Cost Reduction Opportunities Research Articles

Improving Productivity and Reducing Costs in an IT Service Provider: Applying the Lean Six Sigma Methodology

Objective: to present the use of the Six Sigma framework as a framework for IT Governance, in a multinational company that operates in the market of IT outsourcing services, with a view to assisting in the improvement of productivity, in its consequent significant reduction of costs and a better operational performance in the processes of the company providing outsourced IT services. Theoretical Framework: The study addresses concepts of the Lean philosophy, as well as the Six Sigma framework and the marriage of Lean and Six Sigma as a way to obtain advantages from the application of its methods, meeting the needs of the organization. Method: In this study, quantitative and qualitative methods were used from a descriptive research. A literature review and associated issues were carried out and a case study was applied from the results obtained through a project in a large multinational company that provides IT outsourcing services. Outcome and Discussion: The combination of Six Sigma with the business process offered the company an opportunity for cost reduction and improved its competitive advantage in an increasingly competitive and quality-driven market. Regarding the implementation of the incident governance process, a reduction of 24% was obtained; Regarding actions to reduce the number of overtime, a reduction of 40% was obtained. A total monthly reduction of US$ 5,589 was obtained and annually the reduction amount plus benefits reached US$ 67,068. Research Implications: Research contributes to the improvement of quality and significant cost reduction with the application of the Six Sigma framework, properly tested and demonstrated in an organization. Originality/Value: This study contributes to the literature by using the Six Sigma framework as a framework for IT Governance in order to help improve productivity with consequent significant cost reduction and better operational performance in the processes of an outsourced IT service provider. The relevance and value of this research are evidenced by the demonstration of the benefits obtained in the environment of the company under analysis.

Machine Learning-Based Prediction for High Health Care Utilizers by Using a Multi-Institutional Diabetes Registry: Model Training and Evaluation.

The cost of health care in many countries is increasing rapidly. There is a growing interest in using machine learning for predicting high health care utilizers for population health initiatives. Previous studies have focused on individuals who contribute to the highest financial burden. However, this group is small and represents a limited opportunity for long-term cost reduction. We developed a collection of models that predict future health care utilization at various thresholds. We utilized data from a multi-institutional diabetes database from the year 2019 to develop binary classification models. These models predict health care utilization in the subsequent year across 6 different outcomes: patients having a length of stay of ≥7, ≥14, and ≥30 days and emergency department attendance of ≥3, ≥5, and ≥10 visits. To address class imbalance, random and synthetic minority oversampling techniques were employed. The models were then applied to unseen data from 2020 and 2021 to predict health care utilization in the following year. A portfolio of performance metrics, with priority on area under the receiver operating characteristic curve, sensitivity, and positive predictive value, was used for comparison. Explainability analyses were conducted on the best performing models. When trained with random oversampling, 4 models, that is, logistic regression, multivariate adaptive regression splines, boosted trees, and multilayer perceptron consistently achieved high area under the receiver operating characteristic curve (>0.80) and sensitivity (>0.60) across training-validation and test data sets. Correcting for class imbalance proved critical for model performance. Important predictors for all outcomes included age, number of emergency department visits in the present year, chronic kidney disease stage, inpatient bed days in the present year, and mean hemoglobin A1c levels. Explainability analyses using partial dependence plots demonstrated that for the best performing models, the learned patterns were consistent with real-world knowledge, thereby supporting the validity of the models. We successfully developed machine learning models capable of predicting high service level utilization with strong performance and valid explainability. These models can be integrated into wider diabetes-related population health initiatives.

Financial management, efficiency, and care quality: A systematic review in the context of Health 4.0.

This article investigates the intersection between innovation, Health 4.0, and financial management in the healthcare industry, emphasizing the importance of operational efficiency and quality of care. The study aims to analyze how financial management processes in healthcare relate to Health 4.0 and enhance care quality. It begins with a thorough theoretical grounding, proposing a framework that connects Health 4.0 with financial management practices. A systematic review of the literature was conducted, identifying trends, challenges, and opportunities in the financial management of Health 4.0. The results highlight selected articles on responsible innovation, Health 4.0 technologies, investments in health, hospital efficiency, performance forecasting, and high-cost patient management. These articles were clustered into "Data Analysis and Machine Learning in Healthcare" and "Health Management and Sustainability," providing a categorized understanding of the topics. The study reveals that Health 4.0 offers significant opportunities for process efficiency and cost reduction without compromising service quality. It highlights strategic advantages in addressing contemporary healthcare challenges by optimizing processes, improving financial projections, and incorporating advanced technologies efficiently. The successful implementation of Health 4.0 can lead to substantial improvements in service quality, adding value to patients and driving local economic development. This article offers valuable insights for healthcare professionals and managers, emphasizing the transformative potential of Health 4.0 and outlining strategies for its effective implementation. The clustering of articles provides a clearer understanding of current research in Health 4.0, contributing significantly to the field and guiding future research directions.

Scale effects on core design, fuel costs, and spent fuel volume of pressurized water reactors

The desire to improve the economic competitiveness and deployment pace of nuclear energy through modularization, manufacturing, and series production had led to the development of smaller size reactors. As the standard 17x17 fuel technology is mainly maintained in the pressurized water reactors (PWRs) category, this translates into a lower number of fuel assemblies in the core and sometimes a reduced fuel height. To assess the impact of such scale change in core design on fuel cycle cost and spent fuel volume, a scoping analysis tool is developed based on infinite lattice calculations, leakage, fuel management reduced models, and levelized unit cost of electricity (LCOE) estimate. As such, cost dynamics driven by fuel specific power, burnup, core leakage, feed, cycle length, fuel assembly height as well as uranium market data are captured with consistent set of assumptions and analysis methods. A selection of 5 reactor designs representative of leading PWR developers is assessed and compared. Pursuing higher specific powers and optimal burnups are highlighted as the main fuel cost reduction drivers, nevertheless, practical limitations and opportunities must be evaluated to establish the feasibility of such enhanced fuel operation. In consequence, a detailed core design is performed using SIMULATE3 code for 5 PWR variations including natural and forced coolant circulation modes, two reactor scales, power densities of 73, 112, and 123 kW/l and higher discharge burnups. Design and optimization are performed at the lattice level, for the reflector, and at the core loading level. Satisfactory steady-state operation including power distribution, coolant operating limits, and reactivity requirements are analyzed and reported in this paper. The fuel economics of the detailed core designs confirm the scoping analysis findings. Despite the unlocked power uprates in small PWRs, the achievable burnup for a given fuel specific power requires more enrichment and shorter fuel height results in higher fabrication costs per mass of fuel, which makes scaling down core size a more expensive endeavor on the fuel cycle front. Spent fuel volumes are reported for the PWRs designed in this paper. These volumes are driven by the core average discharge burnup regardless of the scale in consideration. Additional cost and core performance aspects related to heavy reflector gains, fuel-reflector substitution, and disposal cost policy in the U.S. are examined.

IMPACT OF GREEN INNOVATION (GI) PERFORMANCE ON COMPETITIVE ADVANTAGE OF FIRMS IN INDIA

Green Innovation (GI) is increasingly recognized as a critical factor in enhancing the competitive advantage of firms globally, and this trend is evident in India as well. This article explores how the performance of Green Innovation contributes to a firm’s competitive edge in the Indian context. Key drivers such as regulatory compliance, market demand, cost-reduction opportunities, and corporate social responsibility (CSR) mandates are examined. The article highlights various GI performance metrics, including resource efficiency and green product development, and discusses how these can translate into competitive advantages such as brand reputation, differentiation, cost leadership, and access to new markets. Case studies of Indian companies like Tata Motors, ITC Limited, and Mahindra & Mahindra demonstrate the real-world impact of GI on business success. Finally, the challenges that firms face in implementing Green Innovation, including high initial costs and supply chain constraints, are considered.

Adopting combination machine learning models could reduce hospital length of stay for oncology patients.

11084 Background: Integra Connect previously created in-patient (IP) admission prediction model based on OCM data. One of the challenges for practices in a value-based care (VBC) program is to provide continuous care-coordination during and after an IP admission. Our objective is to show how adopting combination machine learning (ML) models can predict IP length of stay (LOS). Potential benefits include an overall reduction in LOS which could minimize the risk of hospital acquired conditions. Methods: ML models were trained on 5 major cancer types (Lung Cancer, Multiple Myeloma, Lymphoma, Small Intestine / Colorectal Cancer, High-risk Breast Cancer') from 7 OCM practices of PP4-PP9 data, excluding surgery IP admission. The top 5 cancer types accounted for ~50% of total in-patient admissions and ~50% of total LOS in days. The IP admissions were divided into 4 major cohorts in terms of LOS in days (1-3: class 1, 4-8: class 2, 9-15: class 3, and more than 15: class 4). To reduce the overall LOS, we adopted two ML models: 1) To classify LOS, a multi-classification model (Model1, an eXtreme Gradient Boosted Trees Classifier) and 2) To predict the LOS for classes 1-3, a regression-based model (Model2, an eXtreme Gradient Boosted Trees Regressor with Early Stopping). Class 4 cohort had a wide range (16- 90+ days) for LOS and therefore was excluded from Model2. The other three cohorts belonged to Q1, IQR, and Q4, respectively. Model1 was trained on 4,280 randomly selected sample IP admissions to balance each class and Model2 was trained on 19,636 IP admissions, both with 102 features. Results: The models were tested on PP10-PP11 claims excluding 0 days LOS. Model1 predicted 296 (3,945) IP admissions in class 4 of which 88 were true positives. Assuming at least a 10% reduction in associated total LOS translated to lower LOS of 1-3% for 5 (7) practices. The remaining 3,649 IP admissions were used to predict LOS by Model2. The difference between actual LOS and Predicted LOS was found as 18%-24%. To address model prediction errors, we defined the target LOS to be predicted LOS with an upper bound of at least 10%. This led to reductions of 6% -16% across practices. Finally, combining the results of both ML models we determined that the potential to lower LOS was at least 6% and at most 19%. Conclusions: Our ML models identified opportunities to reduce LOS across multiple OCM cancer practices for 5 major cancer types. We also identified a cohort of patients with critical condition (class 4) that is vital for practice transformation initiatives. These identified reduction in LOS for oncology patients provides cost reduction and quality improvement opportunities in VBC programs. In the future, more opportunities to lower LOS will be explored with a re-admission prediction model.

Contribution of nanotechnology to greater efficiency in animal nutrition and production.

Feed costs present a major burden in animal production for human consumption, representing a key opportunity for cost reduction and profit improvement. Nanotechnology offers potential to increase productivity by creating higher-quality and safer products. The feed sector has benefited from the use of nanosystems to improve the stability and bioavailability of feed ingredients. The development of nanotechnology products for feed must consider the challenges raised by biological barriers as well as regulatory requirements. While some nanotechnology-based products are already commercially available for animal production, the exponential growth and application of these products requires further research ensuring their safety and the establishment of comprehensive legislative frameworks and regulatory guidelines. Thus, this article provides an overview of the current state of the art regarding nanotechnology solutions applied in feed, as well as the risks and opportunities aimed to help researchers and livestock producers.

Review and analysis of the failure risk mitigation via monitoring for monopile offshore wind structures

Structural health monitoring systems are gaining more attention in the offshore wind industry as they offer valuable insights into the integrity status of operating assets. Whilst most Class Society Rules and International Standards recognise the importance of implementing a condition-based maintenance strategy, they only provide theoretical guidance. Ultimately, it is the asset owner’s responsibility to determine how to integrate this strategy into their broader operation and maintenance planning, including identifying which components to monitor and which monitoring techniques to employ. The present paper applies the Failure Mode, Effects, and Criticality methodology to identify the most critical failure modes to prioritise for monopile offshore wind structures. Hence, the potential benefits of incorporating structural health monitoring systems within a condition-based maintenance strategy and exploiting lifetime extension possibilities are assessed. To achieve this, a novel 4-step methodology is introduced, involving understanding failure mechanisms (time-dependent behaviour and pattern), current regime (inspections at intervals), monitoring options (both direct and indirect), improvement potential evaluation through 5 key performance indicators relevant for optimal O&M, which is more comprehensive and realistic than considering only monetary consequence of failure. The study addressed the prevailing failure modes in 5 categories, namely fatigue, corrosion, deformation, buckling and displacement, and connection failure, aiming to demonstrate potential improvement in terms of risk mitigation against these failure modes. The results of this study can significantly help offshore wind developers optimise where and how to allocate their resources for structural health monitoring, resulting in long-term cost reduction opportunities.

Concept for an innovative screw coupling system production process

The article presents the concept of an innovative approach to the production of a screw coupling system, a key element in rail vehicles. The use of ready-made components from various subsuppliers, combined with new quality control methods, offers an opportunity for a significant reduction in cost and production time while increasing the efficiency and flexibility of the process. Key stages of the production process are highlighted, from the selection of semifinished products, through quality control, to the final assembly and validation. The applied strategies can minimise waste, increase material efficiency, and have a positive impact on the environment. This study constitutes a significant contribution to the development of sustainable production in the railway industry, with an emphasis on organisational, process, and product innovations.

Design Optimization of LCV CAB for Frontal Pendulum Test: Enhancing Survival Space Improvement Through Frugal Load Path Transfer Techniques

In the fiercely competitive landscape of the automotive industry, Original Equipment Manufacturers (OEMs) encounter substantial challenges in the realm of Research and Development (R&D), particularly in the pursuit of lightweight design without compromising safety. As a result, the automotive sector continuously seeks innovative tools and methodologies to substantially optimize the structural composition of Light Commercial Vehicle (LCV) segments. The design of lightweight cabins, while simultaneously ensuring crashworthiness, not only plays a pivotal role in determining the market success of a new LCV but also holds significant legal implications. One well-established and indispensable evaluation tool to ascertain compliance with critical homologation requirements is the frontal pendulum test. This test serves as a litmus test for the appropriate design of Body in White (BIW) architecture, crucial for safeguarding occupant safety in unforeseen emergency scenarios.Within the context of adhering to styling themes and the design intent governing the three-dimensional (3D) geometry, a notable deviation emerged in the form of a 33 mm extension of the front panel in the newly stylized cabin. This deviation presented CAB engineers with a formidable challenge, as it disrupted the conventional load path of the frontal pendulum, rerouting it to the CAB itself instead of the intended transfer to the frame via the bull bar. The primary objective of this work is to restore the load path to the frame, all the while adhering to the original styling intent and refraining from introducing any additional modifications to major adjacent components such as the bumper and bumper reinforcement. Furthermore, this undertaking extends to encompass an exploration of cost reduction opportunities within the ambit of the newly styled CAB.
 Keywords: LCV CAB, Frontal Pendulum, Frugal Load, Occupant safety regulation, Styling impact, Pendulum impact, CAE simulation

ENSURING GLOBAL FOOD SAFETY: INTEGRATING BLOCKCHAIN TECHNOLOGY INTO FOOD SUPPLY CHAINS

This concept paper explores the integration of blockchain technology into food supply chains to enhance global food safety. In recent years, food safety has become a critical concern worldwide, with frequent outbreaks of foodborne illnesses and contamination incidents. Traditional supply chain systems often lack transparency, traceability, and efficiency, leading to challenges in identifying the source of contamination and preventing its spread. Blockchain technology offers a promising solution to these challenges by providing a decentralized, immutable, and transparent ledger system. By recording each transaction and transfer of food products on a blockchain, stakeholders can trace the journey of food items from farm to fork in real-time. This enables rapid identification of contaminated products, facilitating targeted recalls and reducing the scope and impact of foodborne illness outbreaks. Key benefits of integrating blockchain technology into food supply chains include enhanced transparency, increased trust among consumers, improved efficiency in recalls and audits, and opportunities for process optimization and cost reduction. However, successful implementation requires collaboration among stakeholders, investment in infrastructure, and addressing technical and regulatory challenges. This concept paper outlines a strategic framework for implementing blockchain technology in food supply chains, including stakeholder engagement, pilot testing, scalability considerations, and regulatory compliance. By leveraging blockchain technology, we can ensure greater food safety, protect public health, and strengthen confidence in the global food supply chain.
 Keywords: Food Safety, Blockchain, Technology, Supply.

Metallurgical characteristics of AA6061 aluminium and AZ31B magnesium dissimilar joints by fusion welding technique.

Aluminium (Al) and magnesium (Mg) alloys are extensively used in the automobile sector because of their high strength-to-weight ratio, excellent castability low density and simplicity of recycling. Al-Mg structures used in the automotive sector can potentially reduce their weight. Although there is a significant opportunity for substantial cost reduction, the use of magnesium in aluminium structures remains restricted. This study aims to weld 3 mm-thick rolled sheets of AA6061 Al and AZ31B Mg alloy using the cold metal transfer (CMT) arc welding process. Three different filler wires (ER1100, ER4043, and ER5356) were used in the experiment. In this article, the mechanical and microstructure characteristics of Al/Mg dissimilar joints manufactured by CMT are evaluated and discussed in detail. Optical microscope (OM), scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDX), and x-ray diffraction (XRD) were used to analyze the CMT-welded Al/Mg dissimilar joints. Of the three filler wires used, ER4043 (Al-5%Si) filler wire yielded defect-free sound joints due to the presence of Si, which improves the flow ability of molten filler during welding. The presence of Mg-rich intermetallics-Al12Mg17)and Al-rich intermetallics-Al3Mg2 were observed. The fractured area of the CMT-welded Al/Mg dissimilar joints revealed the presence of the Mg-rich intermetallics (Al12Mg17), which is responsible for the decrease in tensile strength. The reduction of intermetallics, particularly of Mg-rich intermetallics (Al12Mg17) is important for improving joint strength. RESEARCH HIGHLIGHTS: Cold metal transfer (CMT) arc welding was used to control the Al-Mg-rich intermetallics in the Al/Mg dissimilar joints. The microstructure, morphology and phase composition of the welded joints were studied by OM, SEM, TEM, EDS and XRD. The weld metal and AL substrate bonded with a strong interface, while weld metal and Mg substrate were joined at the epitaxial solidification area where the intermetallic compounds of Mg2Al3, Mg17Al12 and Mg2Si are generated. The weld metal on the Mg side experienced brittle fracture, with a continuous distribution of Mg2Al3, Mg17Al12 and Mg2Si.

Sustainability in Electromagnetic Metamaterials: Synthesis, Applications, and Future Directions with Challenges

This paper is about sustainable Electromagnetic Metamaterials (EM-MM), which are a new class of artificial materials with unique electromagnetic properties that cannot be found in nature. These materials are made from discrete micro and nanoscale objects which resonate, allowing for precise control over how they interact with electromagnetic waves, and hence, leading to unheard of functionalities. Thus the need for sustainable synthesis methods for EM-MM has become paramount to mitigate the quantity of resources associated with conventional fabrication techniques. Renewable resources like biopolymers that mimic natural patterns are examples of the sustainable use of bio based synthetic material pathways. This may guarantee sustainability through fabricating additive manufacturing strategies, especially 3D printing innovation where fabric statement is controlled only as required, diminishing waste. With all this recycling and up cycling offer opportunities for development and cost reduction while reducing the natural impacts related to sustainability. There are several different domains have benefited from the application of EM MM, for example solar energy harvesting offer potential for sustainable power generation, imaging uses met material lenses which have superior resolution and sensitivity, while in telecommunications met material antennas ensure to transmit and get signals more successfully. But there are still a few issues that still need to be resolved in electromagnetic met materials. Future directions include the research of incorporating a plan of new types of electromagnetic composites with upgraded qualities and sustainable synthesis strategies. Applications of technology require to overcome practical challenges such as integration, toughness, and cost-effectiveness while assessing societal implications, financial, and social affects. For the sustainable advancement of metamaterials in order to deal with major societal concerns, minimizing their natural impressions requires collaboration and moral concerns.

Dynamic Life Cycle Assessment Framework of Cold Food Storage Facilities

The imperative of responding to anthropogenic climate change that is driving energy infrastructure managers to implement resilience enhancing policies such as hourly scale dynamic pricing concurrently drives energy intensive industries to monitor energy usage at higher fidelity. This study proposes a Dynamic Life Cycle Assessment (DLCA) framework specifically tailored for cold food storage facilities which provide essential thermodynamic resilience to the human food web and consumes a large share of the web's energy footprint. Different from the conventional LCA, which delivers a snapshot of the environmental impacts and cost statically, DLCA can accommodate temporal variations in operating conditions and energy usage. It interacts with real-time monitoring data and fluctuating energy rates to provide a more accurate and time-sensitive environment impact and cost evaluation. Key parameters from real-time sensors and reference databases are summarized to lay the foundation for DLCA of cold food storage, like operating power and hours, shipment arrival time, and transportation fuel economy. Its feasibility and reliability are validated by scenarios that simulate different operating conditions, like shift change to utilize off-peak rate and change of packaging materials. The proposed framework allows facility operators and policymakers to pinpoint bottlenecks and seize opportunities for environmental impact and cost reduction.

Impact of Sanctions on Formation of the Russian Approach to the Legal Regulation of Cross-Border Insolvency

This article is devoted to the analysis of the impact of sanctions and counter-sanctions measures on the formation of the approach of Russian courts to the consideration of disputes in insolvency cases. under the influence of integration processes on a global and regional scale, there is an intensification of foreign economic relations of economic entities from different countries, the interdependence of legal entities is formed within the framework of the international economic process. the active development of international economic activity brings with it not only great profits, opportunities for cost reduction and the development of international communication, but also the most severe crisis phenomena, a great risk of not staying afloat, resulting in a relatively new phenomenon of cross-border insolvency. The author noted the problematic aspects of the impact of sanctions on the consideration of insolvency disputes, including the initiation of bankruptcy proceedings, the inclusion of foreign creditors in the register of creditors’ claims, the recognition and enforcement of foreign judgments. The author studied cases from the latest practice of Russian courts, noted the features of the consideration of insolvency cases involving creditors and debtors of «unfriendly» countries, made conclusions and assumptions about the further development of judicial practice.

Identifying the influence of the distance factor on the level of transaction costs at agricultural processing enterprises

The object of this study is the transaction costs of agricultural processing enterprises that operate in cooperation with various participants: suppliers of raw materials, buyers of finished products, research enterprises, and other entities. Transaction costs arise at all stages of activity, from the preparation of an agro-processing project to the achievement of the final result. For this, a simulation modeling system is proposed, including an optimization model that allows estimating the quantitative components of transaction costs. The process of transactions between various participants such as suppliers, customers, and partners is studied using simulation models. To demonstrate the applicability of this model to the example of agro-industrial enterprises, some parameters of transaction costs are modeled when choosing suppliers of raw materials at recommended intervals. The feasibility of simulating the costs of establishing a relationship with a new partner in the range of 0.5–0.6, and the benefits in the range of 1.05–1.10 has been determined. It has been found that transaction costs associated with raw material suppliers can be saved by 40.0 % in the next 3 years through optimization and digital capabilities. The presented approach can be useful for a deeper study of the digital environment’s impact on the level of transaction costs in agricultural processing enterprises. Such an analysis will reveal potential opportunities for optimization and cost reduction, which is important for improving the efficiency and competitiveness of these enterprises

A Mathematical Model for Determining the Facility Layout Plan of a Plastic Injection Factory

In this study, a mathematical model has been developed to make the facility layout planning of the annex building, which is being built right next to the old building of a factory that produces plastic parts. Some or all parts of the departments, such as injection machines, semi-finished products, product, raw material warehouses, molding room, and paint shop in the old building of the factory can be moved to the new building. Nevertheless, some cannot be moved. Since injection machines use cranes for electricity, plumbing, and mold transport, relocation is very costly. Different layouts are proposed with the developed mathematical model for seven scenarios that allow and do not allow partitions of the departments. The proposed layout plans were compared in terms of the total carrying costs of the products and the carrying costs of the sections. In this way, the factory has been presented with a significant cost reduction opportunity.

Renewable energy integration in offshore oil and gas installations

As the oil and gas industry seeks to reduce its carbon footprint and align with global decarbonization goals, integrating renewable energy sources into offshore operations presents a promising pathway. This review examines the feasibility of incorporating renewable energy technologies such as offshore wind, solar, and marine energy into the power supply of oil and gas installations. Offshore wind energy, with its high potential and scalability, emerges as a viable option for powering rigs, as demonstrated by projects like Hywind Tampen in Norway, which uses floating wind turbines to supply energy to oil platforms. Solar energy, while more limited in offshore environments due to space and weather constraints, can be part of hybrid systems combining multiple renewable sources. Marine energy, including tidal and wave power, is still in its developmental stages but holds promise for future applications. The review explores hybrid energy systems that integrate renewable sources with conventional energy, such as gas turbines, to ensure continuous power supply. Microgrid technologies and energy storage solutions are also discussed as essential components for balancing renewable energy’s intermittency and optimizing power distribution. Key challenges, such as the harsh marine environment, high initial investment, and the need for new infrastructure, are analyzed alongside potential solutions like technological innovations in floating renewable systems and automated monitoring technologies. Economic feasibility is considered through a cost-benefit analysis, highlighting the potential long-term savings from reduced fuel use and the benefits of regulatory incentives for renewable energy integration. Ultimately, the integration of renewables not only supports decarbonization but also offers operational efficiency and cost reduction opportunities. This review concludes by examining future trends in renewable energy for offshore installations and the potential for fully electrified, sustainable oil and gas platforms.

Non-thermal pasteurization of milk by an innovative energy-saving moderate electrical field equipped with elongated electrodes and process optimization

Environmental concerns and consumer demand necessitate alternative pasteurization techniques that sustainably produce safe and high-quality milk. To this end, a new non-thermal (<42 °C) moderate electric field (MEF) system was developed with elongated electrodes and a reduced electrode gap. Response surface methodology optimized technical and thermo-physical attributes, including viscosity, density, freezing point, solid non-fat (SNF), temperature, power usage, and specific energy consumption (SEC), by altering electrical field intensities (EFI) and mass flow rates (ṁ) from 25 to 30 V/cm and from 0.017 to 0.033 kg/s, respectively. The results were then compared with the conventional thermal pasteurization (CP, 63 °C for 30 min). Besides, process cost analysis in terms of electricity consumption was performed to identify cost reduction opportunity for the industry, and milk samples were analyzed by scanning electron microscopy to elaborate on the mechanisms involved. MEF optimal processing conditions were 29.8 V/cm EFI and 0.018 kg/s ṁ, which reduced 98.58% of energy consumption, 98.51% of SEC, and 99.09% of processing time in comparison with CP. Also, MEF possessed higher productivity than CP. D-value for total count bacteria (TCB) in MEF was significantly lower than CP (0.06 vs. 14.80 min), and MEF and CP reduced TCB by 99% and 88.61%, respectively. Compared with the previously reported MEF milk pasteurizer, the MEF system developed in this study saved energy, cost, and time by 99.2%, 99.0%, and 78.4%; therefore, this emerging technology could further contribute to sustainable manufacturing of foods.

Evaluation of the Capsaicinoid Extraction Conditions from Mexican Capsicum chinense Var. Mayapan with Supercritical Fluid Extraction (SFE)

Capsaicin (Cp) is a secondary metabolite produced by the Capsicum plant family. This molecule exhibits various biological properties such as antioxidant capacities, anti-obesogenic effects, and antidiabetic properties, among others. However, conventional extraction methods for Cp present several disadvantages including toxicity, extraction time, and low purity. Therefore, the utilization of supercritical fluid extraction techniques represents a viable option for obtaining highly pure and low-toxicity oleoresins (capsaicin-rich extracts). This approach involves the use of CO2 in the supercritical state and finds applicability in the pharmaceutical, food, and cosmetic industries. The Capsicum chinense variety from the Yucatán Peninsula is a crop with significant economic impact in the region, due to having the highest concentrations of Cp in Mexico. This significant characteristic is attributed to its adaptation to the unique conditions (climate, soil, solar radiation, humidity) of the southeastern region of Mexico. The objective of this study was to evaluate the effect of temperature (45 °C, 60 °C), pressure (1450 psi, 2900 psi), and extraction time (60 min, 120 min) on the supercritical fluid extraction of Cp and dihydrocapsaicin (DhCp) from Capsicum chinense Jacq. The results obtained demonstrated that the extraction conditions of 45 °C, 1450 psi, and 60 min yielded the highest concentration of Cp (37.09 ± 0.84 mg/g extract) and DhCp (10.17 ± 0.18 mg/g extract), while the highest antioxidant capacity (91.48 ± 0.24% inhibition) was obtained with 60 °C, 2900 psi, and 60 min. The findings of this study indicate that the lower the pressure and extraction time, the higher the concentrations of Cp and DhCp compared to previous reports. This represents an opportunity for cost reduction in production lines and improved utilization of Capsicum chinense in the agrifood industry through additional optimization processes.