Low Cost Operation Research Articles

Performance Analysis of Multi-Tote Storage and Retrieval Autonomous Mobile Robot Systems

Multi-tote storage and retrieval (MTSR) autonomous mobile robots can carry multiple product totes, store and retrieve them from different shelf rack tiers, and transport them to a workstation where the products are picked to fulfill customer orders. In each robot trip, totes retrieved during the previous trip must be stored. This leads to a mixed storage and retrieval route. We analyze this mixed storage and retrieval route problem and derive the optimal travel route for a multiblock warehouse by a layered graph algorithm, based on storage first-retrieval second and mixed storage and retrieval policies. We also propose an effective heuristic routing policy, the closest retrieval (CR) sequence policy, based on a local shortest path. Numerical results show that the CR policy leads to shorter travel times than the well-known S-shape policy, whereas the gap with the optimal mixed storage and retrieval policy in practical scenarios is small. Based on the CR policy, we model the stochastic behavior of the system using a semiopen queuing network (SOQN). This model can accurately estimate average tote throughput time and system throughput capacity as a function of the number of robots in the system. We use the SOQN and corresponding closed queuing network models to optimize the total annual cost as a function of the warehouse shape, the number of robots, and tote buffer positions on the robots for a given average tote throughput time and throughput capacity. Compared with robots that retrieve a single tote per trip, an MTSR system with at least five buffer positions can achieve lower operational costs while meeting given average tote throughput time and tote throughput capacity constraints. Funding: This work was supported by National Natural Science Foundation of China [Grant 72372088] and the Shenzhen Science and Technology Program [Grant GJHZ20220913143003006]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2023.0397 .

Comparison Of Functional Outcomes of Arthroscopic Bankart Repair Vs Open Bristow-Latarjet Procedure for Shoulder Joint Instability

Background: Anterior shoulder instability predominantly affects collegiate athletes, with a notable incidence of 0.12 per 1000 athletic exposures. Acute dislocations pose an orthopedic emergency requiring immediate repositioning to prevent complications such as brachial plexus or artery compression, avascular necrosis of the humeral head, and chronic disability. Conservative therapy often precedes surgical intervention due to concerns over recovery time, discomfort, decreased range of motion, and high recurrence rates. Objective: This study aims to compare the efficacy of Arthroscopic Bankart Repair and open Bristow-Latarjet Procedure in terms of pain reduction, return to normal activities, and improvement in Western Ontario Shoulder Instability (WOSI) score among patients with anterior shoulder joint instability. Methods: A 12-month comparative study was conducted at Lahore General Hospital from April 2022 to April 2023, following ethical review board approval. Thirty-two patients aged 18–32, with severe unidirectional dislocation, consented and participated. They were divided into two groups: Group A underwent Arthroscopic Bankart Repair, and Group B underwent the open Bristow-Latarjet Procedure. Results: The average age was 23 in Group B and 25 in Group A. Males comprised 80% of Group A and 68% of Group B. WOSI scores averaged 72 for Bankart and 76 for Latarjet. Rowe scores were 75 (Bankart) and 69 (Latarjet), with Quick DASH scores of 11 (Bankart) and 15 (Latarjet). External rotation was 77 degrees in Bankart and 73 degrees in Latarjet. Functional satisfaction was reported by 84.0% of Bankart and 11.7% of Latarjet patients. The cost of Latarjet was significantly lower than that of Bankart. Conclusion: The open Latarjet procedure demonstrated higher functional satisfaction and lower operational costs compared to Arthroscopic Bankart Repair, which exhibited a higher recurrence rate. Given the economic constraints in a developing country like Pakistan, Latarjet may be a more viable option despite the non-invasive appeal of Bankart Repair.

GMAlignNet: multi-scale lightweight brain tumor image segmentation with enhanced semantic information consistency

Although the U-shaped architecture, represented by UNet, has become a major network model for brain tumor segmentation, the repeated convolution and sampling operations can easily lead to the loss of crucial information. Additionally, directly fusing features from different levels without distinction can easily result in feature misalignment, affecting segmentation accuracy. On the other hand, traditional convolutional blocks used for feature extraction cannot capture the abundant multi-scale information present in brain tumor images. This paper proposes a multi-scale feature-aligned segmentation model called GMAlignNet that fully utilizes Ghost convolution to solve these problems. Ghost hierarchical decoupled fusion unit and Ghost hierarchical decoupled unit are used instead of standard convolutions in the encoding and decoding paths. This transformation replaces the holistic learning of volume structures by traditional convolutional blocks with multi-level learning on a specific view, facilitating the acquisition of abundant multi-scale contextual information through low-cost operations. Furthermore, a feature alignment unit is proposed that can utilize semantic information flow to guide the recovery of upsampled features. It performs pixel-level semantic information correction on misaligned features due to feature fusion. The proposed method is also employed to optimize three classic networks, namely DMFNet, HDCNet, and 3D UNet, demonstrating its effectiveness in automatic brain tumor segmentation. The proposed network model was applied to the BraTS 2018 dataset, and the results indicate that the proposed GMAlignNet achieved Dice coefficients of 81.65%, 90.07%, and 85.16% for enhancing tumor, whole tumor, and tumor core segmentation, respectively. Moreover, with only 0.29 M parameters and 26.88G FLOPs, it demonstrates better potential in terms of computational efficiency and possesses the advantages of lightweight. Extensive experiments on the BraTS 2018, BraTS 2019, and BraTS 2020 datasets suggest that the proposed model exhibits better potential in handling edge details and contour recognition.

Frequency-selective acoustic micromanipulation platform

Acoustic micromanipulation methods offer versatile tools ranging from lab-on-chip diagnostic platforms to mobile microrobots. Acoustically oscillating bubble-powered microsystems are gaining increased attention owing to their low cost and convenient operation. To date, no studies have reported on the controllability of the driving frequency on acoustic micromanipulation platforms using Helmholtz resonators. Here, we introduce a Helmholtz resonant cavity into a bubble-powered microsystem to reveal the function of the oscillation modes and frequency selectivity. The Su–Schrieffer–Heeger (SSH) model was utilized to construct a topological interfacial state and bubble-powered working location. We experimentally observed that the microparticles were captured by the oscillation bubble and underwent orbital rotation at the topological frequency. However, the microparticles were tightly bound close to the oscillation bubble area when the driving frequency was outside the topological frequency range. Our acoustic micromanipulation platform implements multiple microparticle manipulation modes based on frequency selectivity that are independent of optical or magnetic properties, which can enrich the micromanipulation toolbox and exhibit enormous application potential in the biomedical field.

Investigation of the Impact of SSSC-Based FLC on the Stability of Power Systems Connected to Wind Farms

The integration of renewable energy sources into power systems has increased significantly in recent years. Among various types of renewable energy, the use of wind energy is growing rapidly due to its low operating cost, wide distribution worldwide, and no greenhouse gas emissions. However, power systems integrated with wind energy may face stability and reliability issues due to the intermittent nature of wind power. Therefore, in power systems connected to wind farms, it is usually required to use some compensators such as static synchronous series compensator (SSSC) to increase the system performance under abnormal conditions. On the other hand, for an SSSC to be effective in improving the system performance, it must be equipped with a suitable controller. In this paper, a fuzzy logic controller (FLC) is used for the SSSC because of its advantages over conventional controllers. Extensive research has been conducted in power systems with wind turbines in which SSSC or FLC has been used; however, their simultaneous application in such systems has received less attention. Therefore, this article aims to fill this gap. The proposed method is implemented on two power systems and the simulation results are analyzed. In both systems, the dynamic behavior of three different wind farms is examined. In the first and second wind farms, either a squirrel cage induction generator (SCIG) or doubly-fed induction generator (DFIG) are used, whereas in the third one which is a combined wind farm (CWF), an equal number of SCIG and DFIG are employed. In wind farms with SCIG or DFIG, an SSSC is also utilized. Furthermore, an FLC is employed for the SSSC to improve its efficacy. A proportional integral (PI) controller is also considered for the SSSC, and its results are compared with FLC results. The simulation results confirm the superiority of FLC over PI controller.

Phase calculation of smooth surface with multi-reflectivity based on phase measurement deflectometry

With the continuous advancement of precision machining technology and the growing demand for products, increasingly complex objects with high reflectivity are becoming more prevalent in production and daily life. phase measurement deflectometry (PMD) is a technique that utilizes a surface light source to project structured light for comprehensive detection of highly reflective surfaces. It offers advantages such as high accuracy, fast speed, low cost, and non-contact operation. However, when the surface of the object being measured has varying levels of reflectivity, this method may produce errors due to significant differences in fringe contrast between different reflective areas. In order to enable the fringe deflection system to simultaneously detect multiple reflective objects without sacrificing accuracy, this paper proposes an adaptive method for fringe generation detection. This method can adaptively adjust the intensity based on the reflectivity of the measured surface and compensate for the light at the reflectivity boundary, ultimately achieving phase calculation for multiple reflective surfaces.

A computational efficient approach for distributionally robust unit commitment with enhanced disjointed layered ambiguity set

AbstractTo achieve the sustainable development of the society, renewable energy dominated power systems are gradually formed. However, the uncertainty of renewable power poses challenges for power system operations, such as balancing the load and generation in day‐ahead unit commitment problems. To address this issue, an enhanced disjointed layered ambiguity set is proposed in this paper to effectively capture the uncertainty of renewable generation forecast errors. On this basis, a two‐stage distributionally robust unit commitment optimization problem is formulated, which is computational challenge. To this end, a novel reformation approach and a worst‐case support set identification method are proposed to derive the optimal solution in a computationally efficient way. Simulation results demonstrate that the proposed ambiguity set brings lower operation costs of unit commitment while maintaining similar reliability compared to existing methods. In detail, the proposed ambiguity set achieves a reduction in operating costs of approximately 10.01%. The proposed novel reformation approach and solution method are also shown to have higher computation efficiency than the existing Benders decomposition method, resulting in a reduction in computation time to less than 3.78% of the original duration.

Municipal Wastewater Characterization and Natural Treatment Using Reed Beds

Domestic wastewater, if not correctly disposed of, is a cause of pollution for water-based bodies. The reed bed system is a sort of phytoremediation method used to remove toxins from the environment. This system has a high potential for application in the treatment of household wastewater (WW) because it has good performance as a whole, low operating and maintenance costs, and is not harmful to the environment. This research aimed to study characteristics variation of Grdarasha area WW (located in the left side of Erbil-Kirkuk main road) before and after reed beds. The reed bed system was proven to have a good efficiency in removing Chemical Oxygen Demand (COD) (15. 91-71. 07) %, Total Solid (TS) (8.33-50) %, Total volatile Solid (TVS) (18.8-50) %, and chloride (2.5 – 82.98%). In furtherance of transferring oxygen from the environment, the interplay between pollutant-plants-medium-microbes is critical in pollutant removal utilizing the reed bed technique.

Leveraging Digital Transformation and ERP for Enhanced Operational Efficiency in Manufacturing Enterprises

Purpose: The process of making the most of digital tools in the workplace to support an organization's success is known as "leveraging on technology." By automating manual tasks more quickly, modern ERP systems free up time and funds for other important projects. Data can be aggregated by contemporary ERP systems for simpler management, access, and analysis. Method: Systems for enterprise resource planning, or ERPs, have become a vital component of contemporary manufacturing processes. These integrated software solutions are essential for improving, streamlining, and controlling many aspects of manufacturing, including financial control, customer service, production and inventory management. Manufacturers can effectively manage vital resources like labor, equipment, and materials with the help of ERP systems. ERP helps eliminate waste, minimize production delays, and maximize resource utilization by offering real-time visibility into resource allocation and availability. Result and Conclusion: Manufacturing process synchronization and automation are made easier by ERP software. Work orders, production schedules, and quality control can all be managed by it, resulting in seamless and effective manufacturing processes. In manufacturing, keeping the proper amount of inventory on hand is a difficult task. ERP systems give producers insights into demand trends, order lead times, and reorder points, which helps them optimize inventory levels. In addition to lowering carrying costs and preventing stockouts, this minimizes superfluous inventory. Implication of Research: An organization's operational model is altered by digital transformation. This process involves systems, workflow, processes, and culture. Every level of an organization is impacted by this transition, which unifies data from different departments to collaborate more successfully. Originality/Value: Enhanced Efficiency: Businesses are able to allocate resources more effectively thanks to automation and streamlined processes, which also lower operational costs and increase productivity.

Design of a Low-Cost Open-Top Chamber Facility for the Investigation of the Effects of Elevated Carbon Dioxide Levels on Plant Growth

Open-top chambers (OTCs) consist of semi-open enclosures used to investigate the impact of elevated carbon dioxide [CO2] on crops and larger plant communities. OTCs have lower operational costs than alternatives such as controlled environment cabinets and Free Air Carbon Dioxide Enrichment (FACE). A low-cost design is presented for an OTC with a surface area of 1.2 m2 and a target elevated CO2 concentration [CO2] of 650 µmol mol−1 adequate for trials involving cereals or grain legumes. The elevated CO2 chambers maintained an average concentration ± standard deviation of 652 ± 37 µmol mol−1 despite wind and air turbulences, in comparison to 407 ± 10 µmol mol−1 for non-enriched chambers. Relative to ambient (non-chamber) conditions, plants in the chambers were exposed to slightly warmer conditions (2.3 °C in daylight hours; 0.6 °C during night environment). The materials’ cost for constructing the chambers was USD 560 per chamber, while the CO2 control system for four chambers dedicated to CO2-enriched conditions cost USD 5388. To maintain the concentration of 650 µmol mol−1 during daylight hours, each chamber consumed 1.38 L min−1 of CO2. This means that a size G CO2 cylinder was consumed in 8–9 days in the operation of two chambers (at USD 40).

PI-Filter compensator for LQG controller aimed to fixed-wings aircrafts

Fixed-wing aircraft use their wings to generate lift and propulsion, relying on forward motion for airflow rather than rotating blades like helicopters. They offer advantages such as extended range, higher speeds, stability in turbulent weather, and lower operational costs compared to rotary-wing aircraft. A study introduces a method to improve control smoothness for fixed-wing aircraft using LQG control and PI filter compensation. Flight simulators like FlightGear are used for testing control algorithms before real-world experiments, offering realistic flight dynamics and versatile options for various aircraft types. This approach provides a cost-effective and efficient way to develop and test controllers for challenging flight scenarios.

Optimizing power systems and microgrids: A novel multi-objective model for energy hubs with innovative algorithmic optimization

This article delves into the dynamics of power system and microgrid planning, emphasizing the emerging significance of energy hubs. The study introduces a pioneering multi-objective model that integrates economic considerations and microgrid pollution mitigation. The focus is on renewable sources such as wind and solar, coupled with advanced energy storage systems like E-fuel. Sophisticated probabilistic modeling techniques address uncertainties in renewable resources, complemented by a demand-side management program for cost reduction during peak hours. Transforming into an optimization problem, an innovative algorithm inspired by African vulture foraging behaviors provides a distinctive approach to energy landscape optimization. In a comparative analysis with established models, this approach demonstrates proficiency in simulating market behavior and providing optimal strategies for profit maximization. In a simulation analysis of four scenarios, the impact of risk assessment, a novel electronic fuel storage market, and an innovative energy storage solution on operational costs and pollution emissions is scrutinized. Notably, the proposed method excels in Case 4, showcasing a significant reduction in both operational costs and emissions. Case 4 demonstrates a substantial reduction in operational costs to $1745.732 and pollutant releases to 10753.621 kg, outperforming existing models with lower operational costs and pollutant releases.

Zinc‐Ion Battery Chemistries Enabled by Regulating Electrolyte Solvation Structure

AbstractDesigning next‐generation alternative energy storage devices that feature high safety, low cost, and long operation lifespan is of the utmost importance for future wide range of applications. Aqueous zinc‐ion batteries play a vital part in promoting the development of portability, sustainability, and diversification of rechargeable battery systems. Based on the theory of electrolyte solvation chemistry, deep understanding of interaction between electrolyte components and their impact on the chemical properties has achieved a series of research progress. Analyzing the solvation shell of electrolyte or structure–performance relationship, and establishing more stable and high‐energy battery chemistries are inevitable requirements to suppress the electrolyte–electrode interphase side reaction and realize the functional use of zinc‐ion batteries. In this critical review, the attempt is to overview the current comprehension regarding the electrolyte solvation structure in zinc battery technology. Advanced methodology toward the interactions between zinc cations, solvent molecules, and anions in zinc aqueous electrolytes and the general rules for electrolyte design from the atomic level are summarized. Methods for viable solvation modification are then introduced regarding overcoming the remained challenges for transferring the laboratory results to next‐generation practical applications. Possible research direction with the aim of investigating the ultimate choice for future high‐performance electrolyte solvation construction is also outlined.

Enabling organizations to strategically manage risks in circular supply chains

AbstractCircular supply chains (CSCs) prioritize resource efficiency by reusing, remanufacturing, and recycling materials, offering environmental benefits and competitive advantages. However, they are facing various risks and organizational challenges that hinder their efficiency. To ensure long‐term sustainability, this study identifies the key risks and introduces a prioritization model for risk management in CSC strategies proposing a framework for the risk evaluation based on the set of criteria and prioritization model using a combination of three multicriteria decision‐making (MCDM) methods. The model applies fuzzy Delphi‐based analytical hierarchy process (AHP) method to determine the criteria weights and fuzzy axial distance‐based aggregated measurement (ADAM) method for ranking the alternatives. The findings of this study allow for the identification of the most important risks associated with CSC enabling stakeholders to allocate resources strategically and focus efforts on crucial areas. Results highlight that the most important risks are supply chain complexity, resource availability, and quality and technological challenges. The most important contributions are the identification of the most relevant risks that threaten the resilience and sustainability of CSCs, the establishment of the framework for their evaluation, and the development of a novel hybrid MCDM model for their ranking. These contributions are also the main theoretical implications of the study. On a practical level, it enables organizations to strategically manage risks, standardize risk assessment, and improve their competitive advantage by enhancing resilience, reducing disruptions, and lowering operational costs.

Geopolymer-Based Materials for the Removal of Ibuprofen: A Preliminary Study.

Every year, new compounds contained in consumer products, such as detergents, paints, products for personal hygiene, and drugs for human and veterinary use, are identified in wastewater and are added to the list of molecules that need monitoring. These compounds are indicated with the term emerging contaminants (or Contaminants of Emerging Concern, CECs) since they are potentially dangerous for the environment and human health. To date, among the most widely used methodologies for the removal of CECs from the aquatic environment, adsorption processes play a role of primary importance, as they have proven to be characterized by high removal efficiency, low operating and management costs, and an absence of undesirable by-products. In this paper, the adsorption of ibuprofen (IBU), a nonsteroidal anti-inflammatory drug widely used for treating inflammation or pain, was performed for the first time using two different types of geopolymer-based materials, i.e., a metakaolin-based (GMK) and an organic-inorganic hybrid (GMK-S) geopolymer. The proposed adsorbing matrices are characterized by a low environmental footprint and have been easily obtained as powders or as highly porous filters by direct foaming operated directly into the adsorption column. Preliminary results demonstrated that these materials can be effectively used for the removal of ibuprofen from contaminated water (showing a concentration decrease of IBU up to about 29% in batch, while an IBU removal percentage of about 90% has been reached in continuous), thus suggesting their potential practical application.

Industrial Scale Manufacturing Sub‐10 nm Reverse Osmotic Desalination Membrane on Metallic Single‐Walled Carbon Nanotubes Network

AbstractDifferent from extensively reported carbon nanotubes‐polyamide (PA) composite membranes, this work reports the scalable, low‐cost manufacturing of metallic single‐walled carbon nanotubes network supported PA reverse osmotic desalination membranes. Metallic single‐walled carbon nanotubes (SWCNTs) separated from high‐pressure carbon monoxide conversion (HiPCO) SWCNTs with a diameter ranging from 0.6 to 1.2 nm are deposited on polyethersulfone (PES) films by replacing surfactants around SWCNTs dispersed in aqueous solution, for supporting uniform and smooth sub‐10 nm PA nanofilm formed through aqueous‐organic bilayer interfacial polymerization. The industrial scale manufactured PA/SWCNTs/PES desalination membranes (508 mm × 915 mm) are rolled into spiral wound elements without damage through cutting, gluing, and rolling. The desalination tests on flat PA/SWCNTs/PES membranes exhibits 30 l m−2 h−1 (LMH) under 17.2 bar with 98.45% salt injection when fed with 2000 ppm NaCl at pH = 9. The normalized permeate flux of PA/SWCNTs/PES spiral wound elements is ≈17 LMH under 13.8 bar with 90% salt injection underfed with 2000 ppm MgSO4 at pH = 9–11 condition. The high‐performance sub‐10 nm smooth PA/SWCNTs/PES desalination membranes are fabricated with materials savings and can promote low operation costs compared to conventional 50–100 nm crumpled PA films on any supporting substrates.

Characterization and performance evaluation of in-house ultrafiltration membrane coupled with photocatalysis for 17α-methyltestosterone hormone removal.

17α-methyltestosterone (MT) hormone is a synthetic androgenic steroid hormone utilized to induce Nile tilapia transitioning for enhanced production yield. This study specifically focuses on the removal of MT through the utilization of photocatalytic membrane reactor (PMR), which employs an in-house polyvinylidene fluoride (PVDF) ultrafiltration membrane modified with 1% nanomaterials (either TiO2 or α-Fe2O3). The molecular weight cut-off (MWCO) of the in-house membrane falls within the ultrafiltration range. Under UV95W radiation, the PMR with PVDF/TiO2 and PVDF/α-Fe2O3 membranes achieved 100% MT removal at 140 and 160 min, respectively. The MT removal by the commercial NF03 membrane was only at 50%. In contrast, without light irradiation, the MT removal by all the membranes remained unchanged after 180 min, exhibiting lower performance. The incorporation of TiO2 and α-Fe2O3 enhanced water flux and MT removal of the membrane. Notably, the catalytic activity was limited by the distribution and concentration of the catalyst at the membrane surface. The water contact angle did not correlate with the water flux for the composited membrane. The degradation of MT aligned well with Pseudo-first-order kinetic models. Thus, the in-house ultrafiltration PMR demonstrated superior removal efficiency and lower operational costs than the commercial nanofiltration membrane, attributable to its photocatalytic activities.

A facile and efficient voltammetric sensor for marbofloxacin detection based on zirconium-based metal-organic framework UiO-66/nitrogen-doped graphene nanocomposite

Improper and persistent use of marbofloxacin (MAR) is prone to produce residues that deteriorate the surrounding environment and endanger our health. Hence, it is urgent to stablish a facile and efficient detection technique for the detection of MAR. Herein, a highly efficient electrochemical platform was constructed for sensitive determination of MAR using zirconium-based metal–organic framework (UiO-66)/nitrogen-doped graphene (NG) nanocomposites (UiO-66/NG). The surface morphology, crystalline phase, elemental composition, and electrochemical behavior of UiO-66/NG were characterized by various spectroscopic and electrochemical techniques. Owing to the synergistic interaction of UiO-66 MOFs and NG nanosheets, the UiO-66/NG exhibited remarkable catalytic activity for MAR oxidation. As consequently, the UiO-66/NG demonstrated a wide linear response range (0.01 − 10 μM), high sensitivity (1.80 μM μA−1 cm−2) and low detection limit (0.002 μM). The proposed UiO-66/NG/GCE demonstrated robust voltammetric responses even in the presence of excess potential interfering species and retained stable response signals for at least two weeks. More importantly, the proposed UiO-66/NG/GCE displayed highly consistent sensitivity toward MAR detection in both aquaculture water and milk matrices and PBS buffer, and achieved accurate and sensitive detection of MAR with good recovery. Together with its low cost and facile operation, the UiO-66/NG/GCE shows great prospects for trace detection of MAR from complex matrices.

A comparative study on the effectiveness of pollutants control measures adopted in the steel industry to reduce workplace and environmental exposure: a case study

Our understanding of the environmental and occupational health implications of pollutants emitted in steel production is still lacking, despite the considerable amount of research devoted to this topic. Given the significance of steel recycling and the need to reduce greenhouse gas emissions, many steel factories are adopting electric arc furnace (EAF) technology. The use of a technological system designed for the capture of pollutants emitted through EAF steel production is highly ecological because of its utilization of iron scrap and low investment cost. Despite this, the main issue with the EAF is the environmental impact it poses, specifically the release of pollutants into the air, such as dust and organic substances, chlorinated dioxins and furans, dioxin-like polychlorinated biphenyls and brominated dioxins and furans. As a result, workers in this field have a considerable rate of morbidity. The main challenge for EAFs is to optimize the capture of powders produced during the techno-logical process, both from the EAF and the workplace. A state-of-the art solution for managing pollutants in modern steel manufacturing is highlighted in this paper, featuring a method used in Romania that employs the Best Available Techniques (BAT) reference document for iron and steel production to directly collect pollutants from the EAF. The system included a cylindrical fitting, a heat exchanger to cool the gases and a hood to collect contaminants. In comparison to other ventilation options, this equipment boasts lower investment and lower operational costs because of its effective and minimal air flow. Through the use of cutting-edge technology and progressive strategies, we can move closer toward our objective of a workplace free from injuries in the steel industry.

Integrating project management with advanced cooling solutions for data centers: A path to enhanced energy efficiency

Data centers play a crucial role in modern digital infrastructure, but their energy consumption and associated carbon footprint are significant concerns. Among the various energy-consuming components of data centers, cooling systems stand out as major contributors. This paper explores the integration of project management principles with advanced cooling solutions to enhance energy efficiency in data centers. By effectively managing projects and implementing innovative cooling technologies, data center operators can achieve significant reductions in energy consumption and operational costs. The integration of project management practices with advanced cooling solutions involves several key steps. First, project management methodologies such as Agile or Waterfall are applied to plan and execute the implementation of advanced cooling technologies. This includes assessing current cooling systems, identifying suitable advanced solutions, and developing a timeline for implementation. Next, advanced cooling solutions such as liquid cooling, containment systems, or free cooling are deployed to reduce the energy required for cooling data center equipment. One of the primary benefits of integrating project management with advanced cooling solutions is enhanced energy efficiency. Advanced cooling technologies can significantly reduce the energy consumed by data center cooling systems, leading to lower operational costs and a smaller carbon footprint. Additionally, the use of project management methodologies ensures that the implementation of these technologies is carried out efficiently and effectively. Furthermore, this integration can lead to improved data center performance and reliability. By optimizing cooling systems, data center operators can ensure that IT equipment operates within optimal temperature ranges, reducing the risk of overheating and downtime. Additionally, the implementation of advanced cooling solutions can future-proof data centers against increasing heat loads from high-density computing equipment. In conclusion, integrating project management with advanced cooling solutions offers a promising path to enhance energy efficiency in data centers. By adopting this approach, data center operators can achieve significant energy savings, reduce their environmental impact, and improve overall operational efficiency.