Total Cost Model Research Articles

Robust Design Based on Cost-Quality Model in Micro-Manufacturing

This paper proposes a novel total cost model for the micro‐products' entire life cycle that takes into account the uncertainty of the model parameters. The total cost includes pre-sale manufacturing and post-sale warranty costs. Additionally, different marketing strategies are also given based on the weight of internal and external costs. Furthermore, limited data and unknown effects in experiments may cause large errors in parameter estimates. This could prevent the achievement of reliable designs. To address this, robust optimization and interval estimation are used. This approach reduces the impact of uncertainty on parameter estimates. It ensures optimality and robustness in micro-manufacturing parameters. Example analysis and numerical simulation results show that the proposed method assists companies in selecting the optimal manufacturing parameter level that aligns with their marketing strategies. Besides, considering uncertainty factors can ensure that the optimization results remain guaranteed, even under the worst-case scenarios.

Production System for Delayed Deterioration Inventories with Two-Level Production Rate, Stock-Dependent Demand Rate and Linear Holding Cost Under Trade Credit Policy

This paper introduces an optimized total variable cost model for a production inventory system dealing with delayed deteriorating items. The model incorporates a two-level production rate and a stock-dependent demand rate, all operating under a trade credit policy. The demand rate remains constant during the inventory build-up period, but post-production, before deterioration, it varies based on product availability and nature. The inventory depletes to zero in the model’s final stage due to the combined impact of constant demand and deterioration rates. To characterize the optimality of the analytical results, the paper utilizes theorems and lemmas. The model’s dynamics are described by differential equations, which are solved using MATLAB. A numerical experiment is conducted to demonstrate the practicality of the developed models. Additionally, a sensitivity analysis is performed to illustrate how changes in selected system parameters affect the total variable costs determined in the numerical example. The paper concludes with suggestions and recommendations aimed at reducing the total variable cost. Ultimately, it is demonstrated that the developed model surpasses the one presented in the working paper. The proposed model could be used in inventory management and control of items that exhibit delayed in deterioration to minimises the total variable cost when sudden distraction of production process occurred as revealed by the the result presented.

The Discussion on the Impact of the COVID-19 Epidemic on the Macro-economy and the Establishment of the Work and Production Resumption Model

In order to explore the impact of the COVID-19 epidemic on the macro-economy, this paper established the IS-LM model and the AD-AS model, made corresponding adjustments and calculations to the models, analyzed the impact of the epidemic on aggregate demand and aggregate supply respectively, and put forward policy suggestions according to the actual situation by using the models. And in order to help the government better decide the best timing to return to work and production in different industries, this article utilized the total cost model in epidemic control to build a work resumption coefficient evaluation model of different industries, getting the coefficients of the high-density population industry, the industry whose work resumption can be carried out online, the industry of fewer average interactions, highly mechanized industry and special industries, respectively. And we formulated the standard of work resumption based on the work resumption coefficient under the condition of controlling the total cost to be minimized. After getting the work resumption coefficients of different industries and corresponding resumption standard, the government will be easier to balance the cost of the shutdown and the risk of resuming work and production under the epidemic.

A Fuzzy Dynamic Model for Total Quality Cost

A Fuzzy Dynamic Model for Total Quality Cost

Assembly-based flood repair cost and time models for industrial buildings in Turkey

Flooding is one of the most frequent hazard events significantly affecting the industry in Turkey, leading to severe economic losses and business disruptions. To predict the direct flood losses and business downtimes on the industry, this study proposes probabilistic cost and time models of repairing direct physical flood damage to industrial buildings in Turkey. Using field notes and literature reviews, a typical industrial building was first disassembled into a list of building components vulnerable to flooding. With a focus on façade and interior building components, the flood damage potential of each component was assessed at different flood depths and velocities. Damage state relationships were established for the building components to connect their damage levels under flood actions to their individual repair work. Using the assembly-based approach, costs and times of repairing each flood-damaged component and their associated variabilities were assembled in a probabilistic approach to develop total flood repair cost and time models. The results show that typical repair costs and times for facilities subjected to significant flood depths and velocities might reach substantial levels, up to 28% of building replacement costs and 165 working days on average. The proposed models systematically incorporate existing important uncertainties, therefore, provide reliable estimates.

An improved method of parameter and tolerance concurrent design considering the mass loss

Quality and cost are the core problems in the manufacturing industry. Given the problems of many tests and high manufacturing costs caused by parameter design before tolerance design in the traditional Taguchi product optimization design, based on the idea of robust design and concurrent design, this paper establishes an improved method of parameter and tolerance concurrent design considering quality loss, which effectively saves the manufacturing cost while ensuring the product quality. Firstly, the central composite bounded experimental design (CCI) is carried out, and then the response surface model is established from the data; Then the total cost model composed of the quality loss model and tolerance cost model is established. Finally, the improved genetic algorithm (NSGA - II) is used to find the optimal parameter combination and tolerance at the same time. Through the example analysis of a compliant precision positioning platform, the results show that the parameter combination and tolerance obtained by concurrent design considering the parameters and tolerance of mass loss not only improve the robustness of products but also reduce the manufacturing cost.

Feature Identification, Solution Disassembly and Cost Comparison of Intelligent Driving under Different Technical Routes

Technical route decision making of intelligent driving has always been the focus of attention of automotive enterprises and even the industry. Firstly, this study combs the main technical routes of intelligent driving at different levels from three dimensions: development strategy, intelligence allocation and sensor combination. Then, the methodology of technical component combination is designed to disassemble different technical routes into corresponding technical component combinations. Finally, an improved evaluation model of total cost of ownership of intelligent driving is developed and the total cost of ownership of intelligent driving system under different technical routes is compared. For the development strategy, even if the function superposition can follow some research and development achievements of low-level intelligent driving, scenario-driven is still the option with lower cost and better sustainability. For intelligence allocation, collaborative intelligence can effectively reduce the cost of the vehicle compared with single-vehicle intelligence by up to 46%, but the cost reduction depends on the original on-board hardware. For sensor combination, the multi-source fusion always has the cost advantage compared with vision-only, but the advantage is more obvious in the medium-level and high-level stage of single-vehicle intelligence.

Concurrent optimization of parameter and tolerance design based on the two-stage Bayesian sampling method

ABSTRACT Researchers usually expect to reduce costs while improving product robustness in product quality design. The concurrent optimization of parameter and tolerance design assumes that the output response follows a normal distribution. However, non-normal responses are also common in product quality design. As for the concurrent optimization of parameter and tolerance design with a non-normal response, a novel total cost function based on the two-stage Bayesian sampling method is proposed in this paper. First, the hierarchical Bayesian model constructs the functional relationship between output response, input factors, and tolerance variables. Secondly, a two-stage Bayesian sampling method is used to obtain the simulated values of the output responses. The simulated response values are used to build the rejection cost and quality loss functions. Then, the genetic algorithm is used to optimize the constructed total cost model, including the tolerance cost, rejection cost, and quality loss. Finally, the effectiveness of the proposed method is demonstrated by two examples. The research results show that the proposed method in this paper can effectively improve product quality and reduce manufacturing costs when considering the uncertainty of model parameters and the variation of the output response.

IT-architecture management for small businesses based on total cost of ownership models

The article is dedicated to the tasks of IT architecture management according to the specifics of small and medium-sized businesses. The article comprehensively considers the object model of the IT service as the main component of the IT-architecture management. In the article, the authors propose to present an object model on different layers, which allows to consider the elements of the IT-architecture from different points of view. The service object model has logical and physical layers, where the physical layer consists of the hardware and some software components and the logical ones are the systems and subsystem as software products, and the service itself as a business value. The authors describes the main aspects of using the object model to identify elements of the IT-architecture. This shows that subsystems and the physical layer allows to apply the model of total cost of ownership. The study also identifies key steps in applying the total cost of ownership model to enterprise IT-architecture management; the most difficult stages for the development of small and medium-sized businesses are noted. As a result of the study, the authors developed an approach that allows you to determine the cost of individual IT-systems and their corresponding elements of the sharing infrastructure, taking into account the structuring of costs based on the total cost of ownership model. The authors assume that this approach will be most useful for small and medium-sized businesses. The authors propose to use approaches based on the use of an IT-service object model and a total cost of ownership model for solving IT-architecture management problems. The use of an object model allows to identify business value enterprise IT architecture, its components and their infrastructure elements. Applying the total cost of ownership model enables to use cost management the IT architecture.

Total Financial Burden of Increasing Urology Residency Applications on Applicants and Programs

INTRODUCTION: The annual volume of urology residency applications continues to rise. Previous studies have assessed applicants’ expenses without accounting for the time cost borne by program faculty. We modeled the total financial burden incurred by applicants during submission and program faculty during review. METHODS: For applicant costs, we calculated application submission fees and assessed the applicant pool by year. For program costs, we assumed applications receive a 10-minute screening review by 1 reviewer, and a subset of applications receives a 30-minute full review by 2 reviewers. We extrapolated per-program salary costs to 143 US programs. RESULTS: Average per-applicant applications increased 57% during 2013 to 2022, from 53 to 83 (Figure). Corresponding submission fees rose 67%, from $1,157 to $1,937 per applicant. However, average interviews given by programs and taken by applicants remained relatively static (Figure). In the total cost model for 2017 to 2022, total applicant submission costs rose from $0.7M to $1.2M. Average applications received per program increased 42% (236 to 349 applications), increasing faculty review time by 27% (113 to 144 hours). Extrapolated to all US programs, total program costs rose from $1.6M to $2M. Thus, total costs increased from $2.3M to $3.2M, corresponding to a rise in per-vacancy costs of 22%, more than twice the rate of inflation in the same period. CONCLUSION: Increasing application volumes have resulted in substantially higher total financial costs of the submission and review process. Efforts to control the time cost of faculty review may lead to reliance on suboptimal screening strategies.Figure

Multi-objective optimization of gas turbine combined cycle system considering environmental damage cost of pollution emissions

Currently, most of the performance analysis and optimization design of the gas turbine combined cycle (GTCC) units ignore the economic loss to the environment caused by the pollutant emissions. In this paper, based on the structure theory of thermoeconomics, an environmental thermoeconomic cost model is established. And then an annual total cost model is established, which can reflect the real economic performance. Based on the comprehensive analysis of the energy, economy and environment, with the objectives of the higher exergy efficiency, less annual total cost and lower specific CO2 emission rate, a multi-objective optimization study of the GTCC unit is conducted using the genetic algorithm (GA) in this paper. Pareto frontiers for the multi-objective optimization has been obtained with GA, and in turn a design plan can be selected from the Pareto frontier according to the preference. The multi-objective optimization results show that the optimized system can greatly increase the system environmental thermoeconomic performance. Moreover, the effects of main variables on the economic performance index of the optimized system are investigated. The results show that the natural gas price has the greater impact on the economic performance index compared with the pollutants environmental damage cost and the non-energy cost.

Impact of Social Needs in Electronic Health Records and Claims on Health Care Utilization and Costs Risk-Adjustment Models Within Medicaid Population.

Patients enrolled in Medicaid have significantly higher social needs (SNs) than others. Using claims and electronic health records (EHRs) data, managed care organizations (MCOs) could systemically identify high-risk patients with SNs and develop population health management interventions. Impact of SNs on models predicting health care utilization and costs was assessed. This retrospective study included claims and EHRs data on 39,267 patients younger than age 65 years who were continuously enrolled during 2018-2019 in a Medicaid-managed care plan. SN marker was developed suggesting presence of International Classification of Diseases, 10th revision codes in any of the 5 SN domains. Impact of SN marker was compared across demographic and 2 diagnosis-based (ie, Charlson and Adjusted Clinical Groups risk score) prediction models of emergency department (ED) visit and hospitalizations, and total, medical, and pharmacy costs. After combining data sources, prevalence of documented SN marker increased from 11% and 13% to 18% of the study population across claims, EHRs, and both combined, respectively. SN marker improved predictions of demographic models for all utilization and total costs outcomes (area under the curve [AUC] of ED model increased from 0.57 to 0.61 and R2 of total cost model increased from 10.9 to 12.2). In both diagnosis-based models, adding SN marker marginally improved outcomes prediction (AUC of ED model increased from 0.65 to 0.66). This study demonstrated feasibility of using claims and EHRs data to systematically capture SNs and incorporate in prediction models that could enable MCOs and policy makers to adjust and develop effective population health interventions.

PD30-03 TOTAL FINANCIAL BURDEN OF INCREASING UROLOGY RESIDENCY APPLICATIONS ON APPLICANTS AND PROGRAMS

You have accessJournal of UrologyCME1 May 2022PD30-03 TOTAL FINANCIAL BURDEN OF INCREASING UROLOGY RESIDENCY APPLICATIONS ON APPLICANTS AND PROGRAMS Kevin Koo, Elizabeth Bearrick, Bridget Findlay, and Candace Granberg Kevin KooKevin Koo More articles by this author , Elizabeth BearrickElizabeth Bearrick More articles by this author , Bridget FindlayBridget Findlay More articles by this author , and Candace GranbergCandace Granberg More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002578.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The annual volume of urology residency applications continues to rise. Previous studies have assessed applicants’ expenses without accounting for the time cost borne by program faculty. We aimed to assess the total financial burden of continued increases in application volumes by modeling costs incurred by both applicants during submission and program faculty during application review. METHODS: Public data on urology residency applicants were obtained from the Electronic Residency Application Service (ERAS) and American Urological Association. To model financial costs for applicants, we calculated ERAS submission fees and assessed the total applicant pool by year. For program costs, we assumed that every submitted application receives a 10-minute screening review by 1 reviewer, and a subset of applications equal to twice the average number of interviews given by programs receives a 30-minute full review by 2 reviewers. We calculated the average hourly wage of academic urologists based on published salary data and extrapolated per-program costs to 143 US programs. RESULTS: From 2013 to 2022, the average number of applications submitted per applicant increased 57% (Figure). The corresponding ERAS application fees rose 67%, from $1157 to $1937 per applicant. However, average numbers of interviews given by programs and taken by applicants remained relatively static (Figure). In the total cost model for 2017-2022, total applicant submission costs rose from $0.7M to $1.2M (Table). The average number of applications received per program increased 42%, from 236 to 349 applications, leading to a 27% increase in program faculty time to review, from 113 to 144 hours. Extrapolated to all US programs, total program costs rose from $1.6M to $2M. Thus, total costs of application submission and review increased from $2.3M to $3.2M, corresponding to a rise in per-vacancy costs of 22%, more than twice the rate of inflation in the same period. CONCLUSIONS: Increasing urology residency application volumes have resulted in substantially higher total financial costs of the submission and review process. Efforts to control the time cost of faculty review in the setting of persistent increases in application volume may lead to reliance on suboptimal screening strategies. Source of Funding: None © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e510 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Kevin Koo More articles by this author Elizabeth Bearrick More articles by this author Bridget Findlay More articles by this author Candace Granberg More articles by this author Expand All Advertisement PDF DownloadLoading ...

Location optimization of electric vehicle charging stations: Based on cost model and genetic algorithm

Nowadays, the development of new energy science has gradually entered a good situation, and accordingly, electric vehicles have been recognized by people all over the world and rapidly popularized in various countries. However, the rapid growth of electric vehicles has caused a series of problems, such as insufficient number of charging stations, uneven distribution, and high cost, which are becoming increasingly serious. In order to solve the above problems, this paper takes Ireland as an example for research. Based on the collection of relevant information, this paper first tries to build a social total cost model, and calculates the total operating cost of charging stations under various distribution conditions. In this model, the total social cost is subdivided into comprehensive economic cost and environmental cost. Economic costs include construction costs and fees, while environmental costs include electricity consumption and carbon dioxide emissions. Secondly, this paper established a charging station location optimization model based on genetic algorithm, which simplified the Irish territory into a rectangle with a length of 350 km and a width of 200 km, subdivided it into small squares, and adjusted the correlation coefficient to meet the charging demand. This solution solves the minimization problem of operating cost under the constraints of depreciation period of charging station, power consumption per unit distance of charging station and vehicle charging probability. Finally, in order to determine the factors that may have a significant impact on the total cost of charging stations, we conducted sensitivity analysis and found that the total cost is very sensitive to the number of charging stations and the possibility of EV charging per day.

Research on Evaluation of Intelligent Manufacturing Capability and Layout Superiority of Supply Chains by Big Data Analysis

With the rise of cloud computing, big data and Internet of Things technology, intelligent manufacturing is leading the transformation of manufacturing mode and industrial upgrading of manufacturing industry, becoming the commanding point of a new round of global manufacturing competition. Based on the literature review of intelligent manufacturing and intelligent supply chain, a total factor production cost model for intelligent manufacturing and its formal expression are proposed. Based on the analysis of the model, 12 first-level indicators and 29 second-level indicators of production line, workshop/factory, enterprise and enterprise collaboration are proposed to evaluate the intelligent manufacturing capability of supply chain. This article also further studies the layout superiority and spatial agglomeration characteristics of intelligent manufacturing supply chain, providing useful reference and support for enterprises and policy makers in the decision-making.

Nonconvex multicommodity near equilibrium models: Energy markets perspective

In this paper we explore the application of the minimum total opportunity cost (MTOC) model of Fuller and Celebi (2017) to multicommodity market planning models containing binary variables and price sensitive demands, with or without substitution among commodities. We present a greatly simplified derivation of the MTOC approximation of Fuller and Celebi (2017), here called the near equilibrium (NE) model, a mixed integer program with nonlinearities only in the objective function. For some models, the NE solution achieves the MTOC solution exactly, as in an example. We provide a simple example of capacity expansion in gas and electricity markets that are linked through substitution in demand and in the possibility of using gas to produce electricity. In several cases, we compare the NE solution to the social welfare (SW) maximization solution calculated by a sequential optimization algorithm. In one case, the sequential optimization algorithm fails to converge, due to the binary variables. For the other cases, the NE model has smaller producer opportunity costs – in particular, in most cases, smaller make whole payments that bring negative producer profits up to zero – at some sacrifice of social welfare. We suggest that the NE model could be useful to government regulators as a supplementary tool along with SW models, as the NE solution usually reduces subsidies needed for make whole payments, and sometimes benefits consumers compared to the SW solution.

Cluster segmentation algorithm based on the Vicsek with static summoning points

Because of the low convergence efficiency of the typical Vicsek model, a Vicsek with static summoning points (VSSP) algorithm based on the Vicsek model considering static summoning points is proposed. Firstly, the mathematical model of the individual movement total cost on each summoning point is established. Then the individual classification rule is designed according to the initial state of the cluster to obtain the sub-clusters guided by each summoning point. Finally, the summoning factor is introduced to modify the course angle updating formula of the Vicsek model. To verify the effectiveness of the proposed algorithm and study the effect of the cluster summoning factor on the convergence rate, three groups of simulation experiments under different summoning factors are designed in this paper. To verify the superiority of the VSSP algorithm, the performance of the VSSP algorithm is compared with the classic algorithm by designing the algorithm performance comparison verification experiment. The results show that the algorithm proposed in this paper has good convergence and course angle consistency. The summoning factor is the sensitive factor of cluster convergence. This algorithm can provide a reference for efficient cluster segmentation movement.

Why Orthopedic Surgery for Elderly Indicates that the Maryland Total Cost of Care Model should be Universally Adopted

Arthritis is the disease that kills the fewest but cripples the most. With the aging of the population in the United States and the antiquated DRG reimbursement system for hospital surgical intervention, it is inevitable that the Medicare assistant will bankrupt itself prior to the proposed bankruptcy date of 2026 if changes are not made. It may change would be to insist that the system in Maryland for reimbursement to hospitals for essential joint replacement surgery of the elderly be adapted nationwide.

Economic Production Quantity Model for Deteriorating Items with Weibull Deterioration Rate over the Finite Time Horizon

In the present paper we have considered a production supply chain and developed two models for production supply cycle. These models are (i) The optimum total cost model and (ii) The maximum inventory level model. We have assumed constant demand rate for deteriorating inventory and considered three parameter Weibull distributions for deterioration rate with finite time horizon. We have also considered three different level of production in one cycle with shortages allowed. In real world of production and manufacturing market, EPQ models are playing role of an effective tool. The objective of our work is to find optimal production quantity and minimize total cost per cycle. Our work will be useful for the organizations which are going to launch new product in the market or newly established production organizations where at starting organizations are not aware about the production size and changing their production level according to the market demand. These models will help to avoid surplus stock or shortages in business organizations and reduce holding cost; deterioration cost etc. The objective of this paper is to find optimal total cost and optimal production quantity for one cycle. At last numerical example and sensitivity analysis is given to illustrate the result. We have used Mathematica 0.9 to solve equations, calculation and plotting graph.

Multi-Product Economic Inventory Policy with Time Varying Power Demand, Shortages and Complete Backordering

The present article elaborates a multi-product economic inventory model in which multiple items are considered with demand, which depends on time, abides power law, shortages, and complete backordering. The rate of production is greater than the rate of demand for each item. This type of demand pattern is accessible to various kinds of practical problems in the present modern era. In this paper, the production rate is assumed to be directly proportional to the rate of demand. In real situations, demand is always dependent on the price of any product, so it is also assumed that demand is depleted linearly with the price. This paper aims to fulfill the requirement of products and maximize the overall profit in any organization. Optimal values of involved costs, price, re-order point, and scheduling period are also calculated. In this work, the objective is to maximize the total profit and optimize production quantity. Optimization methods are used to obtain the maximum profit. Shortages are permitted and completely backordered. Total cost and production quantity models for deteriorating items have been developed. The study is validated with a numerical example, and sensitive analysis of the optimal solutions concerning main parameters is carried out using the software Mathematica. The tables are also shown for optimal values of the present model.