Search Results (66)

Engineer-to-order (ETO) manufacturers face persistent cost and complexity challenges driven by product variety, including duplicate components, redundant variants, and inconsistent procurement setups. Although enterprise resource planning (ERP) and product lifecycle management (PLM) systems contain detailed Bills of Materials (BOMs) and procurement records, they typically lack portfolio-wide support for systematic cross-product commonality analysis without substantial manual effort. Structured approaches to design reuse and modularization in ETO contexts exist, but lightweight portfolio-level analytics tools operating on exported enterprise data remain scarce, and companies often still rely on ad hoc spreadsheet analyses. This paper introduces product commonality analysis tools (PCATs) and develops and evaluates one such tool in an action-research collaboration with a European ETO laser manufacturer. The PCAT operates on exported enterprise data to provide interactive portfolio-level views of component reuse and cross-product consistency. Usefulness is evaluated through scenario-based think-aloud usability sessions and a functional comparison against Excel workarounds, standard ERP/PLM reporting, and vendor customizations. The results indicate that a lightweight PCAT can integrate into existing ERP/PLM workflows with minimal disruption and reduce the effort required to prepare reusable portfolio views for engineering and procurement reviews. Full article

A systematic review was conducted on the migration of compounds from plastic containers in the food and pharmaceutical industries, using Web of Science databases and following PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The protocol has been registered with the OSF registry, with the DOI 10.17605/OSF.10/UQ3T2. This review included only review articles in English published within the last fifteen years. Four reviewers independently screened titles and abstracts, discussing inclusion criteria. In this comprehensive evaluation of the information present in an Excel spreadsheet, a substantial number of records were discarded because they were not representative of the topic under study. Following the review process, a total of twenty-eight key records were selected, primarily focusing on migration in the food and pharmaceutical sectors. Of these, twenty-four addressed only food, just two addressed only pharmaceutical sector, and two covered both fields, highlighting limited information on migration in pharmaceuticals, cosmetics, and related products. The analysis emphasized the types of compounds studied, the analytical methods employed, the migration tests conducted, and the toxicity assessments undertaken. The most frequently assessed compounds included phthalates, endocrine disruptors like bisphenol A, and non-intentionally added substances (NIAS). Analytical methods used typically involved pre-treatment steps, such as liquid–liquid or solid-phase extraction, followed by gas or liquid chromatography, depending on compound volatility. Full article

Different crop production scenarios and crop rotation systems should be investigated with lower greenhouse gas (GHG) intensity levels, with it being possible to reach net-zero GHG emissions from grain production farms. This study was divided into three stages—the development of spreadsheets for data acquisition for each crop rotation, calculations of GHG emissions based on IPCC methodologies and specific regional emission factors, and an analysis of the main emissions and sinks sources we evaluated, including the potential for soil and biomass carbon (C) sequestration to offset agricultural emissions. The system C footprints were 2413, 2209, and 2096 kg CO₂eq ha⁻¹ for farms K, M, and G, respectively, demanding estimated C sequestration (soil or biomass) rates of 657, 602, and 571 kg C ha⁻¹ year⁻¹ to offset all emissions of agricultural phases. Mitigating practices can reduce GHG emissions, but compensation via sequestration (soil or biomass C) shall be required to achieve zero GHG emissions. Reserving approximately 10–15% of the farm’s total agricultural production area to plant native trees or eucalyptus in marginal areas or even introducing crop–livestock–forest integration or crop–forest integration systems can offset the GHG emissions of the entire agricultural production phase, considering the potential for soil and biomass C sequestration, showing that it is a feasible option for producing C credit from the agricultural sector. Full article

Most industrial processes depend on heat, electricity, demineralized water, and chemical inputs, which themselves are produced through energy- and resource-intensive industrial activities. In this work, acetic acid (AA) production from syngas (CO, CO₂, and H₂) fermentation is explored and compared against a thermochemical fossil benchmark and other thermochemical/biological processes across four main Key Performance Indicators (KPI)—electricity use, heat use, water consumption, and carbon footprint (CF)—for the years 2023 and 2050 in Portugal and France. CF was evaluated through transparent and public inventories for all the processes involved in chemical production and utilities. Spreadsheet-traceable matrices for hotspot identification were also developed. The fossil benchmark, with all the necessary cascade processes, was 0.64 kg CO_2-eq/kg AA, 1.53 kWh/kg AA, 22.02 MJ/kg AA, and 1.62 L water/kg AA for the Portuguese 2023 energy mix, with a reduction of 162% of the CO₂-eq in the 2050 energy transition context. The results demonstrated that industrial practices would benefit greatly from the transition from fossil to renewable energy and from more sustainable chemical sources. For carbon-intensive sectors like steel or cement, the acetogenic syngas fermentation appears as a scalable bridge technology, converting the flue gas waste stream into marketable products and accelerating the transition towards a circular economy. Full article

The accelerated growth of scientific publications in renowned databases such as Scopus (Elsevier) and Web of Science (Clarivate) has made the identification of unresolved research problems increasingly complex. This challenge is exacerbated by the vast amount of information that must be analyzed, highlighting the imminent need for the application of big data techniques to extract relevant information for researchers, stakeholders in innovation and development, and regulatory policymakers. To address this challenge, this article presents an innovative, structured, and systematic methodology for conducting bibliometric analyses of scientific publications. The proposed approach is designed for researchers who only have an initial research idea, a broad problem context, or a general study area and require methodological tools to precisely define their research problem. The methodology follows a recommended flowchart-guided process, leveraging open-source tools such as Bibliometrix (R), spreadsheets, and text processing techniques to conduct a comprehensive bibliometric study. This enables the analysis of the intellectual, conceptual, and social structures of a research field, facilitating the identification of research gaps and emerging trends. As a practical application, the proposed methodology was implemented for the 2004–2024 period, within the framework of an applied research project in engineering. This case study aimed to answer key research questions formulated during the study design phase, demonstrating the effectiveness of the approach in systematically analyzing scientific production. Beyond the energy sector and energy systems, this methodology has proven to be adaptable to diverse disciplines, such as health sciences, industrial management, construction, and urban development, provided that relevant databases are accessible. Through this structured approach, researchers can better define their research problems and identify future challenges in various areas of knowledge. Full article

Initially designed as an automated ledger tool, Excel swiftly evolved into a data analytics platform for financial analysts to execute intricate financial analyses. Excel is so commonplace in the financial industry that many do not even consider it a fintech tool. The transformation of Excel from a simple ledger tool to a low-code machine learning (mL) platform is not a traditional focus for fintech. The transformation of Excel into an mL platform will let financial analysts and quantitative analyses quickly evolve financial models in Excel to use advanced mL techniques. The low-code interface lets analysts quickly build predictive models. This paper explores how Excel has evolved into a low-code machine platform for financial applications along with the risks associated with Excel’s new functionality. Full article

Remote teaching has been becoming increasingly important in higher education since the COVID-19 pandemic. Additionally, fast and precise modeling of the main operating values of industrial systems is a key point for production and efficiency calculation. After a review of the main modeling equations of an induction motor, this paper proposes to include them in spreadsheet software in the form of practical work so that readers will improve their level in multiple competency fields, such as data processing, the use of spreadsheet software, deepening understanding of induction motors, classical induction motor testing, and modeling and the use of the models to solve classical electrical engineering issues. Furthermore, the fact that this work was designed to be conducted autonomously and asynchronously gives readers the feeling of freedom, which is very useful for developing their desire to progress by their own means and to do their utmost to succeed in their task. Finally, the provided Excel file, which includes an initial spreadsheet with gaps, allows readers to familiarize themselves with the concepts, experiment with them, and extend the base file to their own topics of interest. This work can serve as a proof of the readers’ ability to succeed in industrial modeling tasks and aid in their employment prospects. Full article

Background: The issue of renewable energy (RE) source intermittency, such as wind and solar, along with the geographically uneven distribution of the global RE potential, makes it imperative to establish an energy transport medium to balance the energy demand and supply areas. A promising energy vector to address this situation is hydrogen, which is considered a clean energy carrier for various mobile and portable applications. Unfortunately, at standard pressure and temperature, its energy content per volume is very low (0.01 kJ/L). This necessitates alternative storage technologies to achieve reasonable capacities and enable economically viable long-distance transportation. Among the hydrogen storage technologies using chemical methods, liquid organic hydrogen carrier (LOHC) systems are considered a promising solution. They can be easily managed under ambient conditions, the H₂ storage/release processes are carbon-free, and the carrier liquid is reusable. However, the evolution of the proposals from the carrier liquid type and catalyst elemental composition point of view is scarcely studied, considering that both are critical in the performance of the system (operational parameters, kinetic of the reactions, gravimetric hydrogen content, and others) and impact in the final cost of the technology deployed. The latter is due to the use of the Pt group elements (PGEs) in the catalyst that, for example, have a high demand in the hydrogen production sector, particularly for polymer electrolyte membrane (PEM) water electrolysis. With that in mind, our objective was to examine the evolution and the focus of the research in recent years related to proposals of LOHCs and catalysts for hydrogenation and dehydrogenation reactions in LOHC systems which can be useful in defining routes/strategies for new participants interested in becoming involved in the development of this technology. Data sources: For this systematic review, we searched the SCOPUS database and forward and backward citations for studies published in the database between January 2011 and December 2022. Eligibility criteria: The criteria include articles which assessed or studied the effect of the type of catalyst, type of organic liquid, reactor design(s)/configuration(s), and modification of the reactor operational parameters, among others, over the performance of the LOHC system (de/hydrogenation reaction(s)). Data extraction and analysis: The relevant data from each reviewed study were collected and organized into a pre-designed table on an Excel spreadsheet, categorized by reference, year, carrier organic liquid, reaction (hydrogenation and/or dehydrogenation), investigated catalyst, and primary catalyst element. For processing the data obtained from the selected scientific publications, the data analysis software Orbit Intellixir was employed. Results: For the study, 233 studies were included. For the liquid carrier side, benzyltoluene and carbazole dominate the research strategies. Meanwhile, platinum (Pt) and palladium (Pd) are the most employed catalysts for dehydrogenation reactions, while ruthenium (Ru) is preferred for hydrogenation reactions. Conclusions: From the investigated liquid carrier, those based on benzyltoluene and carbazole together account for over 50% of the total scientific publications. Proposals based on indole, biphenyl, cyclohexane, and cyclohexyl could be considered to be emerging within the time considered in this review, and, therefore, should be monitored for their evolution. A great activity was detected in the development of catalysts oriented toward the dehydrogenation reaction, because this reaction requires high temperatures and presents slow H₂ release kinetics, conditioning the success of the implementation of the technology. Finally, from the perspective of the catalyst composition (monometallic and/or bimetallic), it was identified that, for the dehydrogenation reaction, the most used elements are platinum (Pt) and palladium (Pd), while, for the hydrogenation reaction, ruthenium (Ru) widely leads its use in the different catalyst designs. Therefore, the near-term initiatives driving progress in this field are expected to focus on the development of new or improved catalysts for the dehydrogenation reaction of organic liquids based on benzyltoluene and carbazole. Full article

For building projects, the manager is responsible for coordinating the work of subcontractors at the construction site. This includes operations, material flows, and storage. In summary, one of their main roles is to ensure smooth team rotation, maintain fluid circulation, and avoid congestion or relaxation on the site. However, traditional tools lack the ability to consider the planning and management of worksite spaces when calculating the execution schedule and critical path. Consequently, three-week planning is usually carried out separately on independent plans, often using spreadsheets. In addition, a construction site is highly dynamic and mobile in nature, and the positioning of resources and workers can change daily. This makes the management of available space even more complex, and effective space management becomes an imperative. To address this challenge, this paper develops visual dynamic artifacts that present different operation types. The methodology and the conceptual framework facilitate the calculation of the Occupancy Rate (OR) that enables construction project managers to create simple yet dynamic spatiotemporal models of the construction schedule. By incorporating factors such as crew turnover and occupancy evolution, managers can simplify the calculation process and effectively optimize construction work by utilizing site occupancy rates. In summary, this paper presents the Dynamic Model of the Occupancy Rate Schedule (DMORS), a methodology developed through design science. This model utilizes created artifacts representing various operation types to ensure accurate calculations of dynamic occupancy by floor and sector in a site. Consequently, it enables the construction of a more realistic schedule based on critical space ideologies. The DMORS enables managers to use the OR for different floors and sectors of a site, allowing for better space management. A proof of concept demonstrates that this tool can enhance the efficiency and productivity of construction projects by optimizing crew schedules and resource allocation based on site OR. Full article

In the context of the growing demand for alternative protein sources with the growth of the human population and increasing ecological awareness, the rearing of yellow mealworm larvae (Tenebrio molitor) is a promising option for the production of sustainable protein. The article presents a comprehensive approach to planning and scheduling the production of yellow mealworm larvae in a small enterprise, focusing on the organizational, technical, and economic aspects of the production process. The production installation, the method of rearing using an automated feeding system, and the monitoring of larvae development were described and an attempt was made to identify the key parameters of the process that affect its efficiency. Particular attention was paid to the calculation algorithm implemented in the spreadsheet, which allows the selection of the production batch size and the frequency of their launch, so as to maximize the available capacity of storage racks for cuvettes. In addition, the article analyses logistical challenges related to the production of larvae, including transport activities in order to meet, among others, the demand for feed. Finally, the estimation of revenues and economic indicators, such as profitability and return on investment, is presented, pointing to the need for further improvements in the production process and cost optimization to achieve favorable financial results. The results of the research emphasize the potential of rearing yellow mealworm larvae as a sustainable source of protein while simultaneously pointing to key areas that require further research and development. Full article

Promoting sustainable consumer behavior is now an obligation under new European legislation, requiring life cycle assessment (LCA) for accurate environmental impact evaluation. Portugal is a key textile producer with an edge in competitiveness in sustainable textile production, driven by electricity-reduced carbon footprints and closed-loop manufacturing. Additionally, while simple spreadsheets can estimate a product’s carbon footprint, openLCA v1.11.0 software, combined with the ecoinvent database, greatly enhances environmental footprint calculations by integrating diverse impact categories that are otherwise difficult to estimate. In this study, openLCA is used to evaluate the environmental footprint of a white T-shirt made in Portugal with 50% recycled cotton from post-industrial wastes combined with 50% organic cotton from Turkey to assist in the design of environmental key performance indicators (KPI). The RECIPE and EF methods (adapted) are used to calculate the environmental impacts and allow aggregation into a single score. The KPI related to the global warming impact is validated using a spreadsheet calculator. We propose an “Envi-Score” based on an A-to-E classification for benchmarking and better communication with the buyers. E is set as the normalized environmental impact of the European benchmark for a mixture of material T-shirts encompassing cradle-to-gate boundaries. The introduction of recycled cotton produced in Portugal proves to be environmentally beneficial over organic and conventional cotton. Organic cotton proves to be beneficial in comparison with conventional cotton for most environmental categories, except for the ones affected by the lower production yield, for example, land use. The hotspots for the main impact categories are identified, and finally, a labeling scheme is proposed to clearly inform about the environmental performance of the products and avoid greenwashing with the “Envi-Score” rate, carbon footprint, land use, and water depletion. Full article

Volkswagen Technical Development (TE) is responsible for all prototype development and prototype production for the Volkswagen brand and has its own logistics department (TE-Logistics). In the logistics of prototype parts in the automotive industry, new versions of prototype parts (henceforth referred to as updating parts) are repeatedly assembled in finished prototype vehicles. These updating parts are stored in warehouses and provided to an assembly site to ensure a timely assembly of the associated prototype vehicles. As the internal warehouse on the company site is not large enough for the high variety of parts, an additional external warehouse in the logistics network is needed. However, since prototype parts are unique, the allocation of the parts in suitable warehouses is particularly important. Currently, the various warehouses and the short-term demands repeatedly lead to reactive transshipments between the warehouses. To this end, we developed an approach for proactive transshipments based on a machine learning forecast and a mixed-integer linear programming model for planning proactive transshipments of parts between the warehouses to minimize transport costs. The model is based on a probability estimation of future demands to anticipate the expected optimal warehouse. After the model had revealed high improvement potential through a case study with real-world data in terms of costs and availability time compared to the current reactive process, we derived decision rules and developed a rule-based heuristic algorithm that leads to the optimal solution for the industrial use case. We implemented the heuristic with a spreadsheet-based decision support system (DSS) for daily transshipment planning. After successful test implementation, TE-Logistics estimated the annual cost savings for transport to be approximately 10%. Full article

Food commodities and energy bills have experienced rapid undulating movements and hikes globally in recent times. This spurred this study to examine the possibility that the shocks that arise from fluctuations of one market spill over to the other and to determine how time-varying the spillovers were across a time. Data were daily frequency (prices of grains and energy products) from 1 July 2019 to 31 December 2022, as quoted in markets. The choice of the period was to capture the COVID pandemic and the Russian–Ukrainian war as events that could impact volatility. The returns were duly calculated using spreadsheets and subjected to ADF stationarity, co-integration, and the full BEKK-GARCH estimation. The results revealed a prolonged association between returns in the energy markets and food commodity market returns. Both markets were found to have volatility persistence individually, and time-varying bidirectional transmission of volatility across the markets was found. No lagged-effects spillover was found from one market to the other. The findings confirm that shocks that emanate from fluctuations in energy markets are impactful on the volatility of prices in food commodity markets and vice versa, but this impact occurs immediately after the shocks arise or on the same day such variation occurs. Full article

The importance of biocatalysis for ecologically sustainable syntheses in the chemical industry and for applications in everyday life is increasing. To design efficient applications, it is important to know the related enzyme kinetics; however, the measurement is laborious and error-prone. Flow reactors are suitable for rapid reaction parameter screening; here, a novel workflow is proposed including digital image processing (DIP) for the quantification of product concentrations, and the use of structured data acquisition with EnzymeML spreadsheets combined with ontology-based semantic information, leading to rapid and smooth data integration into a simulation tool for kinetics evaluation. One of the major findings is that a flexibly adaptive ontology is essential for FAIR (findability, accessibility, interoperability, reusability) data handling. Further, Python interfaces enable consistent data transfer. Full article

Tractor accidents caused by lateral overturning and backward rollover during agricultural activities and general driving are common. In this study, various research cases were analyzed to identify the factors influencing the lateral overturning and backward rollover of tractors and to examine their static and dynamic stability. Studies on the analysis of the major causes of these incidents and evaluation of tractor safety were compiled. Test methods, including actual tests and simulations, were categorized, and the characteristics of lateral overturning and backward rollover safety of tractors in different studies were examined. Additionally, safety improvement measures were proposed by identifying and summarizing the causes of accidents involving agricultural machinery. Tractor safety was evaluated primarily by conducting actual tractor and simulation tests. These tests were classified into field tests, tests on scale models, spreadsheet programs, and 3D simulation programs. The primary causes of lateral overturning and backward rollover were unstable center of gravity, extremely high driving speed, and ground conditions. Given the considerable number of studies dedicated to evaluating tractor safety, various technologies aimed at preventing lateral overturning and backward rollover incidents are expected to be applied to tractors in the future. The production and testing of safe agricultural machinery are expected to contribute to a reduction in accident rates. Full article