Floor Space Research Articles

Analyzing Energy Consumption in Universities: A Literature Review

This study investigates energy consumption in general and in universities in particular. A literature review was used as the methodology of the study to show the energy consumption purposes, major findings, research gaps, limitations, and future research about how to analyze energy consumption levels. The number of references examined was 60, with 29 references about universities and some of them are concentrating on the buildings’ consumption in the GCC area. Most of the references concentrated on investigating case studies in different countries. Analysis of the findings showed that tools such as big data analytics, machine learning, simulations, and predictive models were used. However, big data analytics was the most important one. It was found that AC systems are the most important component of energy consumption, especially in hot weather countries. The studies also showed that monitoring the consumption rates will reduce the total consumption of energy. In universities, the type of the building and the day index were found the most important factors affecting energy consumption. Factors such as number of smart devices, location, and floor space were found to have different positive and negative impacts on energy consumption from one study to another. Recommendations for future research were also presented.

PSIII-6 Tail damage caused by tail biting in growing-finishing pigs housed in two group sizes

Abstract Tail biting can compromise the welfare of pigs and cause economic losses for pork producers, but little is known about the development of tail biting and its resulting impact on pigs. In this study, we investigated victimization by tail biting and the resulting impacts on the welfare and performance of pigs housed in two group sizes. Pigs (n = 432, initial body weight = 22.0 ± 3.7 kg) with intact tails were housed in large (LG = 18 pigs/pen, 12 pens) or small groups (SG = 9 pigs/pen, 24 pens) in a barn with fully slatted floors for 14 wk until market weight (120.7 ± 11.8 kg). Floor space (0.76 m2/pig) and feeder space (4 feeder spaces/9 pigs) allowance were identical between group sizes, and pigs were stratified by initial body weight and sex across treatment pens. Growth performance, pig removal, and tail damage were monitored throughout the study. Tail damage was assessed for each pig weekly and during tail biting outbreaks, using a subjective scoring system (0 = no damage; 1 = healed lesions with small scabs; 2 = puncture wounds with visible blood; 3 = wounds with signs of infection; 4 = partial or total loss of the tail). The maximal tail score (MTS) each pig received every four weeks and over the entire 14 weeks was summarized. Pigs that received MTS of ≥ 2 were considered victimized by a tail biter. Data were analyzed using Glimmix procedure with logit function and FREQ procedure with chi-square and CMH test of SAS software. Compared with SG, LG had greater MTS during the initial 4 wk (1.1 vs. 0.8, chi-square = 17.9, df = 1; P < 0.001) and reduced MTS during the last 2 wk (0.7 vs. 0.9, chi-square = 4.8, df = 1; P = 0.03), suggesting that tail damage declined as pigs grew in LG, but not in SG. The number of pigs removed for tail biting tended to be less and those removed for death and sickness tended to be greater in LG than in SG (chi-square = 7.4; df = 3; P = 0.06). Across group sizes, 68% of the removed pigs (n = 28) were victimized by tail biters (MTS ≥ 2). Between group sizes, there was no difference in time to first victimization or how often individual pigs were victimized throughout the study. Across group sizes, 45% of pigs were never victimized, but 22%, 16%, and 9% were victimized 1, 2, and 3 times, respectively. Eight percent of pigs were victimized more than three times, including 6% with MTS of 3 or 4. Pigs with MTS of 4 over the entire study period were three times more likely (odds ratios between 3.18 and 3.70; all P ≤ 0.03; Table 1) to have market weight lower than the average compared with other pigs. Based on these results, we suggest that management strategies should prevent multiple victimizations or tail loss to maintain pig welfare and performance.

304 What does Prop 12 mean for the swine industry

Abstract California’s Proposition 12, also known as the Farm Animal Confinement Initiative, has been fully implemented as of January 1st, 2024. This measure regulates the minimum space requirements for egg-laying hens, dairy calves raised for veal, and breeding pigs in order for the associated products to be sold within the state of California. Suppliers of these covered products need to be accredited by specific, third-party certifying agents to be certified as ‘Prop 12 compliant’. For the swine industry, the spotlight is on the housing of any female breeding pig over the age of 6 mo. These animals must be in an enclosure that allows them to lie down, stand up, turn around, and fully extend their limbs without touching the sides of their stalls or another animal (24 square feet of floor space per animal). These regulations also limit the duration of time producers can house animals in closed crates before farrowing to 5 d. While these housing regulations do not apply during the nursing phase, research contexts, during veterinary treatment or immediately before slaughter, they do apply in the post-weaning phase. This means that the animals cannot be confined for heat-checking or breeding to be considered ‘Prop 12 compliant’. These housing standards have no minimum herd size and apply to those in commercial or private farms if there will be products produced and sold. With any change to the standard operating procedures of animal husbandry, there will be some growing pains. These issues can be addressed when considerations are given to the group composition (age and size of sows), pen mixing practices (pre or post breeding), feeding schedule [collective (trough, floor fed) or individual (electronic sow feeding, free access stalls)], and, pen structural quality (flooring, enrichment). This measure will have considerable economic and ethical implications related to barn renovations, animal care staff training, and husbandry practices for the swine industry.

Dynamic Analysis of the Growth of Building Area and the Immigrant Population in Shanghai based on the PVAR Model

Since the reform and opening up more than 30 years ago, Shanghai has witnessed rapid development of economic and continuous acceleration of urbanization and continuous growth of building area. However, the number of migrants has decreased over the same period, which is inconsistent with previous studies that show that population affects land demand and floor space. In this paper, panel data of each district of Shanghai from 2014 to 2018 are selected and the panel vector autoregression model (PVAR model) is constructed to analyze the dynamic relationship between the building area growth of each district of Shanghai, the immigrant population and the economic growth. The results show that : (a)There is no long‐term equilibrium relationship between the growth of Shanghai's floor area and the migration of foreign population. (b) The construction area growth in Shanghai can affect the regional GDP growth to a certain extent. (c) The migration of migrants into Shanghai has a certain effect on the economic growth of Shanghai.

Use of red grape pomace and Aloe vera gel as nutraceuticals to ameliorate stocking density-induced stress in commercial male broilers

The combined effect of Aloe vera gel (AVG) administered through drinking water and dietary red grape pomace powder (RGP) on growth performance, physiological traits, welfare indicators, and meat quality in densely stocked broilers was evaluated. A total of 750, two-week-old male Ross 308 broilers (317.7 ± 10.12 g live weight) were randomly assigned to 25 cages, with each cage as an experimental unit. The broilers were stocked at a density of 30 birds per cage with a floor space of 1.32 m2. Dietary treatments were a standard grower or finisher diet (CON); CON containing 30 g RGP /kg diet plus either 1 (GPA1), 2 (GPA2), 3 (GPA3), or 4% (GPA4) AVG in drinking water. Treatment GPA1 promoted higher (P < 0.05) overall weight gain and overall feed conversion ratio (FCR) than CON. Positive quadratic effects (P < 0.05) were noted for mean corpuscular hemoglobin, basophils, 24-hour breast meat yellowness, chroma, and hue angle. The GPA2 group had the lowest (P < 0.05) gait score while the CON group had the highest score. Concurrent supplementation with a 30 g RGP /kg diet plus 1% AVG in drinking water enhanced weight gain, FCR, and finisher weight of densely stocked broilers. However, AVG doses beyond 1% did not enhance performance and physiological traits in densely stocked broilers.

UNDERSTANDING THE DYNAMICS OF URBAN HEAT ISLAND AS A FUNCTION OF DEVELOPMENT REGULATIONS

This study is the first-ever attempt to relate the tools of development control like Floor Space Index (FSI/FAR), ground area covered by building footprints (BFs), and proportions/configurations of open areas, with their impact on the surface urban heat island (SUHI) which modulates the air temperatures. In the case of the Indian megacity Mumbai, statistical analysis of the land surface temperatures (LST) and its correlation with the selected development indicators, reveals that for an FSI increase of 1.0 to 1.8 the SUHI is found to be–2.5 °C less and when BFs reduced from 90% to 42% SUHI was also reduced by –2.5 °C. Highrise development with a large plot size is desirable whereas low-rise development with FSI 1.0 on small plot sizes exhibits the highest SUHI. Open spaces without vegetation do not reduce SUHI. The correlation of development regulations with SUHI intensity will help urban planners to make more informed decisions.

The Relationship between Emotional Perception and High-Density Built Environment Based on Social Media Data: Evidence from Spatial Analyses in Wuhan

The utilization of Social Media Data (SMD) from location-based services offers a wealth of information to analyze changes in human emotional perception influenced by high-density built environments. This study aimed to examine the impact of high-density built environment factors on human emotion perception. First, a set of indicators for high-density built environments was established. Subsequently, Natural Language Processing (NLP) was employed to analyze SMD for sentiment identification and classification. Finally, the Multi-scale Geographically Weighted Regression (MGWR) model was utilized to investigate the spatial differentiation of human emotional perception in high-density built environments. The findings revealed that positive emotions display spatial variations in high-density built environments. Additionally, positive emotions were found to be influenced by multiple variables, with different variables simultaneously affecting individuals’ positive emotions. Specific built environment indicators showed positive correlations with Open Space Ratio (OSR), Green Space Ratio (GSR), POI Functional Density (PFD), and Road Network Density (RND), while negative correlations with Floor Space Index (FSI), Ground Space Index (GSI), Building Average Layer (BAL), Water Index (WI), and Space Syntax Integration (SSI) were observed. Normalized Difference Vegetation Index (NDVI), POI Functional Mixture (PFM), Space Syntax Choice (SSC), and Population Density (PD) exhibited mixed results in different spatial contexts. This research on human perception provides insights for refined urban design and governance, addressing the limitations of top-down approaches in dense urban renewal.

An application of the Random Forest algorithm for the prediction of Solar Envelope ‘Floor Space Index’ based on spatiotemporal parameters

It is becoming increasingly important to consider access to the sun in the early stages of a new building's design process. A Solar Envelope is an architectural form that meets required levels of density, whilst also assuring solar access to neighbourhood surfaces, thereby making it feasible to implement active and passive solar technologies there. This preliminary study investigated the cross-cutting intersection between urban morphology, Solar Envelope forms, and a Random Forest algorithm to predict the Solar Envelope's Floor Space Index. Recognizing that Solar Envelope forms depend on various spatiotemporal contexts, mainly the solar exposure cut-off period (equinoxes/solstices) and various neighbourhood geometrical attributes, simulations varying only the rooftop typologies (flat, gable, hip, sled, mansard, and pyramid) and façade orientations (south, east, west, and north) were conducted to evaluate how solar access to those surfaces affect the Floor Space Index of the Solar Envelope. Architectural tools were used to conduct simulations reflecting varying spatiotemporal scenarios. The data was extracted and represented geometrically, involving polar loci, and this synthetic dataset was subsequently utilized to train and evaluate a Random Forest algorithm. The results of this study show that the Random Forest algorithm was able to predict the Floor Space Index of the Solar Envelope with about 90.18% accuracy, though the only parameter influencing the regression model was the solar exposure cut-off period and not any other morphological features. Therefore, the study sheds insight into the need for the development of a more robust dataset through the simulation of randomized and diversified neighbourhood morphologies.

Retail operations strategy for improved customer experience: a better response to crises such as COVID-19 pandemic

Purpose Discount grocery stores (DGSs) are attractive food supply chain (FSC) channels because many cost-conscious Indians use them for monthly needs. Despite capacity, DGSs must address customer concerns about store crowd densities and improve their COVID-19 preparedness. The purpose of this study is to learn how retail operations strategies can improve customer experience and how stores can benefit. Design/methodology/approach The study looked at a case study where retail operations are run more efficiently, and the customer experience is enhanced by standardizing and customizing customer transactions. The potential benefits that customers and retailers might anticipate are then statistically verified. Next, the potential benefits were examined to determine which ones from customers’ and retailers’ views should be prioritized to increase satisfaction. Findings The case situation analysis in the study demonstrates how DGSs can improve their retail operations to reduce customer wait times and provide greater convenience. The study also provides practitioners with potential benefits to pursue from the perspectives of retailers, customers and both retailers and customers. Research limitations/implications This study requires many past transactions and can be considered an extension of the current study, so it does not capture floor space and capacity improvements. Practical implications This research can help FSC retailers compete with upstream supply chain partners and customers in omnichannel retailing. By improving DGS retailer capacity and customer experience, this study can benefit all FSC stakeholders. Originality/value Although there are numerous potential benefits that practitioners can pursue, the current study suggests that practitioners focus on those that can improve retailer and customer satisfaction.

8. META-HEALTH. USING THE METAVERSE TO FACILITATE THE UNDERSTANDING OF THE PATIENT'S INFORMED CONSENT AND THEIR PERIOPERATIVE PROCESS

Abstract Introduction The informed consent (IC) process can sometimes result in a lack of understanding due to the technical nature of the information provided. Coupled with the physical disorientation within the hospital, this can lead to perioperative anxiety and a greater risk of complications. Methods META-health is an application for mobile devices that seeks to improve these deficiencies using metaverse and extended reality visualization technologies. By recreating the hospital environment in a virtual setting, it allows repeating the preoperative consultation and visualization of various hospital areas, including the hospitalization floor, operating room, and consultation spaces. Multimedia content is included so that the information can be more easily understood. In addition, gamification has been implemented as an option to integrate entertainment into the understanding process of stomatal management. Results The pilot application was modeled and developed, and the first focus group was held to assess the quality, management, orientation, and comprehension of content. The sample of 12 patients indicated proposals for improvement and functional errors: 66.7% required control of the explanatory videos, 75% requested information on ostomies and difficulties in handling the joystick. The application is currently focused on colorectal cancer patients and intends to expand to other conditions and functionalities to become a functional metaverse. Finally, 100% of participants confirmed the usefulness of the idea and the importance of receiving information and support throughout the process. Conclusion The use of extended reality and the metaverse improves the understanding of informed consent (IC) by patients and relatives, as well as decreases perioperative anxiety.

Data Centre Refurbishment with the aim of Energy Saving and Achieving Carbon Net Zero

Data Centre Refurbishment with the aim of Energy Saving and Achieving Carbon Net Zero

Prediction of Medical Record Storage Requirement Using Forecasting Technique

Abstract Context: Medical records storage is a valuable and statutory requirement, but for any hospital, it is always most challenging. Many studies on the quality of medical records have been available but very few regarding storage space. Aims: This study uses a forecasting technique to measure the storage space requirement for medical records. Settings and Design: The study is a record-based study using the moving average forecasting technique in a tertiary care 900-bed public hospital in eastern India. Subjects and Methods: The data of the medical record files were collected from 2014 to 2022 years and used the moving average forecasting technique to get the forecasting till 2040. Accordingly, average racks and shelves and floor space requirements were calculated based on forecasted data. Statistical Analysis Used: Simple statistics and moving average forecasting technique was used using Microsoft Excel. Results: The forecasted number of medical record generation data was calculated using moving average forecasting techniques till 2040. From 200 racks and 1168 shelves, it was calculated to be an average of 113 ± 35 records per shelve, 678 ± 35 records per rack, and 3.75 square feet of space per rack is required. Accordingly, cumulative records, eligible for destruction after the retention period, effective cumulative records, racks, and floor space required were calculated. Conclusions: Proper storage of medical records is essential for optimal patient care and medical legal aspects but is a challenge in most organizations. The study findings conclude the forecasted space requirement for medical records and choose a strategic plan accordingly for efficient management of the medical records.

Automatic elevator shaft inspection using a multi-sensor measuring system and computer vision techniques

The present work introduces a system capable of automatically measuring the dimensions of an elevator shaft using computer vision approaches and optical sensors without human intervention. Miscomputations on the available volume of the elevator shaft could lead to the manufacturing of a cabin that cannot be utilized due to the customization of the product. Hereupon, it is crucial to calculate the smallest cross-section in the shaft since this area affects the maximum floor space of the elevator. The suggested methodology employs a low cost multisensor measuring system incorporating a Jetson Nano, a LiDAR, laser sensors, and a Micro Processor Unit (MPU) that scans the whole elevator shaft in one single run and reconstructs it, evaluating the examined shaft. The arrangement descents through a pulley into the investigated shaft using one string on each side, with a weight hanging at the end to increase stability and avoid rotations. Finally, validation experiments were performed in a test elevator shaft, which was manually measured in each floor to provide a ground truth. The acquired results showed sufficient accuracy of less than 1 % and reliability, assuring the proper dimensioning of the elevator shaft and the high standards of the lift industry.

Performance investigation and mass transfer enhancement of a novel cone-type solar seawater still

There are some disadvantages in the operating process of the basin solar seawater still (BSSS), such as long mass transfer distance, large heat indolence, huge floor space, and poor bearing pressure ability. A novel cone-type solar seawater still (CTSSS) is presented to overcome the weaknesses of the BSSS in this study. The CTSSS has the characteristics of seawater liquid film evaporation, short mass transfer distance, the condensation sleeve is parallel to and above the evaporation sleeve, and the condensation area is larger than the evaporation area. In order to clarify the performance of the CTSSS, the influence mechanism of feed seawater mass flow rate, heating power and heating temperature on the fresh water yield of the CTSSS was analyzed, the method of enhancing the mass transfer of the binary mixed gas in the CTSSS was explored, and the law of heat and mass transfer of the binary mixed gas in the annular enclosed small space was investigated. The results indicated that the maximum fresh water yield of the CTSSS is 62.7 g/20 min at the feed seawater mass flow rate of 400 g/h when the input power is 200 W, which is 4.5% higher than that when the feed seawater mass flow rate is 300 g/h. The performance ratio (PR) of the CTSSS is increased as the heating power, the PR of the CTSSS is 0.65 when 180 W heating power is employed. The steady state fresh water yield of the CTSSS with mirror condensation sleeve at 85°C is 84.6 g/20 min, which is 12.1% higher than that with non-mirror condensation sleeve Compared with the CTSSS with non-mirror condensation sleeve, the value of proportions of radiative heat transfer in the total heat transfer of the CTSSS with mirror condensation sleeve decreased by 6.6%, and the value of proportions of evaporative heat transfer increased by 6.4%. This study would provide a reference for small-scale decentralized application of solar desalination in remote areas.

Operational policies and performance analysis for overhead robotic compact warehousing systems with bin reshuffling

ABSTRACTThis paper studies a novel robotic warehousing system called the overhead robotic compact storage and retrieval system, which can free up the floor space occupation at a low cost. Bins, as basic storage containers, are stacked on top of each other to form a bin stack. Along overhead tracks, bin-picking robots transport bins between storage/retrieval positions and workstations with the aid of track-changing robots. Little research has been done to study operational policies and performance analysis for this new robotic compact warehousing system. We propose a nested queuing network model that considers two transportation resources and performs reinforcement learning using real data to improve the reshuffling efficiency. We find that reinforcement learning based reshuffling policy greatly reduces the reshuffling distance and saves computation time compared to existing policies. We find that the storage policy of stacks affects the optimal width/length ratio regardless of the system height. Interestingly, we obtain the number of robots that can stabilise the system to avoid an explosion of the order queue; two more robots than that number will produce relatively low throughput times. Compared to an AutoStore system, using our system reduces cost by 30% with a slight increase in throughput time.

Has the provincial-level residential building sector reached the carbon peak? An integrated assessment model

Assessing the historical peak situation at the provincial level is critical to better predict the future evolution of residential building carbon emissions. However, the provincial carbon peak status of this sector is still unclear. To this end, this study proposes a carbon peak situation integrated assessment model (CPSIAM), which is utilized to comprehensively evaluate the provincial peak situation of total carbon emissions, carbon emissions per capita and carbon emissions per floor space of urban and rural residential buildings and figure out carbon peaking progress in each province. Then, the driving mechanism of differentiated carbon peak status of provincial residential building carbon emissions are examined using the panel STIRPAT model and group regression model. Results show that as for the three residential building carbon emission indicators, Heilongjiang and Shanghai have both reached their full peaks as of 2020, however the former is in passive decline and the latter is in an active peak. Population, population structure, and floor space per capita are the main variables causing the differentiated peak status. This study not only offers a general methodological system for assessing the regional carbon peak situation, but also empowers policymakers to develop effective and differentiated emission-reduction measures based on their knowledge of peaked regions.

Historical carbon peak situation and its driving mechanisms in the commercial building sector in China

Evaluating the peak situation of commercial building carbon emissions (CBCE) at the provincial level and revealing their differentiated driving mechanisms are extremely significant for achieving the national “Dual carbon” target. In this study, a new provincial-level carbon peak situation assessment model is constructed to evaluate the historical CBCE peak situations in China by integrating conditional judgement function, Mann-Kendall trend test, and Tapio decoupling model. Furthermore, the STIRPAT model and grouped regression model are combined to investigate the driving mechanisms on CBCE under different carbon peaking situations. Results showed that the CBCE in Beijing have reached the peak, and Shandong and Inner Mongolia have entered the peak potential period. Beijing achieved the decoupling of CBCE from value added of tertiary sector and floor space per capita. The most important factors leading to different peak situations of CBCE are commercial floor space per capita and energy intensity. Urban population, industrial structure, value added of tertiary industry per capita and energy structure show different degrees of influence on different peak stages of CBCE. This study provides a general methodology for evaluating the carbon peak situation and its driving mechanism. It sets the foundation for the formulation of the differentiated carbon peak pathway and provides a reference for the carbon emission assessment of other countries with regional carbon peak differences in the world.

Optimisation and analysis of an integrated energy system with hydrogen supply using solar spectral beam splitting pre-processing

The application of integrated energy systems (IES) in urban areas is gradually increasing, yet the constraint of limited building space poses a significant challenge to effective system planning. In this paper, to address the issue of area limitation from the perspective of improving solar energy utilization. A novel IES utilizing solar spectral beam splitting (SBS) for hydrogen production is proposed, which introduces SBS technology to make full use of the sun’s full-spectrum energy. Furthermore, the incorporation of photocatalytic hydrogen production introduces an innovative approach to meet the hydrogen needs of hydrogen refuelling stations, facilitating highly efficient co-generation of cooling, heating, electricity, and hydrogen supply. To determine the optimal system configuration, a comparison is made with a stand-alone solar system using a honey badger-simulated annealing optimization algorithm. The results show that the SBS-IES achieves a solar energy utilization rate of 37.72% and reduces equipment footprint by 20.48%. Furthermore, a sensitivity analysis is performed to analyse the impact of changes in floor space on the system. This innovative system is suitable for small-scale IES and serves as an efficient solution for urban energy systems.

Energy efficiency analysis and optimization of a pressurized oxy-fuel circulating fluidized bed combustion system

The commercial application of oxy-fuel combustion technology is limited by energy deduction which is caused by addition of air separation unit (ASU) and carbon dioxide compression and purification unit (CPU). Pressurized circulating fluidized bed (CFB) oxy-fuel combustion technology is one option to improve the net electric generation efficiency. In this research, a series of simulations and optimizations were carried out to analyze the energy efficiency of a pressurized oxy-fuel combustion system. The boiler structure and heat exchange surface arrangement under different pressure were calculated. The cross-sectional area of the furnace and tail flue were both reduced up to 10 % of the original size and the floor space of the boiler was considered to be the lowest at 1.1 MPa. The energy efficiency and exergy analysis were used to explore the influence of pressure on the net efficiency and the optimization potential of system. The net electric generation efficiency reached a maximum value of 24.16 % at 1.1 MPa, which is 5.4 % higher than that at atmospheric pressure. Finally, four parameters, i.e. preheat temperature, oxygen concentration, ASU outlet oxygen purity and CPU compressor outlet pressure, were optimized to improve the system net efficiency to 26.67 %, 29.04 %, 25.87 % and 24.36 %, respectively.

Optimal layout planning for human robot collaborative assembly systems and visualization through immersive technologies

The deployment of Industry 4.0 emerging technologies such as Augmented reality (AR), Virtual reality (VR), and collaborative Robots enhances flexibility and precision in the manufacturing systems. A flexible, and collaborative manufacturing system with robots and human integrates the prominent attributes of customized automation and fortify the safety of the human workforce. The proposed work involves the approach of AR-assisted assembly layout configurations for the Human-Robot Collaboration (HRC) production system, which is a typical example of the smart manufacturing system. The reconfiguration/configuration of the assembly layout is triggered with respect to the demand of new variants into the market and the upgradation of new technologies in the existing system. A multi-objective algorithm is proposed to maximize the production outlet with effective utilization of floor space, minimum idle time and optimum resource allocation. The selected work is branched into three phases: To begin with, the approach of task allocation is constructed to identify the suitable resources (human, robot) for the appropriate assembly tasks in the HRC system. The outcomes such as resource allocation, number of resources, and footprint of resources are considered as input to the optimization model. Further, modified particle swarm optimization (MPSO) is deployed to generate a feasible assembly layout for the HRC manufacturing system. Additionally, the breath-first approach has been utilized to generate the optimal aisle as a conveyor in the layout. Notably, the comparisons studies have been carried out in this work, which facilitates to explore the robustness of proposed modified PSO algorithms for the selected applications. Subsequently, the virtual and AR tool is deployed for the layout planer to explore and validate the obtained layout from the PSO model in both the virtual and physical environment of the industrial workspace. Finally, an industrial case study of rotary gear pump assembly system is adopted for the implementation of the proposed framework.