Plant Layout Research Articles

Exploring Crop Production Strategies to Mitigate Greenhouse Gas Emissions Based on Scenario Analysis

In the context of global climate change and carbon neutrality goals, agriculture has emerged as a major source of greenhouse gas (GHG) emissions, and faces the critical challenge of reducing emissions while ensuring food security. However, existing research has rarely focused on dynamic simulation and scenario-based analysis of optimised agricultural layouts and their impact on GHG emissions. Taking the three northeastern provinces (Heilongjiang, Jilin, and Liaoning) of China as the study area, this study quantifies GHG emissions from major grain crops and employs time-series analysis and machine learning methods to conduct a scenario analysis, including three scenarios (Business as Usual, Sustainable Optimisation, and Ecological Priority). Specific policy implications are proposed for optimising agricultural layouts and mitigating GHG emissions. The results indicate that GHG emissions in Northeast China primarily stem from methane emissions in rice cultivation and nitrous oxide emissions from fertiliser use. A scenario analysis reveals that the “Sustainable Optimisation” scenario reduces GHG emissions by 22.0% through optimised planting layouts while maintaining stable crop production. The “Ecological Priority” scenario further enhances emission reductions to 25.2% by increasing the share of low-emission crops, such as corn, and reducing high-emission crops, such as rice. The study provides a practical reference for promoting the low carbonisation of agriculture, and demonstrates that optimising planting layouts and production structures can simultaneously achieve food security and climate change mitigation.

Design and Evaluation of Noise Simulation Algorithm Using MATLAB Ray Tracing Engine for Noise Assessment and Prediction

The Malaysian Department of Occupational Safety and Health (DOSH) reported that noise-induced hearing loss (NIHL) accounted for 92% of occupational diseases in 2019. To address this, accurate risk assessment is crucial. The current noise evaluation methods are complex and time-consuming, relying on manual calculations and field measurements. An easy-to-use, open-source noise simulator that directly compares the output with national standards would help mitigate this issue. This research aims to develop an advanced noise evaluation tool to assess and predict unregulated workplace noise, providing tailored safety recommendations. Using a representative plant layout, the Sound Pressure Level (SPL) is calculated using MATLAB’s ray tracing propagation model. The model simulates all possible transmission paths from the source to the receiver to derive the resultant SPL. A noise simulation application featuring a graphical user interface (GUI) built with MATLAB’s App Designer (version: R2024a) automates these computations. The simulation results are validated against the DOSH’s safety standards in Malaysia. Additional safety metrics, such as the recommended maximum exposure time and the required Noise Reduction Rating (NRR) for hearing protection, are calculated based on the SPLs for hazardous locations. The simulation algorithm’s functionality is validated against manual calculations, with an average deviation of just 3.06 dB, demonstrating the model’s precision. This tool can assess and predict indoor noise levels, provide information on optimal exposure limits, and recommend necessary protective measures, ultimately reducing the risk of NIHL in factory environments. It can potentially optimise plant floor operations for existing and new facilities, ensuring safer shift operations and reducing worker noise hazard exposure.

A Method for Quantifying Mung Bean Field Planting Layouts Using UAV Images and an Improved YOLOv8-obb Model

A Method for Quantifying Mung Bean Field Planting Layouts Using UAV Images and an Improved YOLOv8-obb Model

Numerical analysis of evaporation reduction in floating photovoltaic power plants: influence of design parameters

Evaporation reduction is one of the advantages provided by floating photovoltaic (FPV) power plants. However, few studies have yet been carried out to understand how to optimise the layout of FPV power plants in order to provide better water management. Indeed, the interaction between atmospheric conditions, water bodies, and the FPV plant creates a dynamic system that is challenging to study and accurately model. This paper investigates the impact on evaporation of various characteristics of FPV plants, such as float technology, plant positioning and orientation, distribution, and coverage ratio. This study was performed using Computational Fluid Dynamics (CFD) of the surrounding atmosphere, with the impact of the FPV plant modelled using specific boundary conditions to reduce computational costs. The numerical results show that the coverage ratio is the most important factor in reducing evaporation. Full coverage could reduce evaporation by 52.8% for a plant with a large footprint on the water and by 43.4% for a plant with a smaller footprint. Other parameters have only a moderate impact, allowing the fine-tuning of evaporation reduction. The optimal configuration would involve covering the entire water body with a single large water footprint island positioned downwind of the prevailing transversal winds. This setup significantly reduces evaporation, thereby enhancing water conservation and making an FPV power plant a valuable tool in sustainable water management.

ENVI-met Simulation of Green Plant Layouts for Urban Thermal Comfort Optimization

ENVI-met Simulation of Green Plant Layouts for Urban Thermal Comfort Optimization

Can a Light Detection and Ranging (LiDAR) and Multispectral Sensor Discriminate Canopy Structure Changes Due to Pruning in Olive Growing? A Field Experimentation.

The present research aimed to evaluate whether two sensors, optical and laser, could highlight the change in olive trees' canopy structure due to pruning. Therefore, two proximal sensors were mounted on a ground vehicle (Kubota B2420 tractor): a multispectral sensor (OptRx ACS 430 AgLeader) and a 2D LiDAR sensor (Sick TIM 561). The multispectral sensor was used to evaluate the potential effect of biomass variability before pruning on sensor response. The 2D LiDAR was used to assess its ability to discriminate volume before and after pruning. Data were collected in a traditional olive grove located in Tenute di Cesa Farm, in the east of Tuscany, Italy, characterized by a 4x6 m planting layout and by developed plants. LiDAR data were used to measure canopy volumes, height, and diameter, and the generated point cloud was studied to assess the difference in density between treatments. Ten plants were selected for the study. To validate the LiDAR results, manual measurements of the canopy height and diameter dimensions of the plants were taken. The pruning weights of the monitored plants were obtained to assess the correlation with the canopy characterization data. The results obtained showed that pruning did not affect the results of the multispectral sensor, and the potential variation in canopy density and porosity did not lead to different results with this instrument. Plant volumes, height, and diameters calculated with the LiDAR sensor correlated well with the values of manual measurements, while volume differences between before and after pruning obtained good correlations with pruning weights (Pearson correlation coefficient: 0.66-0.83). The study of point cloud density in canopy thickness and height showed different shapes before and after pruning, especially in the former case. Correlations between point cloud density obtained from LiDAR and multispectral sensor results were not statistically significant. Even if more studies are necessary, the results obtained can be of interest in pruning management.

Application of System Layout Planning (SLP) in Factory Layout Design

In manufacturing setups characterized by low volume, high optionality, substantial work content, and reliance on trivial knowledge, small and medium-scale industries often lack a systematic approach when it comes to redesigning their existing manufacturing lines or launching new manufacturing process lines. Traditional approaches to plant layout design, while having served their purpose in the past, come with inherent limitations and challenges that may hinder the adaptability and competitiveness of manufacturing facilities in the United States. This white paper delves into the pivotal role of plant layout design in industrial settings for a manufacturing line that consists of 16 sub-assembly lines, explores the drawbacks associated with conventional methods, and advocates for the adoption of a scientific, data-driven approach, precisely, Systematic Layout Planning (SLP), to overcome these challenges and propel manufacturing into a more efficient and adaptable future.

Integration of a solid oxide electrolysis system with solar thermal and electrical energy: A testing campaign for operation and control strategy definition

AbstractThe EU project PROMETEO has the scope of testing a 25 kW solid oxide electrolysis system integrated with a concentrated solar power plant via thermal energy storage in a relevant environment. Given the plant layout and the hydrogen demand characteristics, this work aims to identify how to operate the system effectively when renewable electricity is unavailable and how to modulate the load during hydrogen generation, thus defining the system's operation modes and control strategy. A 5 kWe stack has been tested at the FBK facility. The hot standby tests show that feeding a reducing gas at the negative electrode and air at the positive electrode, without polarizing the stack, effectively keeps the stack hot at 750°C and prevents degradation. Conversely, the electric protection approach leads to significant stack degradation (15% voltage drop in 200 h for one cluster). Regarding modulation of hydrogen generation, with low steam flowrates, the stack current and the flow rate of produced hydrogen mainly depend on the steam flow rate, while it is not affected by the stack temperature; conversely, with high steam flowrates, the current depends only on the stack temperature (from 25 A at 670°C to 65 A at 760°C). Based on the results, two hot standby modes and two load control strategies to be implemented and tested in the PROMETEO prototype are proposed.

Influence of Spatial Scale Effect on UAV Remote Sensing Accuracy in Identifying Chinese Cabbage (Brassica rapa subsp. Pekinensis) Plants

The exploration of the impact of different spatial scales on the low-altitude remote sensing identification of Chinese cabbage (Brassica rapa subsp. Pekinensis) plants offers important theoretical reference value in balancing the accuracy of plant identification with work efficiency. This study focuses on Chinese cabbage plants during the rosette stage; RGB images were obtained by drones at different flight heights (20 m, 30 m, 40 m, 50 m, 60 m, and 70 m). Spectral sampling analysis was conducted on different ground backgrounds to assess their separability. Based on the four commonly used vegetation indices for crop recognition, the Excess Green Index (ExG), Red Green Ratio Index (RGRI), Green Leaf Index (GLI), and Excess Green Minus Excess Red Index (ExG-ExR), the optimal index was selected for extraction. Image processing methods such as frequency domain filtering, threshold segmentation, and morphological filtering were used to reduce the impact of weed and mulch noise on recognition accuracy. The recognition results were vectorized and combined with field data for the statistical verification of accuracy. The research results show that (1) the ExG can effectively distinguish between soil, mulch, and Chinese cabbage plants; (2) images of different spatial resolutions differ in the optimal type of frequency domain filtering and convolution kernel size, and the threshold segmentation effect also varies; (3) as the spatial resolution of the imagery decreases, the optimal window size for morphological filtering also decreases, accordingly; and (4) at a flight height of 30 m to 50 m, the recognition effect is the best, achieving a balance between recognition accuracy and coverage efficiency. The method proposed in this paper is beneficial for agricultural growers and managers in carrying out precision planting management and planting structure optimization analysis and can aid in the timely adjustment of planting density or layout to improve land use efficiency and optimize resource utilization.

Design optimization and performance analysis of a dry-cooled Helium-Xenon Brayton cycle for nuclear microreactor based on detailed models of the cycle components

Nuclear microreactors offer reliable, low-carbon dispatchable power and heat for various end use and applications. The gas-cooled reactor coupled with the dry-cooled closed Brayton cycle has a simple plant layout and can be deployed in water-deficient areas. To evaluate the system performance more precisely and optimize the mole fraction of the He-Xe mixture for the gas-cooled microreactor, an integrated design method based on detailed models of the cycle components was developed. Three designs using 4 g/mol pure helium, 15 g/mol, and 40 g/mol He-Xe were first established as demonstration examples, and performances of the cycle and components were compared. Furthermore, the effects of the He-Xe’s molecular weight on the system’s size and efficiency were discussed, and a parametric analysis of crucial design parameters like specific speed and pressure ratio was conducted. In contrast to the previous results obtained from simplified component models, the current results revealed that a Brayton cycle using 40 g/mol He-Xe could achieve a higher thermal efficiency of 44.42 % compared with 37.65 % of pure helium, which resulted from the improved efficiency in turbomachinery and reduced pressure loss in heat exchangers. Concerning the system size, it was recommended to use the 20–30 g/mol He-Xe for reduced volume as the stage number of the turbomachinery decreased from 5 of pure helium to a single stage of the 20 g/mol He-Xe. Although the turbomachinery occupied a relatively small volume, increasing the compressor inlet temperature could reduce the volume of the precooler, thus significantly reducing the system volume.

Thermodynamic evaluation of an IGCC power plant utilizing allothermal gasification

The present work conducts a comprehensive thermodynamic analysis of a 150 MWe Integrated Gasification Combined Cycle (IGCC) using Indian coal as the fuel source. The plant layout is modelled and simulated using the “Cycle-Tempo” software. In this study, an innovative approach is employed where the gasifier's bed material is heated by circulating hot water through pipes submerged within the bed. The analysis reveals that increasing the external heat supplied to the gasifier enhances the hydrogen (H2) content in the syngas, improving both its heating value and cold gas efficiency. Additionally, this increase in external heat favourably impacts the Steam-Methane reforming reaction, boosting the H2/CH4 ratio. The thermodynamic results show that the plant achieves an energy efficiency of 44.17% and an exergy efficiency of 40.43%. The study also identifies the condenser as the primary source of energy loss, while the combustor experiences the greatest exergy loss.

Mapping Fruit-Tree Plantation Using Sentinel-1/2 Time Series Images with Multi-Index Entropy Weighting Dynamic Time Warping Method

Plantation distribution information is of great significance to the government’s macro-control, optimization of planting layout, and realization of efficient agricultural production. Existing studies primarily relied on high spatiotemporal resolution remote sensing data to address same-spectrum, different-object classification by extracting phenological information from temporal imagery. However, the classification problem of orchard or artificial forest, where the spectral and textural features are similar and their phenological characteristics are alike, still presents a substantial challenge. To address this challenge, we innovatively proposed a multi-index entropy weighting DTW method (ETW-DTW), building upon the traditional DTW method with single-feature inputs. In contrast to previous DTW classification approaches, this method introduces multi-band information and utilizes entropy weighting to increase the inter-class distances. This allowed for accurate classification of orchard categories, even in scenarios where the spectral textures were similar and the phenology was alike. We also investigated the impact of fusing optical and Synthetic Aperture Radar (SAR) data on the classification accuracy. By combining Sentinel-1 and Sentinel-2 time series imagery, we validated the enhanced classification effectiveness with the inclusion of SAR data. The experimental results demonstrated a noticeable improvement in orchard classification accuracy under conditions of similar spectral characteristics and phenological patterns, providing comprehensive information for orchard mapping. Additionally, we further explored the improvement in results based on two different parcel-based classification strategies compared to pixel-based classification methods. By comparing the classification results, we found that the parcel-based averaging method has advantages in clearly defining orchard boundaries and reducing noise interference. In conclusion, the introduction of the ETW-DTW method is of significant practical importance in addressing the challenge of same-spectrum, different-object classification. The obtained orchard distribution can provide valuable information for the government to optimize the planting structure and layout and regulate the macroeconomic benefits of the fruit industry.

Chemical plant optimization layout based on the domino hazard index considering the fixed hazard unit outside the available area

The layout of chemical plants is a significant step to promote the safe and efficient operation of a chemical factory. In the actual production process, the chemical process plant layout may be affected by immovable hazards outside the available layout area. In this paper, the external hazard unit is arranged as one of the chemical process plants. The domino effect potential of all chemical process plants is quantified by using the classical domino hazard index (DHI). A layout optimization model considering the effects of external hazard units has been proposed to obtain the optimal plant layout from economic and safety aspects. The feasible layout solutions are obtained under the orientation, boundary and non-overlapping constraints by the non-dominated sorting genetic algorithm II (NSGA-Ⅱ). The proposed model is further analyzed through a hypothetical case of three storage tanks outside the acrylic acid (AA) production plant layout area. The results show that the total cost range for the optimal solution is 650348–1365443 $, with corresponding DHI values ranging from 29 to 129. The plant with larger DHI value will be arranged to far away from the external hazard units to obtain a safer layout. This work can provide rational layout solutions for the layout designers to make different decisions according to the actual situation.

A modified bi-objective NSGA-II approach to sustainability in reconfiguration planning of dynamic cellular manufacturing systems

Manufacturing plant layouts are developed to facilitate optimal process flow. Modern manufacturing systems must meet present production demands and be adaptable to changes in process flow in the future. Dynamic Cellular Manufacturing Systems (DCMS) increase the flexibility of layouts by reconfiguring cell structure and equipment distribution, to effectively adjust part routings for optimal process flow. Frequent reconfiguring of plant layout may not always be feasible or economical, however, when new product releases are planned, reconfiguring the plant layout to optimise the work-flow may be extremely beneficial. This paper presents a Non-dominated Sorting Genetic Algorithm (NSGA-II) approach to solving a DCMS problem in a sustainable, and responsible manner. A bi-objective integer programming model was developed over multiple planning horizons with fluctuating product demands. This model aims to achieve sustainability by reducing the cost of production, mitigating the environmental impact of production, and minimise negative social impacts on labourers that work in such environments. A penalty function approach was used to enforce the model constraints during optimisation. This study details trade-offs between the economic factors of a DCMS, the environmental implications of reconfiguring such a system, and the social impacts of reconfigurations on the workforce.

Novel Use of Concentrated Solar Thermal Energy for Producing Highly Thermal Activated Materials for CCUS via Mineral Carbonation of Mine Waste

An assessment of the levelised cost and associated CO2-eq emissions for the thermal activation of serpentine mine tailings to be used as activated feedstock for CCUS processes via mineral carbonation, is reported here for the first time. Two main technological scenarios were assessed, based on either direct fuel sources heating (natural gas and hydrogen) or indirect, CST-based heating with a back-up burner and storage to provide continuous operations, for a 200 ton/hr of processed ore and a targeted roasting ore temperature of 700°C. For CST-based systems, 3 different solar input scales, namely 50, 150 and 450 MWth, were considered, and simulations performed over a year timeline with a 10 minutes time step, using Mt Keith Nickel mine in Western Australia as the reference location. The analysis highlighted that the proposed CST-hybrid plant layout can achieve similar cost to that of fuel-only cases with current Australian fuel prices for natural gas and hydrogen, with lower CO2-eq emissions, and a parity cost with fuel-only scenarios of some 16 USD/GJ. The proposed CST-hybrid plant layout was also identified as the potential, preferred route over direct CST routes to achieve 24/7 continuous heat supply while retaining fine tuning of activation temperature, given a very narrow temperature window of activation for the chosen mine tailings for mineral carbonation processes.

Integrated environmental management and GPS-X modelling for current and future sustainable wastewater treatment: A case study from the Middle East

In the context of today's rapidly changing environmental challenges, accurately predicting the performance and efficiency of environmental management strategies is crucial. Particularly in the Middle East, where research on wastewater treatment plants (WWTPs) is notably lacking, addressing this need is imperative. This study investigates the treatment efficiency of a wastewater treatment plant and proposes various techniques to enhance its performance. Employing a case study method, we utilise the GPS-X model to forecast the plant's performance under diverse scenarios, offering solutions for future challenges. The results reveal that the current plant layout operates efficiently, with removal efficiencies for Total Suspended Solids (TSS), Chemical Oxygen Demand (COD), and Biochemical Oxygen Demand (BOD) at 98.3 %, 95.1 %, and 96.1 %, respectively. The outlet Dissolved Oxygen (DO) of 1.9 mg/L meets local wastewater reuse standards. Furthermore, the GPS-X model forecasts the plant's performance under different scenarios, suggesting the feasibility of a new layout within 20–25 years and the need for additional units after 40 years. As inflow approaches maximum design capacity, simulation results underscore the importance of utilising the full plant design and expanding it for optimal operation over 60 years. This research provides critical insights for improving WWTP performance and emphasizes the significance of strategic planning in addressing long-term environmental management challenges. Moreover, this study represents a pioneering effort in addressing critical water scarcity challenges in Jordan by exploring the potential of treated wastewater (TWW) as a sustainable solution, thus contributing to the advancement of environmental management practices in the region.

SLP (Systematic Layout Planning) for Enhanced Plant Layout Efficiency

SLP (Systematic Layout Planning) for Enhanced Plant Layout Efficiency

Land-based wind plant wake characterization using dual-Doppler radar measurements at AWAKEN

Wind plant wakes have been shown to persist for tens of kilometers downstream in offshore environments, reducing the power output of neighboring plants, but their behavior on land remains relatively unexplored through observation. This study capitalizes on the unique and extensive field data collected for the American WAKE ExperimeNt (AWAKEN) project underway in northern Oklahoma. X-band dual-Doppler radars deployed at this site measure wind speed and direction at 25-m and 2-min resolution within a 30-km range, capturing the interactions between three neighboring wind plants. These measurements show that the wake of one wind plant extends at least 15 km downstream under easterly wind and stable atmospheric conditions. Though the wake wind speed increases within the first 10 km, it plateaus at 90% of the freestream wind speed. The spanwise velocity distribution within the wake initially shows the clear signature of the wind plant layout, which is smoothed as it propagates downstream, indicating spanwise momentum transfer is a key mechanism in wind plant wake development and recovery. These findings have important implications for wind plant siting decisions and resource assessments, and provide insights into atmospheric interactions at the wind plant scale.

How Industry 4.0 technologies can contribute to plant layout design and management: a systematic literature review

How Industry 4.0 technologies can contribute to plant layout design and management: a systematic literature review

Application of Kaizen Principles to a Small Scale Industry in India

This case-study presents the application of Kaizen concept to Chempromech Engineers Pvt. Ltd. in Butribori, Maharashtra, India. The work carried out focuses on Kaizen approach to the Plant Layout of the industry to make it more efficient and desirable to work in as well as gives a formula to the industry to calculate its production in kg/hr theoretically. Chempromech Engineers Pvt. Ltd. Is a small scale industry present in the Butibori MIDC area in Nagpur, Maharashtra which specializes in manufacturing of circlip washer wires and washers. Being a small-scale industry, it is faced with problems pertaining to limited workspace, so a new layout is designed which helps groups machines based in their product type and thus freeing out space for future expansion. Product Based Plant Layout is preferred for this industry as its products vary in size and weight. Key words:- Kaizen, Plant Layout, Product Based Plant Layout, Washers and Washer wire.