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Pallets ensure efficient processes in logistics and are exchanged between the different actors, while passing through various supply chains several times. In common practice, the exchange is often not directly carried out on site, e.g. due to a lack of time, so that additional trips and new pallet purchases become necessary. To reduce these negative effects, a digital cross-actor platform is designed, and its potential is investigated.

The authors developed an agent-based simulation model with mathematical optimization. Using experience from practitioners, as well as real-world datasets which were analyzed, the authors ensure a realistic model of the pallet exchange system in Germany.

The authors demonstrated that, with the help of this platform concept, transport routes can be shortened, debts and receivables can partly be equaled out through balancing, and the quantity of pallets in the overall system can be reduced.

The results are not directly transferable to pallet exchange systems in other countries without considering their general settings.

Digital networking increases the efficiency of the existing pallet exchange system. Even small collaborations prove to be reasonable.

The authors developed new mechanisms for a digital pallet exchange platform, which takes on the role of a central planning instance, in addition to recording pallet receivables and debts. It enables the planning of the commodity flow of empty pallets, which are transported by the forwarders on regular routes, and distributed between the platform participants.

The purpose of this study is an assessment of the existing roughness models to simulate the flow in the narrow gap between corotating and rough disks. A specific configuration of the flow through the gap, which forms a minichannel with variable cross sections and rotating walls, makes it a complex problem and, therefore, worth discussing in more detail.

Two roughness models were examined, the first one was based on the wall function modification by application of the shift in the dimensionless velocity profile, and the second one was based on the correction of turbulence parameters at the wall, proposed by Aupoix. Due to the lack of data to validate that specific case, the approach to deal with was selected after a systematic study of reported test cases. It started with a zero-pressure-gradient boundary layer in the flow over a flat plate, continued with flow through minichannels with stationary walls, and finally, focused on the flow between corotating discs, pertaining each time to smooth and rough surfaces.

The limitations of the roughness models were highlighted, which make the models not reliable in the application to minichannel flows. It concerns turbulence models, near-wall discretization and roughness approaches. Aupoix’s method to account for roughness was selected, and the influence of minichannel height, mass flow rate, fluid properties and roughness height on the velocity profile between corotating discs in both smooth and rough cases was discussed.

The originality of this study is the evaluation and validation of different methods to account for the roughness in rotating mini channels, where the protrusions can cover a substantial part of the channel. Flow behavior and performance of different turbulence models were analyzed as well.

Purpose: The study aims to explore the wider acceptance of blockchain technology and growing faith in this technology among all business domains to mitigate the chances of fraud in various sectors.

Design/Methodology/Approach: The authors focus on studies conducted during 2015–2022 using keywords such as blockchain, fraud detection and financial domain for Systematic Literature Review (SLR). The SLR approach entails two databases, namely, Scopus and IEEE Xplore, to seek relevant articles covering the effectiveness of blockchain technology in controlling financial fraud.

Findings: The findings of the research explored different types of business domains using blockchains in detecting fraud. They examined their effectiveness in other sectors such as insurance, banks, online transactions, real estate, credit card usage, etc.

Practical Implications: The results of this research highlight (1) the real-life applications of blockchain technology to secure the gateway for online transactions; (2) people from diverse backgrounds with different business objectives can strongly rely on blockchains to prevent fraud.

Originality/Value: The SLR conducted in this study assists in the identification of future avenues with practical implications, making researchers aware of the work so far carried out for checking the effectiveness of blockchain; however, it does not ignore the possibility of zero to less effectiveness in some businesses which is yet to be explored.

316 L stainless steel alloy is potentially the most used material in the selective laser melting (SLM) process because of its versatility and broad fields of applications (e.g. medical devices, tooling, automotive, etc.). That is why producing fully functional parts through optimal printing configuration is still a key issue to be addressed. This paper aims to present an entirely new framework for simultaneously reducing surface roughness (SR) while increasing the material processing rate in the SLM process of 316L stainless steel, keeping fundamental mechanical properties within their allowable range.

Considering the nonlinear relationship between the printing parameters and features analyzed in the entire experimental space, machine learning and statistical modeling methods were defined to describe the behavior of the selected variables in the as-built conditions. First, the Box–Behnken design was adopted and corresponding experimental planning was conducted to measure the required variables. Second, the relationship between the laser power, scanning speed, hatch distance, layer thickness and selected responses was modeled using empirical methods. Subsequently, three heuristic algorithms (nonsorting genetic algorithm, multi-objective particle swarm optimization and cross-entropy method) were used and compared to search for the Pareto solutions of the formulated multi-objective problem.

A minimum SR value of approximately 12.83 μm and a maximum material processing rate of 2.35 mm³/s were achieved. Finally, some verification experiments recommended by the decision-making system implemented strongly confirmed the reliability of the proposed optimization methodology by providing the ultimate part qualities and their mechanical properties nearly identical to those defined in the literature, with only approximately 10% of error at the maximum.

To the best of the authors’ knowledge, this is the first study dealing with an entirely different and more comprehensive approach for optimizing the 316 L SLM process, embedding it in a unique framework of mechanical and surface properties and material processing rate.

This paper aims to deal with a real-life strategic conflict in joint operations (JOs) for facility location decision and planning in an oil and gas field that stretches over two countries and tries to develop a basis for mitigating such conflict.

This paper develops a novel approach using integer linear programming (ILP) to determine optimal facility location considering technical, economic and environmental factors. Strategic decision-making in JOs is also influenced by business priorities of individual partner, sociopolitical issues and other covert factors. The cost-related quantitative factors are normalized using inverse normalization function as these are to be minimized, and qualitative factors that are multi-decision-making criteria are maximized, thus transforming both qualitative and quantitative factors as a single objective of maximization in ILP model.

The model identifies the most suitable facility location based on a wide range of factors that would provide maximum benefit in the long term, which will help decision-makers and managers.

The model can be expanded incorporating other quantitative and qualitative factors such as tax incentives by the government, local bodies and government regulations.

The applicability of the model is not limited to JOs or oil/gas field, but is applicable to a wide range of sectors.

The model is transparent and based on rational and scientific basis, which would help in building consensus among the dissenting parties and aid in mitigating strategic conflict. Such type of model for mitigating strategic conflict has not been reported/used before.

The purpose of this study is to determine the material extrusion (MEX) printability envelope of a new kind of low-viscosity powder-binder feedstocks using rheological properties.

Formulation of 13 feedstocks (variation of solid loading 60–67 Vol.% and thickening agent proportion 3–15 Vol.%) that were characterized and printed at different temperatures.

Three rheological models were successfully used to define the viscosity envelope, producing stable and defect-free printing. At a shear deformation rate experienced by the feedstock in the nozzle ranging from 100 to 300 s^–1, it was confirmed that metal injection molding (MIM) feedstocks exhibiting a low viscosity between 100 and 150 Pa s could be printed using an extrusion temperature as low as 85 °C.

MEX can be used in synergy with MIM to accelerate mold development for a new injected part or simply as a replacement for MIM when the cost of the mold becomes too high for very small production volumes.

Correlation between the rheological properties of this new generation of low-viscosity feedstocks and MEX printability has been demonstrated for the first time.

As the core technology of blockchain, various consensus mechanisms have emerged to satisfy the demands of different application scenarios. Since determining the security, scalability and other related performance of the blockchain, how to reach consensus efficiently of consensus mechanism is a critical issue in the blockchain.

The paper opted for a research overview on the blockchain consensus mechanism, including the consensus mechanisms' consensus progress, classification and comparison, which are complemented by documentary analysis.

This survey analyzes solutions for the improvement of consensus mechanisms in blockchain that have been proposed during the last few years and suggests future research directions around consensus mechanisms. First, the authors outline the consensus processes, the advantages and disadvantages of the mainstream consensus mechanisms. Additionally, the consensus mechanisms are subdivided into four types according to their characteristics. Then, the consensus mechanisms are compared and analyzed based on four evaluation criteria. Finally, the authors summarize the representative progress of consensus mechanisms and provide some suggestions on the design of consensus mechanisms to make further advances in this field.

This paper summarizes the future research development of the consensus mechanisms.

The purpose of this research is to (1) identify factors affecting food choices of young adults in Canada based on environmental perceptions, personal and behavioral factors as determinants of eating behaviors; (2) segment Canadian young adults based on the importance of the identified factors in their food choices.

An online survey was administered to Canadians aged between 18 and 24 to collect data on socio-demographic factors and eating behaviors (N = 297). An exploratory factor analysis (EFA) was used to identify the main factors affecting eating behaviors in young adults, followed by K-means clustering to categorize the respondents into consumer segments based on their propensity to agree with the factors.

Six factors were extracted: beliefs (ethical, environmental and personal); familiarity and convenience; joy and experience; food influencers and sociability; cultural identity; and body image. Using these factors, six consumer segments were identified, whereby members of each segment have more similar scores on each factor than members of other segments. The six consumer segments were: “conventional”; “concerned”; “indifferent”; “non-trend follower”; “tradition-follower”; and “eat what you love”.

Identifying major factors influencing eating behaviors and consumer segmentation provides insights on how eating behaviors might be shaped. Furthermore, the outcomes of this study are important for designing effective interventions for shaping eating behaviors particularly improving sustainable eating habits.

In Italy, worker cooperatives (WCs), whose workers hold major control rights over collectively-owned assets, are the leading vehicle for the promotion and development of employee ownership. Worker cooperatives are present in all regions and in most economic sectors, employing about 506,000 workers and generating a turnover of about €22 bn. Despite their history and diffusion, the high prevalence of WCs in Italy is under-researched and -thematised and requires new research.

The paper leverages unpublished primary and secondary data from Centro Studi Legacoop databank, the Aida-Bureau Van Dijk databank and the Cooperative Registry of the Ministry of Economic Development (CRMED) to explain the spread of WCs in Italy.

This paper reveals descriptive statistics of WCs and investigates their distribution across economic sectors and regions, their economic and financial performance and gives an overview of the relevant legislation. The paper indicates that older small- and medium-sized cooperatives located in central and north-eastern Italy perform best economically. However, in recent years, an increasing number of young cooperatives has emerged in South Italy thanks to favourable legislation, cooperative finance and the diffusion of cooperative know-how. Limitations to such results are reported in the conclusions.

The paper sheds light on past and recent development trends of WCs in Italy, highlights their growth in South Italy and revitalises the debate on the drivers, structures and rationales of employee-owned enterprises in Italy. Findings generate implications for research and practice. Given the tendency of WCs to better protect jobs than investor-owned enterprises, the spread of these enterprises may help workers find better and more stable jobs, counter-cyclically mitigating the dangerous effects of macro- and meso-economic fluctuations and instability.

Selective laser melting and electron beam melting processes are well-known for the additive manufacturing of metal parts. Metal powder bed fusion (MPBF) is a common term for them. The MPBF process can empower the manufacturing of intricate shapes by reducing the use of special tools, shortening the supply chain and allowing small batches. However, the MPBF process suffers from many quality issues. In literature, several works are recorded for qualification of the MPBF part. The purpose of this study is to recollect those works done for quality control and report their helpful findings for further research and development.

A systematic literature review was conducted to highlight the major quality issues in the MPBF process and its root causes. Further, the works reported in the literature for mitigation of these issues are classified and discussed in five categories: experimental investigation, finite element method-based numerical models, physics-based analytical models, in-situ control using artificial intelligence (AI) and machine learning (ML) methods and statistical approaches. A comparison is also prepared among these strategies based on their suitability and limitations. Additionally, improvements in MPBF printers are pointed out to enhance the part quality.

Analytical models require less computational time to simulate the MPBF process and need a smaller number of experiments to confirm the results. They can be used as an efficient process parameter planning tool to print metal parts for noncritical applications. The AI-ML based quality control is also suitable for MPBF processes as it can control many processing parameters that may affect the quality of the MPBF part. Moreover, capabilities of MPBF printers like thinner layer thickness, smaller beam diameter, multiple lasers and high build temperature range can help in quality control.

This study converts the piecemeal data on MPBF part qualification methods into interesting information and presents it in tabular form under each strategy. This tabular information provides the basis for further quality improvement efforts in the MPBF process.

This study references researchers and practitioners on recent quality control efforts and their significant findings for a better quality of MPBF part.