The Development of Costing Systems： A Historical Perspective

The paper studies the historical development of costing systems. The changes of costing systems are proposed to be caused by the changes in product market, production technology and demand for control. The result of this research provides historical evidence to support the proposition.

Optimized scheduling of integrated energy systems for low carbon economy considering carbon transaction costs

With the introduction of the“dual carbon”goal and the continuous promotion of low-carbon development,the integrated energy system(IES)has gradually become an effective way to save energy and reduce emissions.This study proposes a low-carbon economic optimization scheduling model for an IES that considers carbon trading costs.With the goal of minimizing the total operating cost of the IES and considering the transferable and curtailable characteristics of the electric and thermal flexible loads,an optimal scheduling model of the IES that considers the cost of carbon trading and flexible loads on the user side was established.The role of flexible loads in improving the economy of an energy system was investigated using examples,and the rationality and effectiveness of the study were verified through a comparative analysis of different scenarios.The results showed that the total cost of the system in different scenarios was reduced by 18.04%,9.1%,3.35%,and 7.03%,respectively,whereas the total carbon emissions of the system were reduced by 65.28%,20.63%,3.85%,and 18.03%,respectively,when the carbon trading cost and demand-side flexible electric and thermal load responses were considered simultaneously.Flexible electrical and thermal loads did not have the same impact on the system performance.In the analyzed case,the total cost and carbon emissions of the system when only the flexible electrical load response was considered were lower than those when only the flexible thermal load response was taken into account.Photovoltaics have an excess of carbon trading credits and can profit from selling them,whereas other devices have an excess of carbon trading and need to buy carbon credits.

Managerial perspectives of scaling up robotic-assisted surgery in healthcare systems:A systematic literature review

Objectives Robotic-assisted surgery(RAS)is a minimally invasive technique practiced in multiple specialties.Standard training is essential for the acquisition of RAS skills.The cost of RAS is considered to be high,which makes it a burden for institutes and unaffordable for patients.This systematic literature review(SLR)focused on the various RAS training methods applied in different surgical specialties,as well as the cost elements of RAS,and was to summarize the opportunities and challenges associated with scaling up RAS.Methods An SLR was carried out based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses reporting guidelines.The PubMed,EBSCO,and Scopus databases were searched for reports from January 2018 through January 2024.Full-text reviews and research articles in the English language from Asia-Pacific countries were included.Articles that outlined training and costs associated with RAS were chosen.Results The most common training system is the da Vinci system.The simulation technique,which includes dry-lab,wet-lab,and virtual reality training,was found to be a common and important practice.The cost of RAS encompasses the installation and maintenance costs of the robotic system,the operation theatre rent,personnel cost,surgical instrument and material cost,and other miscellaneous charges.The synthesis of SLR revealed the challenges and opportunities regarding RAS training and cost.Conclusions The results of this SLR will help stakeholders such as decision-makers,influencers,and end users of RAS to understand the significance of training and cost in scaling up RAS from a managerial perspective.For any healthcare innovation to reach a vast population,cost-effectiveness and standard training are crucial.

Surgical treatment of liver cancer and pancreatic cancer under the China Healthcare Security Diagnosis Related Groups payment system

BACKGROUND Data from the World Health Organization’s International Agency for Research on Cancer reported that China had the highest prevalence of cancer and cancer deaths in 2022.Liver and pancreatic cancers accounted for the highest number of new cases.Real-world data(RWD)is now widely preferred to traditional clinical trials in various fields of medicine and healthcare,as the traditional research approach often involves highly selected populations and interventions and controls that are strictly regulated.Additionally,research results from the RWD match global reality better than those from traditional clinical trials.AIM To analyze the cost disparity between surgical treatments for liver and pancreatic cancer under various factors.METHODS This study analyzed RWD 1137 cases within the HB1 group(patients who underwent pancreatectomy,hepatectomy,and/or shunt surgery)in 2023.It distinguished different expenditure categories,including medical,nursing,technical,management,drug,and consumable costs.Additionally,it assessed the contribution of each expenditure category to total hospital costs and performed cross-group comparisons using the non-parametric Kruskal–Wallis test.This study used the Steel–Dwass test for post-hoc multiple comparisons and the Spearman correlation coefficient to examine the relationships between variables.RESULTS The study found that in HB11 and HB13,the total hospitalization costs were significantly higher for pancreaticoduodenectomy than for pancreatectomy and hepatectomy.Although no significant difference was observed in the length of hospital stay between patients who underwent pancreaticoduodenectomy and pancreatectomy,both were significantly longer than those who underwent liver resection.In HB15,no significant difference was observed in the total cost of hospitalization between pancreaticoduodenectomy and pancreatectomy;however,both were significantly higher than those in hepatectomy.Additionally,the length of hospital stay was significantly longer for patients who underwent pancreaticoduodenectomy than for those who underwent pancreatectomy or liver resection.CONCLUSION China Healthcare Security Diagnosis Related Groups payment system positively impacts liver and pancreatic cancer surgeries by improving medical quality and controlling costs.Further research could refine this grouping system and ensure continuous effectiveness and sustainability.

Cost analysis of radical resection of malignant breast tumors under the China Healthcare Security Diagnosis Related Groups payment system

BACKGROUND Breast cancer is one of the most common malignant tumors in women worldwide and poses a severe threat to their health.Therefore,this study examined patients who underwent breast cancer surgery,analyzed hospitalization costs and structure,and explored the impact of China Healthcare Security Diagnosis Related Groups(CHS-DRG)management on patient costs.It aimed to provide medical institutions with ways to reduce costs,optimize cost structures,reduce patient burden,and improve service efficiency.AIM To study the CHS-DRG payment system’s impact on breast cancer surgery costs.METHODS Using the CHS-DRG(version 1.1)grouping criteria,4073 patients,who underwent the radical resection of breast malignant tumors from January to December 2023,were included in the JA29 group;1028 patients were part of the CHS-DRG payment system,unlike the rest.Through an independent sample t-test,the length of hospital stay as well as total hospitalization,medicine and consumables,medical,nursing,medical technology,and management expenses were compared.Pearson’s correlation coefficient was used to test the cost correlation.RESULTS In terms of hospitalization expenses,patients in the CHS-DRG payment group had lower medical,nursing,and management expenses than those in the diagnosis-related group(DRG)non-payment group.For patients in the DRG payment group,the factors affecting the total hospitalization cost,in descending order of relevance,were medicine and consumable costs,consumable costs,medicine costs,medical costs,medical technology costs,management costs,nursing costs,and length of hospital stay.For patients in the DRG nonpayment group,the factors affecting the total hospitalization expenses in descending order of relevance were medicines and consumable expenses,consumable expenses,medical technology expenses,the cost of medicines,medical expenses,nursing expenses,length of hospital stay,and management expenses.CONCLUSION The CHS-DRG system can help control and reduce unnecessary medical expenses by controlling medicine costs,medical consumable costs,and the length of hospital stay while ensuring medical safety.

Exploring the impact of high density planting system and deficit irrigation in cotton(Gossypium hirsutum L.):a comprehensive review

Lessons learned from past experiences push for an alternate way of crop production.In India,adopting high density planting system(HDPS)to boost cotton yield is becoming a growing trend.HDPS has recently been considered a replacement for the current Indian production system.It is also suitable for mechanical harvesting,which reducing labour costs,increasing input use efficiency,timely harvesting timely,maintaining cotton quality,and offering the potential to increase productivity and profitability.This technology has become widespread in globally cotton growing regions.Water management is critical for the success of high density cotton planting.Due to the problem of freshwater availability,more crops should be produced per drop of water.In the high-density planting system,optimum water application is essential to control excessive vegetative growth and improve the translocation of photoassimilates to reproductive organs.Deficit irrigation is a tool to save water without compromising yield.At the same time,it consumes less water than the normal evapotranspiration of crops.This review comprehensively documents the importance of growing cotton under a high-density planting system with deficit irrigation.Based on the current research and combined with cotton production reality,this review discusses the application and future development of deficit irrigation,which may provide theoretical guidance for the sustainable advancement of cotton planting systems.

SmartMicro Grid Energy System Management Based on Optimum Running Cost for Rural Communities in Rwanda

The governmental electric utility and the private sector are joining hands to meet the target of electrifying all households by 2024.However,the aforementioned goal is challenged by households that are scattered in remote areas.So far,Solar Home Systems(SHS)have mostly been applied to increase electricity access in rural areas.SHSs have continuous constraints to meet electricity demands and cannot run income-generating activities.The current research presents the feasibility study of electrifying Remera village with the smart microgrid as a case study.The renewable energy resources available in Remera are the key sources of electricity in that village.The generation capacity is estimated based on the load profile.The microgrid configurations are simulated with HOMER,and the genetic algorithm is used to analyze the optimum cost.By analyzing the impact of operation and maintenance costs,the results show that the absence of subsidies increases the levelized cost of electricity(COE)five times greater than the electricity price from the public utility.The microgrid made up of PV,diesel generator,and batteries proved to be the most viable solution and ensured continuous power supply to customers.By considering the subsidies,COE reaches 0.186$/kWh,a competitive price with electricity from public utilities in Rwanda.

Reliability-BasedModel for Incomplete Preventive ReplacementMaintenance of Photovoltaic Power Systems

At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under-repair of equipment.Therefore,a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed.First,a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment,and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle.Then,based on the reliability as a constraint,the average maintenance cost and availability of the equipment are considered,and the non-periodic incomplete maintenance model of the PV power generation system is established to obtain the optimal number of repairs,each maintenance cycle and the replacement cycle of the PV power generation system components.Next,the inverter of a PV power plant is used as a research object.The model in this paper is compared and analyzed with the equal cycle maintenance model without considering reliability and the maintenance model without considering the equipment replacement threshold,Through model comparison,when the optimal maintenance strategy is(0.80,4),the average maintenance cost of this paper’s model are decreased by 20.3%and 5.54%and the availability is increased by 0.2395% and 0.0337%,respectively,compared with the equal-cycle maintenance model without considering the reliability constraint and the maintenance model without considering the equipment replacement threshold.Therefore,this maintenance model can ensure the high reliability of PV plant operation while increasing the equipment availability to improve the system economy.

Optimizing a Transportation System Using Metaheuristics Approaches (EGD/GA/ACO): A Forest Vehicle Routing Case Study

The large-scale optimization problem requires some optimization techniques, and the Metaheuristics approach is highly useful for solving difficult optimization problems in practice. The purpose of the research is to optimize the transportation system with the help of this approach. We selected forest vehicle routing data as the case study to minimize the total cost and the distance of the forest transportation system. Matlab software helps us find the best solution for this case by applying three algorithms of Metaheuristics: Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Extended Great Deluge (EGD). The results show that GA, compared to ACO and EGD, provides the best solution for the cost and the length of our case study. EGD is the second preferred approach, and ACO offers the last solution.

Decoding the Einstein-Type Formula for Reducing Energy Conversion to Carbon Emissions in Renewables Systems

This article explores the role of distributed energy resources such as efficient solar cells that drive carbon neutrality within the solar energy. For example, the perovskite solar cells offer high efficiency and potential for low-cost production. A novel theoretical model is discovered in distributed energy resources for power emissions and cost. The smart carbon neutrality approaches are analyzed in both theory and experiments. The advantages, current challenges, and future prospects of the related solutions are discussed methodically. By addressing stability and scalability issues, these approaches can contribute significantly to reducing carbon emissions and promoting sustainable energy solutions.

Research on workflow meta model supporting activity based costing

Activity based costing (ABC) is a method which can solve many limitations of the traditional cost systems in manufacturing management. In this paper, we investigate how to integrate ABC with workflow technology, and build a workflow meta model supporting ABC. Firstly, the concept and concept model of activity based costing (ABC) are introduced. Next, the meta model of P -PROCE (Process, Product, Resource, Organization, and Cost & Evaluation) is presented. Then the cost meta model is defined by adding ABC to P -PROCE model. Object constraint language (OCL) is used to express meta model and constraints. Finally, we show an enterprise modeling and simulation tool based on the workflow meta model. We can systematically construct an enterprise model and easily and efficiently conduct simulation. Moreover it enables us to analyze and evaluate business processes and its costs.

Efficacy-cost analysis of endoscopic mucosal resection and cold snare polypectomy:A propensity score matching analysis

BACKGROUND Although substantial evidence supports the advantages of cold snare polypectomy(CSP)in terms of polypectomy efficacy and reduced postoperative adverse events,few studies have examined the cost differences between CSP and traditional endoscopic mucosal resection(EMR)for the treatment of intestinal polyps.AIM To compare the efficacy-cost of EMR and CSP in the treatment of intestinal polyps.METHODS A total of 100 patients with intestinal polyps were included in the retrospective data of our hospital from April 2022 to May 2023.According to the treatment methods,they were divided into EMR(n=46)group and CSP(n=54)group.The baseline data of the two groups were balanced by 1:1 propensity score matching(PSM),and the cost-effectiveness analysis was performed on the two groups after matching.The recurrence rate of the two groups of patients was followed up for 1 year,and they were divided into recurrence group and non-recurrence group according to whether they recurred.Multivariate logistic regression analysis was used to screen out the influencing factors affecting the recurrence of intestinal polyps after endoscopic resection.RESULTS Significant disparities were observed in the number of polyps and smoking background between the two groups before PSM(P<0.05).Following PSM,the number of polyps and smoking history were well balanced between the EMR and CSP groups.The direct cost incurred by the CSP group was markedly higher than that incurred by the EMR group.Concurrently,the cost-effectiveness ratio in the CSP group was substantially reduced when juxtaposed with that in the EMR group(P<0.05).Upon completion of the 1-year follow-up,the rate of recurrence after endoscopic intestinal polypectomy was 38.00%.Multivariate methods revealed that age≥60 years,male sex,number of polyps≥3,and pathological type of adenoma were risk factors for recurrence after endoscopic intestinal polypectomy(all P<0.05).CONCLUSION CSP was more cost-effective for the treatment of intestinal polyps.An age≥60 years,male sex,having a number of polyps≥3,and pathological type of adenoma are independent influencing factors for recurrence.

Decentralized robust guaranteed cost control for a class of interconnected singular large-scale systems with time-delay and parameter uncertainty

The decentralized robust guaranteed cost control problem is studied for a class of interconnected singular large-scale systems with time-delay and norm-bounded time-invariant parameter uncertainty under a given quadratic cost performance function. The problem that is addressed in this study is to design a decentralized robust guaranteed cost state feedback controller such that the closed-loop system is not only regular, impulse-free and stable, but also guarantees an adequate level of performance for all admissible uncertainties. A sufficient condition for the existence of the decentralized robust guaranteed cost state feedback controllers is proposed in terms of a linear matrix inequality （LMI） via LMI approach. When this condition is feasible, the desired state feedback decentralized robust guaranteed cost controller gain matrices can be obtained. Finally, an illustrative example is provided to demonstrate the effectiveness of the proposed approach.

IFC implementation in lifecycle costing

Life Cycle Costing (LCC) is always a major concern in the Architecture, Engineering and Construction (AEC) industry. This paper presents the implementation of Building Information Modeling (BIM) technology in the development of a lifecycle cost-estimating tool. The IFC (Industry Foundation Classes) model as an interoperable building information model has been adopted as the central data repository to deliver the integrated information of building designs from CAD design systems into the lifecycle-costing database. In this paper, the conceptions and relevant factors, which could affect the LCC estimation, have been introduced. The problems of current LCC applications have been identified as the lack of LCC data and the complexity of LCC exercises. The software application of IFC models and relevant auxiliary are depicted as a solution of the problem identified. The lifecycle costing tool is a part of the nD Modeling tool and as such is based on its integrated interface prototype toolkit and is able to holistically present an IFC model into a 3D virtual reality view, a tree-view and a list of element properties. The functions and some technical points are also detailed in the paper. Through the research, it demonstrates the potential and possibility of implementing BIM methods and techniques, particularly IFCs to enhance the computer applications in the processes of building construction and facility management.

Guaranteed Cost Consensus for High-dimensional Multi-agent Systems With Time-varying Delays

Guaranteed cost consensus analysis and design problems for high-dimensional multi-agent systems with time varying delays are investigated. The idea of guaranteed cost con trol is introduced into consensus problems for high-dimensiona multi-agent systems with time-varying delays, where a cos function is defined based on state errors among neighboring agents and control inputs of all the agents. By the state space decomposition approach and the linear matrix inequality(LMI)sufficient conditions for guaranteed cost consensus and consensu alization are given. Moreover, a guaranteed cost upper bound o the cost function is determined. It should be mentioned that these LMI criteria are dependent on the change rate of time delays and the maximum time delay, the guaranteed cost upper bound is only dependent on the maximum time delay but independen of the Laplacian matrix. Finally, numerical simulations are given to demonstrate theoretical results.

A system-wide approach to minimize the operational cost of bench production in open-cast mining operations

The production cycle of open-cast coal mines generally in eludes drilling, blasting, loading, hauling and coal preparation activities. Individual optimization of these activities does not mean that the whole system is optimized. This paper proposes a cost model considering all activities in mining cycle and system-wide approach to minimize the total mining cost of bench production. Since the fragmentation size and blast-hole diameter are linked to all activities of mining system, they are considered as decision variables in the problem form ul at io n. The operatio n costs are then minimized by using the evolutionary algorithm. Moreover, the impact of the change in the explosive price, and the hourly unit cost of equipment on total mining cost is quantified by sensitivity analysis. A case study is implemented to demonstrate the developed model.

Fluid-based Slotting Optimization for Automated Order Picking System with Multiple Dispenser Types

Slotting strategy heavily influences the throughput and operational cost of automated order picking system with multiple dispenser types, which is called the complex automated order picking system （CAOPS）. Existing research either focuses on one aspect of the slotting optimization problem or only considers one part of CAOPS, such as the Low-volume Dispensers, to develop corresponding slotting strategies. In order to provide a comprehensive and systemic approach, a fluid-based slotting strategy is proposed in this paper. The configuration of CAOPS is presented with specific reference to its fast-picking and restocking subsystems. Based on extended fluid model, a nonlinear mathematical programming model is developed to determine the optimal volume allotted to each stock keeping unit （SKU） in a certain mode by minimize the restocking cost of that mode. Conclusion from the allocation model is specified for the storage modules of high-volume dispensers and low-volume dispensers. Optimal allocation of storage resources in the fast-picking area of CAOPS is then discussed with the aim of identifying the optimal space of each picking mode. The SKU assignment problem referring to the total restocking cost of CAOPS is analyzed and a greedy heuristic with low time complexity is developed according to the characteristics of CAOPS. Real life application from the tobacco industry is presented in order to exemplify the proposed slotting strategy and assess the effectiveness of the developed methodology. Entry-item-quantity （EIQ） based experiential solutions and proposed-model-based near-optimal solutions are compared. The comparison results show that the proposed strategy generates a savings of over 18% referring to the total restocking cost over one-year period. The strategy proposed in this paper, which can handle the multiple dispenser types, provides a practical quantitative slotting method for CAOPS and can help picking-system-designers make slotting decisions efficiently and effectively.

Observer-based Adaptive Optimal Control for Unknown Singularly Perturbed Nonlinear Systems With Input Constraints

This paper introduces an observer-based adaptive optimal control method for unknown singularly perturbed nonlinear systems with input constraints. First, a multi-Time scales dynamic neural network MTSDNN observer with a novel updating law derived from a properly designed Lyapunov function is proposed to estimate the system states. Then, an adaptive learning rule driven by the critic NN weight error is presented for the critic NN, which is used to approximate the optimal cost function. Finally, the optimal control action is calculated by online solving the Hamilton-Jacobi-Bellman HJB equation associated with the MTSDNN observer and critic NN. The stability of the overall closed-loop system consisting of the MTSDNN observer, the critic NN and the optimal control action is proved. The proposed observer-based optimal control approach has an essential advantage that the system dynamics are not needed for implementation, and only the measured input U+002F output data is needed. Moreover, the proposed optimal control design takes the input constraints into consideration and thus can overcome the restriction of actuator saturation. Simulation results are presented to confirm the validity of the investigated approach. © 2014 Chinese Association of Automation.

Condition-based maintenance optimization for continuously monitored degrading systems under imperfect maintenance actions

Condition-based maintenance(CBM) is receiving increasing attention in various engineering systems because of its effectiveness. This paper formulates a new CBM optimization problem for continuously monitored degrading systems considering imperfect maintenance actions. In terms of maintenance actions,in practice, they scarcely restore the system to an as-good-as new state due to residual damage. According to up-to-data researches, imperfect maintenance actions are likely to speed up the degradation process. Regarding the developed CBM optimization strategy, it can balance the maintenance cost and the availability by the searching the optimal preventive maintenance threshold.The maximum number of maintenance is also considered, which is regarded as an availability constraint in the CBM optimization problem. A numerical example is introduced, and experimental results can demonstrate the novelty, feasibility and flexibility of the proposed CBM optimization strategy.