Search results

The purpose of this paper is to develop a new approach for equipment states prediction and provide a method for early warning of possible trouble states.

A new two-stage multi-level equipment state classification system was proposed to forecast equipment operation status. The first stage involves predicting the equipment's normal state, and the second stage involves forecasting the equipment's abnormal status. Meanwhile, the equipment state classification is done according to the manufacturing company's internal specifications to define various equipment statuses. Then, the trouble state and waiting state were predicted by grey state prediction model.

A new two-stage multi-level equipment status classification system and a new approach for equipment states prediction has been proposed in this paper.

The application on a real-world case shown that the model is very effective for predicting equipment state. The equipment's major failure risk can be reduced significantly.

The proposed approach can help improve the effective prediction of the equipment's various operation states and reduce the equipment's major failure risk and thus maintenance costs.

The main purpose of this paper is to select appropriate voltage vectors in the switching techniques and, by selecting the proper voltage vectors, be able to achieve a DC link with the same outputs and a symmetric multi-level inverter.

The proposed structure, a two-stage DC–AC symmetric multi-level inverter with modified Model Predictive Control (MMPC) method, is presented for Photovoltaic (PV) applications. The voltage of DC-link capacitors of the boost converter is controlled by MMPC control method to select appropriate switching vectors for the multi-level inverter. The proposed structure is provided for single-phase power system, which increases 65 V input voltage to 220 V/50 Hz output voltage, with 400 V DC link. Simulation results of proposed structure with MMPC method are carried out by PSCAD/EMTDC software.

Based on the proposed structure and control method, total harmonic distortion (THD) reduces, which leads to lower power losses and higher circuit reliability. In addition, reducing the number of active switches in current path causes to lower voltage stress on the switches, lower PV leakage current and higher overall efficiency.

In the proposed structure, a new control method is presented that can make a symmetric five-level voltage with lower THD by selecting proper switching for PV applications.

To dilute the financial difficulties in agricultural production and operation, the Chinese government has actively explored and developed rural supply chain finance (RSCF) service systems. The purpose of this study is to evaluate and analyze the performance of RSCF systems in China.

To evaluate the performance of RSCF systems in China, this study proposes a two-stage data envelopment analysis model. Compared with other models, the model proposed in this study considers not only the technical gap between RSCF systems but also the maximization of intermediate output to conform to the practice of RSCF.

Based on the empirical analysis, this study draws the following four conclusions. First, the overall efficiency of China's RSCF systems is low, and there remains great potential for improvement. Second, the technology gap ratio index score and meta-frontier efficiency of RSCF systems in Central China are the lowest in all regions, indicating that the technical level of RSCF systems in Central China is the lowest. Third, the relationship between rural residents' disposable income and the efficiency of RSCF systems is U-shaped, and the efficiency of RSCF systems in the high-income group is far greater than that of other income groups. Finally, the main reason for the lack of efficiency in RSCF seems to lie in management and technology.

This study divides all RSCF systems into four types according to management potential and technical potential, and recommend corresponding improvement suggestions for different kinds of RSCF systems.

A comprehensive review of the literature for the problem of lot‐size scheduling (serial and assembly) considering the uncapacitated problem and complicated capacitated assembly manufacturing structure. Analyses the different solution techniques and findings for each product set.

Of critical concern to the world is the need to reduce consumption and waste of natural resources. This study provides a multi-level exploration of the ways situational and transformational links between levels and challenges are related to the adoption and utilization of material flow cost accounting in Vietnam, to encourage green productivity.

Based on triangulation of public documents at different institutional levels and a set of semi-structured interviews, situational and transformational links and challenges for material flow cost accounting in Vietnam are examined using purposive and snowball sampling of key actors.

Using a multi-level framework the research identifies six situational and transformational barriers to implementation of material flow cost accounting and suggests opportunities to overcome these. The weakest links identified involve macro-to meso-situational and micro-to macro-transformational links. The paper highlights the dominance of meso-level institutions and lack of focus on micro transformation to cut waste and enable improvements in green productivity.

The paper identifies ways for companies in Vietnam to reduce unsustainability and enable transformation towards sustainable management and waste reduction.

The paper is the first to develop and use a multi-level/multi-time period framework to examine the take-up of material flow cost accounting to encourage transformation towards green productivity. Consideration of the Vietnamese case builds understanding of the challenges for achieving United Nations Sustainable Development Goal number 12, to help enable sustainable production and consumption patterns.

The purpose of this paper is to model a block-based inspection policy for a multi-component system with stochastic dependence. Some components may develop a hidden failure, an occurrence of which neither stops the system nor accelerates the other components’ deterioration. On the other hand, other components may experience three states: healthy, defective and revealed failures. Any revealed failure of each component not only stops the system but also generates a shock to all the other ones, which increases their occurrence rate of hidden, defect and revealed failures.

A block-based inspection policy is considered to take advantage of economic dependence as follows. In addition to the periodic inspections, the system is also inspected at revealed failures’ moments of each component to detect and fix both defects and hidden failures on all the other components. To calculate the expected total cost, the recursive equations for the required expected values is first mathematically derived. Then, due to computational complexity, an efficient Monte Carlo simulation algorithm is designed to calculate the expected values.

The proposed approach is illustrated through a numerical example, and the optimal periodic inspection interval over a finite time horizon is obtained via minimization of the expected total cost. Finally, the correctness of the results is validated by conducting sensitivity analysis.

Planning an appropriate inspection policy over a finite time horizon becomes more complicated when considering a multi-component system because different units may experience different failure modes with stochastic dependence.

This paper aims to propose a new configuration of a shunt active power filter (SAPF) connected with a photovoltaic (PV) system through a Z-source inverter (ZSI) topology. This topology ensures a single-stage operation and overcomes the limitations of the conventional two-stage operation topologies based on the DC–DC boost converter. The proposed system is designed for the purpose of reducing the total harmonic distortion of the source current by eliminating the current harmonics and exploiting the solar irradiation.

First, all the main parts of the proposed shunt active power filter are fully described in this paper, and then a PV system based on a Z-source inverter with a maximum power point tracking controller is used to exploit the solar irradiance and solve the problem of discharging of the direct current (DC) capacitor during the filtering process.

From the extensive simulation tests carried out using MATLAB/Simulink, the obtained results prove that the proposed shunt active power filter performs well despite several operation scenarios, including different load types and under abrupt irradiance.

A new shunt active power filter configuration has been proposed. This configuration benefits from the solar irradiation and overcomes the drawbacks of the conventional configurations by using the Z-source inverter instead of the voltage source inverter and DC–DC boost converter.

Optimization of energy planning for growth and sustainable development has become very important in the context of climate change mitigation imperatives in developing countries. Existing models do not capture developing country realities adequately. The purpose of this paper is to conceptualizes a framework for energy strategy optimization of the Indian energy sector, which can be applied in all emerging economies.

Hierarchical multi‐objective policy optimization methodology adopts a policy‐centric approach and groups the energy strategies into multi‐level portfolios based on convergence of objectives appropriate to each level. This arrangement facilitates application of the optimality principle of dynamic programming. Synchronised optimization of strategies with respect to the common objectives at each level results in optimal policy portfolios.

The reductionist policy‐centric approach to complex energy economy modelling, facilitated by the dynamic programming methodology, is most suitable for policy optimization in the context of a developing country. Barriers to project implementation and cost risks are critical features of developing countries which are captured in the framework in the form of a comprehensive risk barrier index. Genetic algorithms are suitable for optimization of the first level objectives, while the efficiency approach, using restricted weight stochastic data envelopment analysis, is appropriate for higher levels of the objective hierarchy.

The methodology has been designed for application to the energy sector planning for India's 12th Five Year Plan for which the objectives of faster growth, better inclusion, energy security and sustainability have been identified. The conceptual framework combines, within the policy domain, the bottom‐up and top‐down processes to form a hybrid modelling approach yielding optimal outcomes, transparent and convincing to the policy makers. The research findings have substantial implications for transition management to a sustainable energy framework.

The methodology is general in nature and can be employed in all sectors of the economy. It is especially suited to policy design in developing countries with the ground realities factored into the model as project barriers. It offers modularity and flexibility in implementation and can accommodate all the key strategies from diverse sectors along with multiple objectives in the policy optimization process. It enables adoption of an evidence‐based and transparent approach to policy making. The research findings have substantial value for transition management to a sustainable energy framework in developing countries.

This paper aims to present a model of a multi‐phase multi‐product manufacturing system considering a CONstant work‐in‐process (CONWIP) control mechanism and using continuous‐time Markov chain modelling approach.

The model includes defining a state space then constructing the rate matrix, which contains the transition rates, followed by formulating the transition matrix. The time‐dependent probabilities that a product is in a particular state at a certain time are characterized. Performance measures related to the statistics on the waiting time and average number of work‐in‐process in the production system have been determined. Consequently, a numerical example is presented to illustrate the computations of different model aspects.

The analyses explain a foundation needed for analyzing the steady state behavior of manufacturing systems. Results have shown how production data can be easily modified for what‐if analyses by the use of Excel add‐in tool.

The multi‐level model outlines a framework that provides a practical tool for production engineers seeking to enhance the performance of their production system by selecting the best order release mechanism.

A novel aspect of the work reported in this paper is the application of Chapman‐Kolmogrov mathematics and CONWIP ordering theory, which is developed for evaluating and managing CONWIP controlled production systems.

The purpose of this paper is to present a new method and model for constructing a new decision-making paradigm of Medicare, which can not only satisfy the needs of the sick people but also reduce the possibility of people slipping back to poverty due to diseases under the policy of Targeted Poverty Alleviation (TPA) of China.

This paper uses the traditional supply chain theory to analyze the Medicare of impoverished people with the policy of TPA of China and transforms it into a multi-layer supply chain optimization decision-making problem. First, a nonlinear integer programming model for poor people’s Medicare decision with opportunity constraints is constructed. To facilitate the solution of the optimal decision scheme, the abovementioned model is transformed into a linear integer programming model with opportunity constraints by using the Newsvendor model for reference. Meanwhile, the scope of the inventory model is discussed, for it can be combined with the construction of the medical insurance system better. Second, the theoretical model is applied to the practical problem. Finally, based on the results of the theoretical model applying the practical problem, we give further improvement and modification of the theoretical model applies it to the actual situation further.

This paper presents a theoretical model about determine the optimal the inventory, under the framework of traditional supply chain decision-making, for it can be combined with the construction of the medical insurance system better. The theoretical model is applied to the practical problem of the fight against poverty in XX County, China. By using the actual data and MATLAB, optimal decision scheme is obtained.

There are two aspects of value. On the one hand, this paper provides a new way to construct a Medicare system of impoverished people with TPA of China. On the other hand, this paper tries making a new way to handle the storage of medicines and related medical devices at basic standard clinics decision-making problems based on above mentioned Medicare system.