, predicting hysteresis and energy dissipation in aged SBRs.

This research offers novel insights by comprehensively investigating the impact of thermo-mechanical aging on CB-reinforced-SBR. The fusion of experimental techniques with FEA simulations reveals time-dependent mechanical behavior and microstructural changes in SBR materials. The model serves as a valuable tool for predicting material responses under various conditions, advancing the design and engineering of SBR-based products across industries.

This paper aims to address the development and implementation of “AltPrint,” a slicing algorithm based on a new filling process planning from a variation in the deposited material geometry. AltPrint enables changes in the extruded material flow toward local variations in stiffness. The technical feasibility evaluation was conducted experimentally by fused filament fabrication (FFF) process of snap-fit subjected to a mechanical cyclical test.

The methodology is based on the estimation of the parameter E from the mathematical relationships among the variation of the material in the material flow, nozzle geometry and extrusion parameters. Calibration, validation and analysis of the printed specimens were divided into two moments, of which the first refers to the material responses (flexural and dynamic mechanical analysis) and the second involves the analysis of the printed components with localized flow properties (for estimating the response to cyclic loading). Finite element analysis assisted in the comparison of two snap-fit geometries, one traditional and one generated by AltPrint. Finally, three examples of compliant mechanisms were developed to demonstrate the potential of the algorithm in the generation of functional prototypes.

The contribution of AltPrint is the variable fill width integrated with the slicing software that varies the print parameters in different regions of the object. The alternative extrusion method based on material rate variation was conceived as an “open software” available in GitHub platform, hence, open manufacturing with initial focus on desktop 3D printer based on FFF. The slicing method provides deposited variable-width segments in an organized and replicable filling strategy, resulting in mechanical properties variations in specific regions of a part. It was implemented and evaluated experimentally and indicated potential applications in parts manufactured by the additive process based on extrusion, which requires local flexibilities.

This paper presents a new alternative method for application in an open additive manufacturing context, specifically for additive extrusion techniques that enable local variations in the material flow. Its potential for manufacturing functional parts, which require flexibility due to cyclic loading, was demonstrated by fabrication and experimental evaluations of parts made in acrylonitrile butadiene styrene filament. The changes proposed by AltPrint enable geometric modifications in the response of the printed parts. The proposed slicing and filling control of parameters is inserted in a context of design for additive manufacturing and shows great potential in the area of product design.

Each stage in disaster management faces different challenges concerning information gathering, sharing, interpretation and dissemination. However, a comprehensive understanding of different information and communication technology (ICT) systems utilised for humanitarian disaster management is limited. Therefore, the paper follows a systems thinking approach to examine ten major man-made and/or natural disasters to comprehend the influence of ICT systems on humanitarian relief operations.

A longitudinal, multi-case study captures the use of ICT tools, stakeholders involvement, disaster stages and zones of operations for relief operations over the past two decades. A systems thinking approach is utilised to draw several inferences and develop frameworks.

Multiple ICT tools such as geographic information systems, online webpages/search engines, social media, unmanned aerial vehicles/robots and artificial intelligence are used for rapid disaster response and mitigation. Speed and coordination of relief operations have significantly increased in recent years due to the increased use of ICT systems.

Secondary data on the past ten disasters is utilised to draw inferences. The developed ICT-driven model must be validated during upcoming humanitarian relief operations.

A holistic understanding of a complex inter-relationship between influential variables (stakeholders, disaster stages, zones of operation, ICT systems) is beneficial for effectively managing humanitarian disasters.

Broadly classifying the ICT systems into surveillance, decision support and broadcasting systems, a novel ICT-enabled model for humanitarian relief operations is developed.

Looked after children (LAC) are criminalised at five times the rate of children in the general population. Children in contact with both child welfare and child justice systems have higher rates of neurodisability and substance use problems, and LAC in general have high rates of school exclusion, homelessness and unemployment. This study aims to understand whether these factors persist in LAC who are in prison as adults.

Administrative data collected by the Do-IT profiler screening tool in a prison in Wales, UK, were analysed to compare sentenced prisoners who were LAC (n = 631) to sentenced prisoners who were not LAC (n = 2,201). The sample comprised all prisoners who were screened on entry to prison in a two-year period.

Prisoners who were LAC scored more poorly on a functional screener for neurodisability (effect size = 0.24), and on four self-report measures capturing traits of dyslexia (0.22), attention-deficit hyperactivity disorder (0.40), autism spectrum disorders (0.34) and developmental co-ordination disorder (0.33). Prisoners who were LAC were more likely to have been to a pupil referral unit (0.24), have substance use problems (0.16), be homeless or marginally housed (0.18) and be unemployed or unable to work due to disability (0.13).

This study uniquely contributes to our understanding of prisoners who were LAC as a target group for intervention and support with re-integration into the community upon release. LAC in prison as adults may require additional interventions to help with employment, housing and substance use. Education programmes in prison should screen for neurodisability, to develop strategies to support engagement.

The construction workforce plays a crucial role in the successful delivery of any construction project and, eventually, the performance of any construction organisation. Effectively managing these workforces becomes crucial. However, past studies have shown that workforce management within the construction industry has been on the back foot, with workers being seen as resources required to deliver construction projects. This situation begs the need for a construction workforce management model that can be tailored to an organisation’s situation and adopted to manage workers and improve organisational performance effectively. To this end, this chapter reviewed existing workforce management theories, models, and practices to develop a suitable approach towards managing the construction workforce. Ultimately, a strategic workforce management with a classical view using a soft workforce management approach that embraces employees’ empowerment and development through trust was proposed. Five major practices that best suit the soft workforce management approach were identified as key constructs in the proposed construction workforce management model.

This paper seeks to assess the capabilities and maturity of supply chain planning and product quality management systems implemented by the dairy industries in three different countries: Russia, Kazakhstan, and Lithuania.

Through a systematic analysis of statistical information, the descriptors of the logistics supply chain efficiency were identified. Directions for dairy supply chain management improvement were also highlighted. The study uses secondary statistics from open sources as a basis for the comparative analysis across a range of indicators, including the Logistics Performance Index (LPI), the dairy products quantity, the production volume of milk and dairy products, and other indicators characterizing the dairy industry.

The results of this study suggest the inconsistency and narrowness of single indexes and ranking, which are traditionally used to evaluate the logistics system. LPI values confirmed that the internal efficiency of the Lithuanian logistics system exceeds similar systems in Russia and Kazakhstan.

In this paper, ways to improve supply chain management of dairy products in the context of globalization have been determined, the prerequisites for the formation of the perishable goods market according to the balance of supply and demand and the institutional mechanism of this process, which represents important information for all interested economic agents, have been analyzed.

The proposed approach points to the importance of having detailed information on the supply chain infrastructure and the need to introduce a single information space based on modern information and communication technologies.

Being acquainted with both lean and action learning in theory and in practice, this study finds that the theoretical complementarity of these two research streams has traditionally been underexploited. In this conceptual paper, this study aims to advance the theoretical understanding of lean by exploring the complementarity of lean thinking and action learning leading to a proposed integrated theory of these two research streams. Target audience is the operations management research community.

By deliberately adopting a process of theorising, this paper explores, reflects upon and combines individual experiences of researching, teaching and engaging in lean and action learning as operations management scholars.

Having taken a gemba walk through the literature and practices of lean and action learning, this study views and notices a systematic and complementary relationship between the two domains. The overlapping theoretical and practical complementarities of lean and action learning suggest that these two research streams are ripe for synthesis into an integrated theory. This finding provides an opportunity to (1) progress towards an integrative design of interventions leading to more sustainable lean system adoptions and (2) add new depth to our theoretical explanation of the success and failures of lean system adoptions.

This paper contributes an original integrated theory perspective on lean and action learning.

While steady-state analysis is useful, it does not consider the inherent transient characteristics of repairable systems' behavior, especially in systems that have relatively short life spans, or when their transient behavior is of special concern such as the motivating example used in this paper, military systems. Therefore, a maintenance policy that considers both transient and steady-state availability and aims to achieve the best trade-off between high steady-state availability and rapid stabilization is essential.

This paper studies the transient behavior of system availability under the Kijima Type II virtual age model. While such systems achieve steady-state availability, and it has been proved that deploying preventive maintenance (PM) can significantly improve its steady-state availability, this improvement often comes at the price of longer and increased fluctuating transient behavior, which affects overall system performance. The authors present a methodology that identifies the optimal PM policy that achieves the best trade-off between high steady-state availability and rapid stabilization based on cost-availability analysis.

When the proposed simulation-based optimization and cost analysis methodology is applied to the motivating example, it produces an optimal PM policy that achieves an availability–variability balance between transient and steady-state system behaviors. The optimal PM policy produces a notably lower availability coefficient of variation (by 11.5%), while at the same time suffering a negligible limiting availability loss of only 0.3%. The new optimal PM policy also provides cost savings of about 5% in total maintenance cost. The performed sensitivity analysis shows that the system's optimal maintenance cost is sensitive to the repair time, the shape parameter of the Weibull distribution and the downtime cost, but is robust with respect to changes in the remaining parameters.

Most of the current maintenance models emphasize the steady-state behavior of availability and neglect its transient behavior. For some systems, using steady-state availability as the sole metric for performance is not adequate, especially in systems that have relatively short life spans or when their transient behavior affects the overall performance. However, little work has been done on the transient analysis of such systems. In this paper, the authors aim to fill this gap by emphasizing such systems and applications where transient behavior is of critical importance to efficiently optimize system performance. The authors use military systems as a motivating example.

This study has covered many types of solar-powered air-conditioning systems that may be used as an alternative to traditional electrically powered air-conditioning systems in order to reduce energy usage. Solar adsorption air cooling is a great alternative to traditional vapor compression air-conditioning. Solar adsorption has several advantages over traditional vapor-compression systems, including being a green cooling technology which uses solar energy to drive the cycle, using pure water as an eco-friendly HFC-free refrigerant, and being mechanically simple with only the magnetic valves as moving parts. Several advancements and breakthroughs have been developed in the area of solar adsorption air-conditioners during the previous decade. However, further study is required before this technology can be put into practise. As a result, this book chapter highlights current research that adds to the understanding of solar adsorption air-conditioning technologies, with a focus on practical research. These systems have the potential to become the next iteration of air-conditioning systems, with the benefit of lowering energy usage while using plentiful solar energy supplies to supply the cooling demand.