Cost Constraints Research Articles

METHODOLOGICAL FOUNDATIONS OF OPTIMAL SWARM MANAGEMENT OF UAVS IN ENERGY CROP SPRAYING WITH AGROCHEMICAL AGENTS

The work is devoted to research on the optimal management of a UAV swarm when spraying energy crops with toxic chemicals. The relevance of the work lies in the fact that, at present, the solution of chemical plant protection tasks using UAVs is based on the individual experience of a human operator, who manages a swarm of UAVs, as a rule, in a non-optimal way with significant time and cost costs. The purpose of the article is to develop methodological principles for optimal management of a UAV swarm when spraying energy crops with agrochemicals. In order to achieve the goal, the following tasks must be solved: the formulation of the task of optimizing the management of a UAV swarm is substantiated, taking into account the time and cost constraints for the performance of chemical plant protection tasks, a method of optimal management of a UAV swarm when spraying energy crops with toxic chemicals and foliar feeding is developed, which provides a solution tasks to maximize the number of sprayed plants in each field section under time and cost constraints, a structural diagram of the solution to the task of optimizing the UAV swarm management was developed for the high-quality practice of chemical plant protection tasks. The scientific novelty of the work consists in the application of the dynamic programming method in the distribution and management of a swarm of UAVs on each site when spraying energy crops with agrochemicals. The practical value of the work lies in the development of a structural scheme for solving the problem of optimizing the control of a UAV swarm, with the help of which the optimal number of UAVs in a given time sequence is calculated in special software. automated operator's workplace for high-quality performance of chemical protection and plant nutrition tasks.

Optimal test plans for accelerated life tests based on progressive type-I censoring with engineering applications

In reliability engineering studies, the accelerated life tests with optimal test design that balances cost constraints is particularly important since the lifetimes of electro-mechanical, electronic, and mechanical goods are typically modelled with this characteristic. Comparative optimal test plans for accelerated life tests are developed in a variety of applications, including engineering, biological, medical, and other related fields. In this study, we compare, under cost restriction with a specified budget, optimum multiple constant stress and step stress accelerated life tests based on progressive-type-I censoring. The goal is to assess the advantage provided by step-stress testing over constant-stress testing. In order to conduct an accelerated life test effectively, stress durations need to be carefully specified during the design stage due to limited resources in engineering practice. The estimated accuracy of the parameters of interest and the expense of the experiment are directly impacted by the stress durations. Under a prespecified budget and cost constraints, this article examines the optimal stress durations based on D-, E-, T-, C-, R-, and P-optimal criteria. These criteria are also contrasted together. We illustrate the application of the optimal durations using numerical and simulation examples. A study is conducted to determine how sensitive the optimal duration is to model parameter misspecification.

Advancing pneumonia virus drug discovery with virtual screening: A cutting-edge fast and resource efficient machine learning framework for predictive analysis

Pneumonia, a severe respiratory infection characterized by a significant morbidity and fatality rate, afflicts many individuals globally. The demand for highly effective antiviral medications has experienced a surge because of the emergence of novel pneumonia viruses, such as the COVID-19 coronavirus. Due to their inherent time and cost constraints, conventional drug development strategies sometimes need to be more manageable. Exploring alternative approaches is crucial to identifying and establishing effective therapy choices. This work introduces a computational methodology for analyzing the chemical space of medications targeting the pneumonia virus, employing Python-based data mining tools. Using computer-aided analysis in drug molecules aims to enhance the efficiency of identifying and evaluating potential new therapeutic candidates using Machine Learning (ML). The research successfully discovered two therapeutic compounds by utilizing the Bayesian Ridge approach, which is the most accurate with the least mean squared error, is less computationally expensive in terms of power, memory, and CPU, and is the fastest of the investigated approaches. It discovered the CHEMBL433378 and CHEMBL93653, with promising docking scores of −4.3 and −4.2, respectively. Additionally, both molecules demonstrated significant inhibitory activity against their respective targets, as seen by their IC50 values of 0.0018 and 0.001. Both compounds meet the criteria for the B. Mann Whitney U Test and Lipinski test.

РОЗВ’ЯЗАННЯ МУЛЬТИМОДАЛЬНОЇ ТРАНСПОРТНОЇ ЗАДАЧІ З УРАХУВАННЯМ ОБМЕЖЕНЬ ЛОГІСТИЧНИХ ПОКАЗНИКІВ

The implementation of military transportation by all types of transport involves planning, management, deployment of transport communications, distribution and preparation of types of transport, organization of the transportation of troops and military property, evacuation of the wounded and sick, damaged weapons and military equipment, and trophy property. As a result of these actions, the issue of timely delivery of material and technical means with the lowest costs should be resolved. The solution to the multimodal (three-index biplanar) transportation problem is presented to find the rational distribution and delivery of material and technical means. The proposed solution considers the limitations of logistics indicators, such as delivery time, the available carrying capacity of different types of vehicles, the total cost of transportation in the operational movement of storage points and consumers, changes in supply routes, and delivery vehicle types. Introducing an additional constraint into the three-index biplanar transport problem turns it into a linear programming problem of general form. The three-index transportation problem with extra logistical constraints is given a mathematical formulation. A form of input data presentation in the extended transport tables of transportation costs and time spent on cargo transportation is given. An easy way to solve this kind of problem using the simplex method is demonstrated in the Microsoft Excel spreadsheet processor "Solver" add-on. The article presents the results of solving a multimodal transportation problem with logistical constraints in Microsoft Excel using the example of the delivery of material and technical means by three types of transport (road, rail, and river), with time and cost constraints. The example uses conditional input data for the simulation of the delivery of cargo from three Ukrainian cities (storage points) to the other three (consumption points).

Enterprise Resource Planning (ERP): Opportunities, Benefits and Implementation Challenges in Bangladesh

Enterprise Resource Planning (ERP) is a software system used by organizations to manage and integrate the core functions like manufacturing, finance, human resources, supply chain, and customer management of their business processes in a unified system which has been proved to be a vital instrument for improving operational efficiency, reducing manual work, enhancing data accuracy and thus facilitates timely and accurate decision-making which help an organization to adapt and craft an appropriate proactive response to evolving challenges and problems of today's changing market trends, rising customer expectations, and growing global competition. With this backdrop, the aim of this study is to know the status of available opportunities that create facilitating conditions for effective ERP implementation in Bangladesh and the resulting benefits of ERP implementation as well as the challenges of ERP implementation in Bangladeshi enterprises. This paper used secondary data sources that include browsing internet databases like Google scholar, emerald, web of science, and research gate to find research papers, articles, and study materials on ERP. The study reveals that supportive policies of government, increasing technological infrastructure, growing IT expertise, financial support from different financial institutions create major opportunities for ERP implementation in Bangladesh. Moreover, improved efficiency, centralized information systems, facilitating better decision-making, automatic process identified as the major benefits of adopting ERP and cost constraint, resource constraint, inadequate IT infrastructure, organizational resistance, customization challenges, vendor dependency are the prime challenges of implementing ERP system in Bangladeshi organizations. Finally, the paper proposes some suggestions to overcome the challenges.

Production Activity Control Framework for the Make-To-Order Industry Utilizing Cyber-Physical Production System

The make-to-order industry has complex production activities due to the varying nature of customer orders. The ability to meet production specifications within agreed time and cost constraints is crucial in satisfying customer demands. Therefore, effective monitoring of production activities is essential. In order to track production activities, this research proposes a Production Activity Control Framework using the Cyber-Physical Production System. The proposed framework enables precise monitoring of 1) machine activities, which include idle, setup, and processing times, and 2) operator activities, such as productive and idle times. The effectiveness of the proposed framework was tested and validated in the make-to-order industry. Its implementation demonstrates the ability to enhance control over the production schedule and direct manufacturing costs. With the proposed framework, the evaluation of operator and machining costs can be performed accurately, as opposed to the traditional production activity control activities in the make-to-order, which relies on estimates or an aggregate approach.

Environmental investment timing and dual government incentives under uncertain carbon allowances

The government's post compliance cycle announcement of carbon allowances hampers firms from obtaining accurate information. Firms must estimate carbon allowances before determining the optimal environmental investment timing. Typically, firms prioritize environmental investments by introducing environmental equipment during the compliance cycle (ID) when their estimated carbon allowances are low. Conversely, they prefer to make environmental investments after the compliance cycle (IA) by purchasing carbon credits to offset excess emissions. This study aims to present a process and outcomes for firms to accurately select the timing of environmental investments based on estimated carbon allowances. Moreover, their improper timing can lead to a loss in government social welfare. To mitigate the loss, the dual government incentives of commitment and subsidies are further introduced. Contrary to the intuition that low carbon estimates would lead to an ID decision, firms should choose IA due to the higher costs and shorter lifespan for introducing environmental equipment or lower carbon prices. Generally, the government sets the least strict carbon allowances that still achieve the desired incentives while staying within the permissible spectrum of environmental preservation. However, for firms that face high market demand but experience reduced production due to technological or cost constraints, the government should provide subsidies to encourage them to adopt alternative investment timing. This will ensure product supply, maintain firm profits, and enhance social welfare.

Evidence-based dust exposure prediction and/or control tools in occupational settings: A scoping review protocol.

Workplace atmospheric exposure monitoring is the standard method to assess and control hazardous dust exposure; however, feasibility and cost constraints often limit its application. In recent decades, evidence-based tools supporting exposure modelling and control banding have been developed to aid in predicting and/or controlling occupational exposure to various contaminants. However, there is limited information on the availability and applicability of evidence-based tools for predicting and/or controlling occupational dust exposure, as well as on the methods for evaluating these tools across different exposure scenarios. Therefore, this planned scoping review aims to identify existing evidence-based tools for dust exposure predicting and/or controlling and to present evaluation approaches. We will employ the scoping review methods developed by the Joanna Briggs Institute (JBI). The search will be conducted on PubMed, Scopus, and Web of Science databases, in addition to grey literature from the National Institute for Occupational Safety and Health (NIOSH) and advanced Google searches. Studies will be included if they report evidence-based tools for predicting and/or controlling dust exposure using quantitative or semi-quantitative designs and provide a detailed explanation of the methods used for tool development. There will be no restrictions on publication date or geographical location; however, only studies published in English will be considered. Studies focusing exclusively on dust exposure in environmental settings will be excluded. Each member of the review team will screen titles, abstracts, and full texts independently and in collaboration, based on the inclusion criteria. The extracted data will encompass details such as author, title, country, accessible platforms, method/tool names, intended users, types of dust, and occupational settings. Descriptions of the identified tools will include numerical data and narrative summaries to ensure a comprehensive overview. OSF (https://doi.org/10.17605/OSF.IO/S6EZJ).

A Potential-Real-Time Thigh Orientation Prediction Method Based on Two Shanks-Mounted IMUs and Its Clinical Application

The detection and evaluation of gait kinematics is vital for patient diagnosis and rehabilitation. Aiming at limitations of commonly used optical capture and wearable sensing systems in clinical applications, this paper proposes a thigh attitude angle prediction method based on the hip error tolerance from the kinematic data of two shank-mounted IMUs (Inertial Measurement Unit). The novelties of the proposed method are summarized as follows: i) It develops a parallel approach to regress variation of hip error tolerance for different subjects. This parallel approach, by simultaneously deconstructing the shank kinematics data via different regression algorithm including support vector machine, boosting tree, and stepwise linearity regression, is able to well accommodate the characteristics of both health subjects and patients. ii) It develops some evaluation indices based on gait symmetry, consistency, and activity to fully evaluate the human lower limbs motion performance in gait by only two IMUs. The effectiveness of the proposed method is verified by the experimental results among 8 healthy subjects and 16 cerebral infarction patients. For the healthy subjects, the estimated error of thigh prediction compared with Xsens and Vicon are <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.3 \pm {0.3^ \circ }$</tex-math> </inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.5 \pm {0.7^ \circ }$</tex-math> </inline-formula> , respectively. For the patients, the estimated error compared with Xsens-measured angle is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4.8 \pm {1.7^ \circ }$</tex-math> </inline-formula> . Its broad significance in actual intelligent healthcare and robotics-assisted rehabilitation is three-fold: First, it is a recursive real-time method as it only needs data from the previous gait cycle to predict the thigh angle. Second, its accuracy meets the actual clinical needs. Third, it is a low-cost method that only needs two IMUs and has high potentials of clinical applications. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Gait is of great significance to quantify the degree of movement disorders in clinical practice, and the existing equipment is rarely able to meet the needs of full dimension, low cost, and low place constraints in clinical practice. This paper presents an innovative gait kinematic prediction method, which only uses two IMUs attached to the shanks to predict the orientation of thigh. Compared with related works, the proposed methods have achieved high-precision, real-time and low-cost acquisition. This paper is inspired by the problems of large number, high motion interference, and high cost of wearable gait measurement devices in clinical practice. The proposed method have potential to be integrated into exoskeletons and medical walking AIDS, which could greatly improve the comfort and control precision of the wearable system.

Distributed Online Stochastic-Constrained Convex Optimization With Bandit Feedback.

This article studies the distributed online stochastic convex optimization problem with the time-varying constraint over a multiagent system constructed by various agents. The sequences of cost functions and constraint functions, both of which have dynamic parameters following time-varying distributions, are unacquainted to the agent ahead of time. Agents in the network are able to interact with their neighbors through a sequence of strongly connected and time-varying graphs. We develop the adaptive distributed bandit primal-dual algorithm whose step size and regularization sequences are adaptive and have no prior knowledge about the total iteration span T . The adaptive distributed bandit primal-dual algorithm applies bandit feedback with a one-point or two-point gradient estimator to evaluate gradient values. It is illustrated in this article that if the drift of the benchmark sequence is sublinear, then the adaptive distributed bandit primal-dual algorithm exhibits sublinear expected dynamic regret and constraint violation using both two kinds of gradient estimator to compute gradient information. We present a numerical experiment to show the performance of the proposed method.

Implementing integrative therapies in adult critical care: Barriers and strategies

BackgroundCritically ill patients experience intense physical and psychological stressors in the intensive care unit (ICU). More than half of ICU survivors report overwhelming mental health symptoms after ICU discharge, such as post-traumatic stress symptoms, anxiety, and depression. Relaxation-inducing integrative therapies such as guided imagery, massage, therapeutic touch, music therapy, and spirituality-based healing practices have the potential to promote comfort and relaxation and improve patient outcomes. ObjectivesThe aim of this study was to explore the attitudes of healthcare professionals towards the implementation of relaxation-inducing integrative therapies in critical care, barriers to implementation, and potential strategies to overcome them. MethodsWe conducted seven focus group interviews with 23 critical care clinicians (70% nurses, 17% allied health professionals, 13% physicians). Interviews were audiotaped and transcribed verbatim. Data were thematically analysed using an inductive content analysis approach. FindingsResults reveal a constant interplay between mostly positive personal attitudes towards implementation of integrative therapies and the perceived culture and priorities of the unit. The main benefits for critically ill patients as perceived by participants were promotion of comfort, sleep, and coping, increase of trust, and decrease of pain and stress. As for barriers, dominant themes were a perceived lack of evidence, cost, and time constraints and the fear of loss of professional credibility. Participants related nurses’ education and training, family involvement, and leadership were seen as main strategies for implementation. ConclusionsThe dominant ICU culture needs to be considered when implementing integrative therapies. Education, access to evidence, and role modelling are proposed as means to shift the ICU culture towards utilisation of integrative therapies in critical care.

Assessing the Moderating Role of Supervisor Support in Amplifying Total Quality Management Practices and Project Performance within Pakistan’s Manufacturing Sector Post-Covid19: An Empirical Study

This empirical research investigates the interplay between Total Quality Management (TQM), Project Performance (PP), and Supervisor Support (SS) within the context of post-Covid-19 pandemic manufacturing firms in Pakistan. The study involved the development and distribution of a questionnaire to manufacturing industries located in federal area of Pakistan, Khyber Pakhtunkhwa, Pakistan and northern Punjab, Pakistan. Upon scrutinizing the collected data, the research revealed a noteworthy and positive correlation between Total Quality Management and Project Performance. Out of 195 distributed questionnaires, 131 responses were received. Interestingly, while global literature commonly asserts that Supervisor Support serves as a beneficial moderator in the relationship between Total Quality Management and Project Performance, the study’s findings in the Pakistani manufacturing sector suggested a different reality. Specifically, supervisors were perceived as providing insufficient support to their subordinates in matters of quality. Some employees also highlighted that their organizations struggled to implement TQM practices fully, occasionally breaching cost and time constraints in projects; nevertheless, these organizations remained highly profitable. Overall, it suggests that manufacturing industries in Pakistan may benefit from prioritizing Supervisor Support within the framework of Total Quality Management to enhance their overall performance and production efficiency.

Extending SysML to Integrate Cost Analysis Into Model-Based Systems Engineering

Model-based systems design (MBSD), a current trend adopted by INCOSE, employs the systems modeling language (SysML), a standard introduced by OMG and INCOSE. Though there are numerous works on integrating performance exploitation in SysML, cost is not sufficiently explored as a driving design parameter. By integrating cost analysis in a popular modeling language like SysML, the proposed approach may be applied to any system designed using standardized languages and tools. In this work, we integrate cost analysis within SysML models at a generic level to explore design alternatives under specific cost and performance restrictions and perform tradeoff analysis. The proposed SysML extensions provide: 1) cost-related entities to encode cost aspects, such as capital and operating expenses, and 2) functions that enable the automatic computation of costs; these extensions are contained in a custom SysML cost profile. The feasibility and benefits of the approach are explored in two distinct real-world case studies with different purpose and characteristics. 1) Configuring a remote elderly monitoring system, taking into consideration patients' budgetary and operational concerns regarding the equipment installed in their homes. In this case, patients had the opportunity to evaluate and prioritize their concerns prior to using the system. 2) Exploring the improvement of the passengers' comfort as a level of service indicator in the Athens Metro railway system, taking into account operational cost constraints. In this case, the operator obtained forecasts of performance and cost of the metro system operation in order to choose between different operational policies.

Robustness Optimization of Air Transportation Network With Total Route Cost Constraint

Robustness Optimization of Air Transportation Network With Total Route Cost Constraint

Construction Project Management Issues and Development in Current for Future Construction Project: Challenges and Prospects in Sustainable Project Management

The global construction industry faces escalating pressure to embrace sustainable practices in response to increasing awareness of environmental and social issues. The construction sector, with its profound impact on the built environment, plays a pivotal role with far-reaching environmental, social, and economic implications. Stakeholders in the construction industry, driven by concerns related to climate change, resource depletion, and social equity, actively seek strategies to mitigate their environmental and societal impact. This has culminated in a heightened emphasis on sustainability in construction project management. The aim of this research is to investigate the challenges and propose proactive strategies among construction project stakeholders to effectively integrate sustainable practices into project management. This research systematically reviews existing literature to illuminate the challenges and prospects associated with integrating sustainability into construction project management, focusing on the future of construction projects. Challenges encountered by construction project managers include cost constraints, limited awareness and training, resistance to change, and the complexity of sustainability metrics. Understanding and addressing these challenges are imperative for the successful implementation of sustainable construction practices tailored to the unique context of construction firms. On the positive side, integrating sustainability into construction project management holds promising prospects. It is anticipated to result in reduced resource consumption, enhanced energy efficiency, lower operational costs, and an improved public image. Furthermore, aligning construction projects with sustainable development goals opens avenues for innovation and market differentiation. This research underscores the necessity of proactive strategies and collaborative efforts among project stakeholders to overcome challenges associated with sustainable construction. It highlights the potential for future construction projects to contribute significantly to a more sustainable built environment, emphasizing the growing importance of sustainability in construction projects. By addressing these challenges, the construction industry can progress towards a more sustainable future, aligning with global efforts to combat climate change and promote responsible resource management.

Manual red cell exchange (RBCXm) in acute sickle cell crisis: A feasible modality in resource limited settings

This short communication highlights the significance of manual red blood cell exchange (RBCXm) procedure which is an emergency procedure for patients of sickle cell disease (SCD) in sickle cell crisis . To the best of our knowledge there is no standardised technique for performing RBCXm meanwhile, an automated method using an apheresis machine is either unavailable or is unaffordable. As a result, patients end up receiving top up red cell transfusions further associated with risk of iron overload, hyper viscosity and sometimes volume overload overshadowing the benefits of red cell exchange. Therefore, we developed a protocol for manual red cell exchange (RBCXm) and performed it in a patient with painful sickle cell crisis who had cost constraints for automated red cell exchange (RBCXa) procedure. RBCXm provided symptomatic relief to our patient with adequate sickle cell reduction. This RBCXm protocol may be useful in low income (LIC) and low middle income countries (LMIC) where patients have recurrent episodes of sickle cell crisis and there is unavailability or unaffordability for RBCXa using an apheresis equipment.

Evaluating Novel SP-B and SP-C Synthetic Analogues for Pulmonary Surfactant Efficacy.

Pulmonary surfactants, a complex assembly of phospholipids and surfactant proteins such as SP-B and SP-C, are critical for maintaining respiratory system functionality by lowering surface tension (ST) and preventing alveolar collapse. Our study introduced five synthetic SP-B peptides and one SP-C peptide, leading to the synthesis of CHAsurf candidates (CHAsurf-1 to CHAsurf-5) for evaluation. We utilized a modified Wilhelmy balance test to assess the surface tension properties of the surfactants, measuring spreading rate, surface adsorption, and ST-area diagrams to comprehensively evaluate their performance. Animal experiments were performed on New Zealand white rabbits to test the efficacy of CHAsurf-4B, a variant chosen for its economic viability and promising ST reduction properties, comparable to Curosurf®. The study confirmed that higher doses of SP-B in CHAsurf-4 are associated with improved ST reduction. However, due to cost constraints, CHAsurf-4B was selected for in vivo assessment. The animal model revealed that CHAsurf-4B could restore alveolar structure and improve lung elasticity, akin to Curosurf®. Our research highlights the significance of cysteine residues and disulfide bonds in the structural integrity and function of synthetic SP-B analogues, offering a foundation for future surfactant therapy in respiratory disorders. This study's findings support the potential of CHAsurf-4B as a therapeutic agent, meriting further investigation to solidify its role in clinical applications.

Proportional Topology Optimization algorithm with virtual elements for multi-material problems considering mass and cost constraints

This paper presents an extension of the Proportional Topology Optimization (PTO) with virtual elements for multi-material problems with mass and cost constraints. In particular, the linear virtual element method (VEM) is constructed on unstructured polygonal meshes. The linear VEM is desirable in the sense that numerical integration is not explicitly required, significantly reducing the computational effort. Furthermore, the unstructured polygonal mesh naturally eliminates the issue of one-node connections encountered by the usual quadrilateral mesh. A feature of PTO is that it does not require sensitivity information, i.e., the derivative of the objective function with respect to design variables. Instead, the amount of material distributed into each element is determined proportionally to the contribution of that element to the objective function. For multi-material problems, the Ordered Solid Isotropic Material with Penalization (Ordered SIMP) technique is integrated into the PTO framework. Compared to other techniques for problems that involve multiple materials, Ordered SIMP has the advantage that computational cost does not depend on the number of materials. Furthermore, for the first time, the PTO approach is extended to consider two types of constraints: mass and cost simultaneously. The feasibility and efficiency of the proposed method are demonstrated via several benchmark examples and comparisons with the existing approach.

Joint optimization of two-dimensional warranty period and maintenance strategy considering availability and cost constraints

Abstract Warranty can improve customer satisfaction and increase product sales, but it will bring additional economic burden to manufacturers, so making reasonable warranty decisions is particularly important. The current research focuses more on the interests of manufacturers, while there is less attention paid to indicators that consumers are concerned about, such as system availability. To solve this problem, a joint optimization model of the two-dimensional warranty period and preventive maintenance (PM) strategy considering availability and cost constraints was established. Based on the failure dependence analysis of multi-component systems, the actual failure rate function is constructed by using the failure dependence coefficient matrix. Based on the comprehensive consideration of imperfect PM and minimum maintenance, the two-dimensional warranty cost model and system availability model are established, respectively. Aiming at maximum availability and considering the warranty cost budget constraint, a joint optimization model of the two-dimensional warranty period and PM strategy was built, and a model-solving algorithm combining grid search and binary search was introduced. The effectiveness of the model is verified by the case analysis, and the necessity of the PM strategy and considering failure dependence are reflected in the model comparative analysis and parameter sensitivity analysis. Finally, reasonable suggestions are put forward for manufacturers’ warranty decisions through the result analysis.

개인정보 분쟁의 특수성과 분쟁해결제도에 관한 연구

The proliferation of indispensable platforms and services has elevated the utilization of users' personal data, consequently giving rise to an escalation in personal information disputes. Over the past decade, the number of cases managed by the Personal Information Dispute Resolution Committee has surged by 582%. Traditional legal proceedings face formidable challenges due to substantial time and cost constraints, hindering expeditious resolutions. Furthermore, the multifaceted nature of personal information breaches adds complexity to accurately discerning the nuances of the damages incurred.&#x0D; Personal information breaches occur on various fronts, disseminating sensitive information through online behavioral tracking technology and big data analysis. Due to the unique characteristics associated with personal information, including anonymity, data intricacies, and technological vulnerabilities, a diverse range of breach methods emerges.&#x0D; Personal information breaches occur on various fronts, disseminating sensitive information through online behavioral tracking technology and big data analysis. Due to the unique characteristics associated with personal information, including anonymity, data intricacies, and technological vulnerabilities, a diverse range of breach methods emerges.&#x0D; Disputes related to personal information have the potential to evolve into significant issues affecting not only individual concerns but the entire societal landscape. Recognizing and increasing awareness of this importance, along with efforts for legal system enhancements, becomes imperative. This study aims to explore effective improvements in the system and appropriate policy directions for addressing disputes related to personal information.