Cost Control Research Articles

Analytical Model for Contaminant Transport in the CGCW and Aquifer Dual-Domain System Considering GMB Holes

Composite geomembrane cut-off walls (CGCW) have been widely used for the remediation of polluted sites, especially where the environmental conditions are complex. Accurate predictions of the GMB hole leakage and CGCW performance are essential for engineering design and cost control. This paper establishes empirical equations to predict the leakages through the CGCWs based on the numerical models. Additionally, an analytical solution for contaminant migration through the CGCW is proposed considering the effects of GMB holes. The accuracy of the established equations and analytical solution is verified by the numerical models. The key effects of the GMB thickness (TG), head loss (HG), cut-off wall hydraulic conductivity (kG), hole radius (rG) and shape on the leakage and CGCW performance are investigated. The results show that compared with other hole shapes, the leakage through the circular hole is lowest. This is mainly because the shape factor for the circular hole is 1.15–1.3 times lower than that for other shapes of holes with the same area. Additionally, the effects of the hole geometric properties and head loss on the CGCW performance can be more significant when the cut-off wall hydraulic coefficient is small. For example, the breakthrough time differences between the cases with rG = 0.005 m and 0.05 m are 0.8 and 5.0 years when kG = 10−10 and 10−9 m/s, respectively. This is because the impermeability of the CGCW is good when kG is small. This will weaken the impacts of the hole geometric properties on the leakage. The proposed empirical equations and analytical solution can provide effective suggestions for the design of the CGCW in different GMB hole cases.

Raw Material Management Strategy in The Production Process of Tos-Tos Tortilla Chips (Case Study at PT Dua Kelinci)

PT Dua Kelinci is a company based in Pati that operates in the food industry. The purpose of this study is to analyze the raw material management strategy in the production process within PT Dua Kelinci’s Tos-tos Tortilla Chips division. The focus of this study is the role of the production supervisor in managing raw materials and ensuring efficient processes. This study employed a qualitative descriptive method, utilizing primary data collected through interviews. The data was then analyzed through data reduction, data presentation, and conclusion drawing. The findings of the study indicate that PT Dua Kelinci implements its raw material management strategy by (1) following a production process in accordance with work guidelines that outline monthly food orders, (2) recording input and output materials for accurate tracking, and (3) sourcing materials based on the quantity and variety of food orders, ensuring timely procurement of required flavors. This approach ensures a smooth production process, helps maintain product quality, and fulfills customer demands. Efficient management of raw materials not only reduces the likelihood of production delays but also ensures operational stability and cost control. The study concludes that strategic raw material management is essential for sustaining production efficiency and product quality at PT Dua Kelinci.

Cost Impact Factors and Control Measures of Road and Bridge Projects Based on Linear Regression Model

Cost Impact Factors and Control Measures of Road and Bridge Projects Based on Linear Regression Model

Impact of the entomopathogenic fungus Metarhizium anisopliae (Metchnikoff ) Sorokin on Spodoptera frugiperda (J.E Smith), an invasive maize pest in Chad

The invasion of agricultural plots by Spodoptera frugiperda (J.E Smith) constitutes a serious constraint to the sustainable maize production in Chad. Since then, farmers have unsuccessfully used available chemical insecticides to control this pest at that respect, the present study evaluated the bio-efficacy of two strains (Chinese and Senegalese) of Metarhizium anisopliae on the pest, both under laboratory and field conditions. Laboratory results showed that both strains were virulent against FAW resulting in a mortality of 90 ± 5.77% for the strain from Senegal and 75 ± 5.00% for that from China. In the field, significant differences were observed among the four treatments tested, namely the two M. anisopliae strains (2.5 kg/ha), the control and Emamectin benzoate (20g/ha) for both the infestation of maize plants and FAW densities (P <0.05). Meanwhile, maize grain yields were significantly the highest in plots treated with Emamectin benzoate followed by plots treated with either of the two strains of the fungus whose yields were statistically similar (df = 3; F = 27.13; P <0.0001). This biopesticide was more virulent under laboratory and field conditions and could be a promising biological control agent against S. frugiperda as an alternative to synthetic insecticides. However, additional studies that evaluate the implementation cost of the microbiological control are very necessary for more objective and robust conclusions. Key words: Fall armyworm, microbiological control, Zea mays, Emamectin benzoate, biopesticides.

Pengendalian Biaya Kedelai Home Industry Tahu-Tempe Mbak Sri

This study aims to analyze the material cost control in Mbak Sri's home industry of tofu and tempeh production. Material costs constitute a significant portion of the total production costs, and effective control measures are crucial for ensuring profitability. The research employs a qualitative approach, utilizing observation and in-depth interviews to gather data. The findings reveal that Mbak Sri implements several cost control strategies, including careful material selection, efficient utilization, and waste minimization. However, challenges arise due to fluctuating raw material prices and limited bargaining power. The study recommends implementing a comprehensive material management system, establishing strategic supplier relationships, and exploring alternative sourcing options to enhance cost control measures. By addressing these recommendations, Mbak Sri's home industry can improve its overall operational efficiency and profitability.

Analisis Efisiensi Biaya Tenaga Kerja Langsung pada PT. Davincy Airindo

This study was conducted with the aim to determine the efficiency of direct labor costs carried out by the company PT Davincy Airindo. In this study using literature review and observation, namely by conducting research in the field through direct interviews and data collection, related documents from the company through internet media. The data obtained is analyzed using the quantitative descriptive analysis method, namely how to compare labor costs that actually occur (actual). The results of the analysis will show whether direct labor costs are used efficiently to produce a product. This shows that Direct Labor Cost Control is in the efficient and stable category (in control).

Event-triggered finite-time guaranteed cost control of uncertain active suspension vehicle system

The event-triggered finite-time guaranteed cost control problem is important for an uncertain active suspension vehicle system. Existing works on the design of finite-time controllers for active suspension systems have not been extended to the event-triggered finite-time guaranteed cost control problem for uncertain active suspension systems. In this paper, we investigate the problem of designing an event-triggered finite-time guaranteed cost controller for an uncertain active suspension system. A new event-triggered controller and a cost function are first defined. Then, some new sufficient conditions for designing an event-triggered state feedback controller are derived based on linear matrix inequalities to stabilise the closed-loop systems while guaranteeing an adequate cost level of performance. Finally, numerical results and simulations are given to illustrate the effectiveness of the proposed method.

Research on Driver Emotion Monitoring and Regulation System in Intelligent Assisted Driving

Abstract. With the rapid development of smart connected vehicles, the influence, recognition and regulation of driver's emotions are crucial for intelligent cockpits with "emotional interaction". This review aims to provide a comprehensive analysis of driver emotion monitoring systems in intelligent assisted driving. By summarizing and analyzing related literature, the structure and application of emotion monitoring systems are introduced, their principles and evaluation criteria are discussed in depth, and the advantages and limitations of the three sub-systems, namely, detection, decision-making and regulation, are analyzed in detail. The results show that although emotion monitoring and modulation technologies perform well in enhancing driving safety and comfort, their practical applications still face challenges in terms of technology maturity, cost control, and privacy protection. In addition, the reliability and accuracy of current emotion monitoring systems in complex driving environments have yet to be improved. Future research should focus on interdisciplinary cooperation to integrate the latest achievements in psychology, computer science and engineering. At the same time, it is necessary to develop unified technical standards and evaluation guidelines to promote compatibility and interoperability between different systems and enhance research on privacy protection measures to ensure the security and confidentiality of user data. Through these efforts, the field of intelligent driving is expected to achieve comprehensive development and wide application, further enhancing driver safety and user experience.

Event-triggered explorized IRL-based decentralized fault-tolerant guaranteed cost control for interconnected systems against actuator failures

This paper presents a novel data-based decentralized guaranteed cost (DGC) fault tolerant control (FTC) scheme for the large-scale systems subject to actuator faults and mismatched interconnection. First, the FTC issues of interconnected systems are converted into a series of near optimal event-triggered control (ETC) methods for isolated subsystems via constructing a modified performance index function of each subsystem. By means of adaptive dynamic programming (ADP) algorithm, the upper bound of performance index function of large-scale systems can be obtained by solving the Hamilton–Jacobi-Bellman (HJB) equation of each auxiliary subsystem. Second, according to the proposed ADP-based decentralized approach and utilizing the event-based synchronous integral reinforcement learning (IRL) algorithm, a model-free guaranteed cost (GC) FTC approach is developed for interconnected large-scale system which can relax the restriction on the condition that system functions must be known. Further, the ultimate uniformly bounded (UUB) stability of auxiliary subsystems can be proved according to the Lyapunov principle. Finally, the effectiveness of the proposed control method is verified by presenting the simulation results.

Global practical finite-time synchronization of disturbed inertial neural networks by delayed impulsive control

This paper delves into the practical finite-time synchronization (FTS) problem for inertial neural networks (INNs) with external disturbances. Firstly, based on Lyapunov theory, the local practical FTS of INNs with bounded external disturbances can be realized by effective finite time control. Then, building upon the local results, we extend the synchronization to a global practical level under delayed impulsive control. By designing appropriate hybrid controllers, the global practical FTS criteria of disturbed INNs are obtained and the corresponding settling time is estimated. In addition, for impulsive control, the maximum impulsive interval is used to describe the frequency at which the impulses occur. We optimize the maximum impulsive interval, aiming to minimize impulses occurrence, which directly translates to reduced control costs. Moreover, by comparing the global FTS results for INNs without external disturbances, it can be found that the existence of perturbations necessitates either higher impulsive intensity or denser impulses to maintain networks synchronization. Two examples are shown to demonstrate the reasonableness of designed hybrid controllers.

The role of digital transformation in mergers and acquisitions

How digital transformation influences mergers and acquisitions (M&A) in firms is a significant yet seldom-explored inquiry. We argue that, differing from the “winner-take-all” logic observed in M&A undertaken by born-digital enterprises, digital transformation initiatives pursued by traditional firms can enhance long-term M&A performance by mitigating internal control costs in terms of organizational inertia. The findings from an analysis of M&A activities conducted by publicly listed Chinese firms demonstrate that the digital transformation efforts of traditional enterprises possess the potential to substantially augment long-term M&A performance. Nevertheless, this facilitative impact may encounter limitations due to structural inertia, strategic persistence and external pressure. Moreover, when compared to “technology-based” digital transformation, “application-based” digital transformation exhibits a superior capacity to facilitate long-term M&A performance by alleviating routine rigidity. This study extends the application of organizational inertia theory to the digital economy era and provides practical insights for enterprises that are implementing digital-transformation strategies.

Cost-utility analysis of provision of e-cigarette starter kits for smoking cessation in emergency departments: An economic evaluation of a randomized controlled trial.

To assess the cost-effectiveness of the Cessation of Smoking Trial in Emergency Department (COSTED) intervention compared with signposting to local stop smoking service (SSS) from the National Health Service (NHS) and personal social services (PSS) perspective. This was a two-group, multi-centre, pragmatic, individually randomized controlled trial set in six Emergency Departments (EDs) in urban and rural areas in the United Kingdom. Adult (≥ 18 years) daily smokers (at least one cigarette or equivalent per day) but not daily e-cigarette users, with carbon monoxide reading ≥8parts per million, attending the ED (n= 972) were included. The intervention consisted of provision of an e-cigarette starter kit plus brief smoking cessation advice and referral to a local SSS. Control was an information card on how to access local SSS. Intervention costs included costs of training and delivery. Control costs included costs of printing information cards. Costs of smoking cessation and health-care services were estimated based on quantities reported by participants and unit costs extracted from secondary sources. The effects were measured by quality-adjusted life years (QALYs) derived from EQ-5D-5L. Other outcomes were smoking cessation measures. The primary outcome was incremental cost-effectiveness ratio (ICER), which was calculated by dividing the difference in costs by the difference in QALYs between groups. The mean intervention costs were £48 [standard error (SE) = £0] per participant and the mean control costs were £0.2 (SE = £0) per participant. Using regression estimates, total costs were £31 [95% confidence interval (CI) = -£341 to £283] higher and 6-month QALYs were 0.004 (95% CI = -0.004 to 0.014) higher in the intervention group than in the control group. The ICER was calculated at £7750 (probability of cost-effective at range £20 000-30 000: 72.2-76.5%). The UK Cessation of Smoking Trial in Emergency Department (COSTED) intervention (provision of an e-cigarette starter kit plus brief smoking cessation advice) was cost-effective compared with signposting to local stop smoking services under the current recommendations of the maximum acceptable thresholds.

Cloud migration and microservices optimization framework for large-scale enterprises

As large-scale enterprises increasingly adopt cloud computing, the need for a structured framework to guide seamless cloud migration and optimize microservices architecture becomes critical. This review presents a comprehensive designed to address the challenges and opportunities associated with transitioning to cloud environments and optimizing microservices for performance, scalability, and security. The review begins with an assessment of the enterprise’s current infrastructure, emphasizing a phased approach to cloud migration. It outlines key strategies such as lift-and-shift, re-platforming, and re-architecting, each tailored to specific organizational needs. The selection of the appropriate cloud model (public, private, or hybrid) and the use of multi-cloud strategies are discussed to ensure flexibility and risk mitigation during migration. For microservices optimization, focuses on designing services that are loosely coupled and highly scalable. Key elements include the use of service discovery, load balancing, API gateways, and database management strategies to improve the efficiency and reliability of microservices. Additionally, this introduces security best practices, including identity and access management (IAM), encryption protocols, and microservices-specific security measures such as Zero Trust Architecture. The review also highlights optimization strategies involving containerization (Docker) and orchestration (Kubernetes), alongside the integration of Continuous Integration/Continuous Delivery (CI/CD) pipelines for streamlined development and deployment. Performance monitoring, real-time logging, and proactive maintenance are emphasized for sustained efficiency and cost control in cloud environments. Case studies demonstrate the successful implementation of cloud migration and microservices optimization in large enterprises, showcasing both the benefits and common challenges. The review concludes by exploring future trends, such as serverless computing and AI-driven optimization, that will continue to shape cloud migration and microservices architecture.

Research on Issues and Strategies of Financial Management Informationization in the Era of Big Data

In the context of rapidly evolving big data and cloud computing technologies, the field of corporate financial management is undergoing a profound transformation. Financial management informationization, as a core engine driving improvements in corporate efficiency and cost optimization, has become a new frontier in industry competition. This trend not only accelerates the intelligent and real-time nature of corporate decision-making processes but also profoundly alters traditional models of capital operations, cost control, and risk management. However, while the wave of big data offers unprecedented data treasures and powerful analytical tools for corporate financial management, it also brings a series of pressing challenges that need to be addressed. This paper aims to thoroughly analyze the main obstacles faced by financial management informationization in the era of big data and to propose a series of practical solutions.

Modern management model for KAREB Bojonegoro cooperative: Integration of ABM, lean six sigma, and RBV and TPB approaches

In global business competition, ABM helps cooperatives such as KAREB Bojonegoro Cooperative achieve cost efficiency without sacrificing quality. KAREB Cooperative's expenditure is very high, reaching IDR158.82 billion in five years, with the main costs on fuel, labor, and maintenance. Optimizing expenditure and cost management is important to reduce waste, increase efficiency, and profitability. Various studies have shown that Lean Six Sigma and ABM methods increase efficiency, reduce waste, and improve financial performance in various industries with proper implementation and intensive training. However, external factors, recent data, and regional variations, with deficiencies in data and methodology, and challenges in lean sigma implementation have not contributed simultaneously. This study offers the Integration of ABM, RBV, and TPB in Lean Sigma at KAREB Bojonegoro Cooperative because it is suspected that the condition of tobacco processing is not optimal and this approach needs to improve sustainable production efficiency. This study will analyze the implementation of ABM and Lean Sigma for cost control and waste reduction in tobacco drying at Kareb Cooperative with the contribution of Resource-Based View (RBV) and Theory of Planned Behavior (TPB) to improve process quality and optimal resource monitoring. This study uses a qualitative model with a case study method to assess the implementation of Activity-Based Management (ABM) in production cost efficiency, linking it with Lean Six Sigma, Resource-Based View (RBV), and Theory of Planned Behavior (TPB). Key informants from Kareb Cooperative Bojonegoro, including the Head of Production, Accounting, and HR, provided insights into the impact of ABM and internal factors on efficiency. The research instruments included in-depth interviews, observation, and documentation, while the research procedure followed a systematic flow to ensure the validity and relevance of the data. This study states that the implementation of ABM at Kareb Cooperative Bojonegoro allocates costs based on actual activities, improving efficiency and cost control. Costs include procurement of materials (Rp24,375,300,000), production (Rp9,216,862,000), and distribution (Rp6,000,000,000). Lean Sigma focuses on reducing waste such as overproduction, defects, and waiting by improving processes and training. The ability is quite large in identifying production inputs and related costs such as fuel (Rp14,375,300,000), raw materials (Rp10,000,000,000), and production and distribution processes. Waste management such as overproduction and waiting, as well as the implementation of ABM and Lean Sigma, aims to increase efficiency and reduce costs. Evaluation and training are carried out to optimize processes and reduce waste. Setting costs based on activities, while Lean Sigma uses the Just-In-Time (JIT) system. Variable costs are optimized, production is controlled to reduce defects,and distribution and storage are improved for cost efficiency. The keys to success are open communication, management support, and intensive training. The implementation of ABM and Lean Sigma in Kareb Bojonegoro Cooperative effectively reduces costs and waste through training, JIT, and process control. These findings are expected to increase productivity, reduce costs, and improve the competitiveness of cooperatives and provide a model for implementing modern management.

Optimal control of a queueing system

ABSTRACT We consider the M / M / k queueing model modified as follows: we assume that one can decide how many servers are working at any time. Suppose that at a given time instant, there are k + l customers in the system and that they are all waiting for service. Our aim is to determine how many servers should be used in order to reduce the number of customers to k + r, where 0 ≤ r < l , as rapidly as possible, while taking the control costs into account. The dynamic programming equation satisfied by the value function is obtained in the general case, and particular problems are solved explicitly.

Revolutionizing Procurement: How AI &amp; Data Analytics Driving Cost Effective Solutions in EPC

This paper, therefore, discusses the revolution brought by AI and Data Analytics in the procurement processes of EPC (Engineering, Procurement and Construction) and how each of the challenges, including cost control, enhanced efficiency and procurement downtime, could be solved using the two technologies. When the use of the procurement models is applied, the following benefits will be realized: supplier selection is facilitated using artificial intelligence, thereby automating the entire process; there is increased accuracy of costs compared to manual estimation, therefore reducing bias. The use of AI will allow better historical and real-time data analysis for procurement needs forecast, supplier evaluation and material cost prediction. Furthermore, machine learning algorithms can automate adjustments depending on real-time market variability, such for instance, a change in the price of the materials or a disruption in the supply chain, as well as execution flexibility regarding the project needs. Data Analytics also adds more weightage to procurement efficiency because it gives detailed analysis of the past and present procurement data. By utilizing state-of-the-art analytical frameworks, top managements are allowed to make powerful supplier analyses in relation to reliability, lead time, and cost of contracts prior to negotiations on contract supplier contracts and before contracting risks. What this study aims to do is to highlight real-life implementations of these technologies and how EPC firms can capitalize on these technologies to drive procurement efficiency, cost reduction, project delivery, and supplier relationship all for efficient project delivery. This paper thus provides a detailed discussion on the MI and TI of implementing AI and DA within procurement in the EPC sector via case studies and examples.

Can public hospital reform reduce medical resource mismatches? Evidence from China

BackgroundThe mismatch of medical resources is a significant issue in global healthcare, undermining both service accessibility and system efficiency. In China, despite the implementation of the “Healthy China” strategy, persistent mismatches remain due to factors such as industrialization, urbanization, and population aging. This study empirically evaluates the impact of Public Hospital Reform (PHR) on mitigating these mismatches.MethodsA Difference-in-Differences (DD) approach is applied to panel data from 300 cities spanning 2010 to 2021, using the phased implementation of PHR as a quasi-natural experiment. This allows for a comparative analysis of changes in resource allocation between cities that adopted the reform and those that did not. Quantile regression assesses the effects of PHR across varying levels of resource mismatch, while mechanism tests investigate how PHR influences mismatches through cost reduction and supply expansion.ResultsPHR is found to reduce medical resource mismatches by 13.9%, primarily driven by cost reductions and increased resource supply. The effects are more pronounced at both lower and higher levels of mismatch, with a limited impact at mid-levels. Furthermore, the reform’s effectiveness diminishes as it is extended to more cities, suggesting a potential saturation effect.ConclusionsThis study demonstrates that PHR significantly alleviates medical resource mismatches in China. The findings underscore the need to focus on cost control and resource supply in future healthcare reforms, providing key insights for policymakers in developing countries facing similar healthcare resource challenges.

Guaranteed Cost Control of Impulsive Nonlinear Stochastic Systems With Mixed Time Delays

ABSTRACTThis article mainly addresses the guaranteed cost control (GCC) problem for a class of impulsive nonlinear stochastic systems with mixed time delays, where both distributed time delay as well as discrete time delay are considered. Utilizing the Hamilton–Jacobi inequalities technique, Lyapunov–Krasovskii functional (LKF) and stochastic control theory, a new delay‐dependent sufficient condition is acquired to ensure the asymptotic stability in probability (ASP) of the closed‐loop system (CLS). Moreover, the guaranteed cost controller is designed and the upper bound of cost function is given. At the same time, three corollaries are presented for the special circumstance without impulse, distributed time delays or time‐varying time delay, respectively. Finally, the feasibility of the theoretical results is verified by an example.

Robust data-driven model-free adaptive control to uncertainties and disturbances for NARMAX systems

This paper introduces an enhancement to the model-free adaptive control (MFAC) method based on a new control input cost function for full-form dynamic linearization (FFDL) for NARMAX systems. The new control cost function includes the one-step-ahead tracking error, OER, and output error integral. The main feature of the approach is that it has a high ability to overcome disturbances in the control input and measured noise in the output. Analytical and extensive simulations have demonstrated that the novel control law exhibits superior response and robustness in comparison to the prototype MFAC. Moreover, it guarantees stability and convergence of the tracking error by enforcing bounded-input bounded-output (BIBO) criteria. In addition, 20 Monte Carlo simulations were conducted to test the initial conditions and random control parameters, and the results demonstrated that the proposed control outperformed the prototype MFAC.