Operating Conditions Of Equipment Research Articles

STOCK PROJECTION MODEL FOR CRITICAL COMPONENTS OF EX5500 EXCAVATORS

ABSTRACT This study provides evidence related to the improvement of the management of the maintenance area as well as the operational efficiency of mining sites, by analyzing a model applied to a real case. The results highlight the benefit of incorporating EBO in the stock projection of critical components of EX5500 hydraulic excavators. In addition, by considering the typical concerns related to the topic, the model was evaluated based on the company’s annual budget restriction. Savings of 557,128 EUR compared to the stock investment of the current company policy (estimated at 5,273,511 EUR) at a service level of 98% and warehouse availability of 95% were found. Furthermore, by using a solver, the projection was optimized and adjusted to the annual budget, increasing the savings to 928,753 EUR, at a service level of 96.4% and warehouse availability of 93.7%. Although the EBO approach has been previously studied within the equipment availability context, the equipment operating conditions were not the same as they vary depending on the area in which they operate. Therefore, it is necessary to provide clear evidence of its effectiveness of application before adopting actions which rely on promising results developed in other contexts. This is even more crucial when dealing with excavators, which are critical, large-scale, capital intensive pieces of equipment. Keywords: EBO; availability, optimization, stock, critical components, mining.

Failure Rate Prediction Model of Substation Equipment Based on Weibull Distribution and Time Series Analysis

The failure rate is an important indicator to assess the reliability of substation equipment, and the failure rate prediction is an effective way to master the operation status of substation equipment. According to the characteristics of failure rate data, such as failure period segmentation and stochastic variation, this paper proposes a combined prediction method by the data decomposition of failure rate time series and the segmentation theory of failure periods and then establishes a new failure rate prediction model of the substation equipment based on the Weibull distribution and time series analysis. Compared with the traditional Weibull distribution function model which cannot describe the stochastic variation of failure rate data and cannot identify the failure period automatically, the proposed model in this paper uses the minimum sum algorithm of residual squares obtained by the Weibull distribution to accurately identify the demarcation point between different failure periods and then establishes the autoregressive moving average (ARMA) model to achieve combined prediction. Finally, the effectiveness of the proposed model is verified by the engineering example and comparison with the traditional failure rate prediction methods.

An improved technique for identification of mathematical model parameters of thermal power equipment and assessment of its performance

The problems of state estimation of thermal power system operation and identification of mathematical model parameters have not been acceptably solved due to the complexity of studied objects and their mathematical models, and the lack of effective methods, algorithms and computer programs to solve the required mathematical problems. The results of solving the indicated problems are of importance as such, and play a great part in the qualitative solution to the problems of thermal power equipment control, e.g., the problems of optimal load dispatch among thermal power plant units and optimal control of thermal power equipment operation conditions. The paper describes a technique improved by the author for identification (adjustment, verification) of mathematical model parameters for complex thermal power equipment. The technique allows us to more effectively detect gross errors in measurements of control parameters used for identification of the mathematical model of the studied equipment, to evaluate correctness and rectify errors in the mathematical model construction, and to improve identification accuracy. An improved technique for identification of mathematical model parameters was tested on a detailed mathematical model of the present-day 225 MW generating unit that was constructed by the author. The paper presents results of solving the identification problem of mathematical model parameters of a generating unit and an example of the optimization calculation of the real operation condition in order to reduce specific fuel consumption for electricity generation. In addition, the paper discusses an issue of assessing the identification accuracy of mathematical model parameters of thermal power equipment that depends on the accuracy of measurements of control parameters used to adjust the model, as well as on the correctness of the mathematical model construction and the calculation technique applied.

Operation optimization research of circulating cooling water system based on superstructure and domain knowledge

Circulating cooling water system (CCWS) is an important auxiliary system in the industrial production process, and it is also one of the main energy-consuming units in the whole process. This paper presents a comprehensive operation optimization method of water and energy, and aims to design an optimal operation plan of the CCWS with improved system operation status and reduced system operation cost. To this end, the operation optimization model based on superstructure method is established, which is comprehensive and practical compared with previous researches in two aspects. Firstly, this model is further extended to realize the comprehensive description and synchronous optimization of network structure, equipment operation mode and equipment operation status, and the optimal operation plan of the system is thus obtained. Secondly, the application range of this model is expanded and thus the proposed method is made more general for various of networks. Moreover, proposed optimization model and the solution algorithm are improved with the fusion of domain knowledge. To be specific, the knowledge of system hydraulic balance and system operation are fused into the operation optimization problem, which improves the energy-saving optimization effect and the algorithm calculation efficiency. Finally, the practicality of the proposed operation optimization method is verified through simulation experiments based on the actual network data, and the comprehensive energy-saving rate reaches 31.3%, so the system operation costs are effectively reduced.

Optimization Method With Prediction-Based Maintenance Strategy for Traction Power Supply Equipment Based on Risk Quantification

A prediction-based maintenance (PBM) strategy can save resources while simultaneously guaranteeing the traction power supply system (TPSS) operates in a stable and reliable condition. Based on risk quantification, this paper presents a method to assess maintenance needs and optimize the PBM strategy for traction power supply equipment (TPSE). This method utilizes historical maintenance information and the fault record of the TPSE as inputs to a fault prediction model based on a Bayesian classifier. By comparing the prediction results with the actual equipment operation state, statistical parameters are obtained to calculate the reliability and economic indices for the maintenance strategies. The comprehensive maintenance risk is then quantified by integrating the dynamic inspection and fault risk costs for the TPSE. The minimum comprehensive risk is selected as the optimization objective, and the criterion for fault prediction spurs from the optimization results are used to form the PBM strategy. Practical maintenance information and fault record data of 27.5-kV vacuum circuit breakers for a TPSS are used to verify the proposed method. The results show that, by fully utilizing the current data, this method can predict equipment faults by considering multiple factors, and it can quantify the risk for a particular PBM strategy, which is also applicable to similar large-scale traction power supply facilities. To improve the PBM strategy, the approach optimizes fault prediction criteria to achieve a minimum comprehensive maintenance risk. The proposed method can provide effective data and confidence for decision makers in implementing PBM for TPSS.

Incipient fault diagnosis of limit switch based on a ARMA model

The limit switch is one of the key components in many pieces of electromechanical equipment. Although the limit switch is cheap and its structure is simple usually, it plays a key role in ensuring good operation condition of electromechanical equipment. Any failure of a limit switch may lead to the complete shutdown of equipment. In this paper, an incipient fault diagnosis method is developed, based on which one can replace the limit switch before its functional failure. In this method, the voltage of the limit switch is monitored and sampled. Then, the feature extraction of the voltage data sequence based on the Auto-Regressive and Moving Average (ARMA) model is performed, and the k-Nearest Neighbor (k-NN) method is used for the feature classification of the voltage data. Finally, the experiment of the incipient fault diagnosis is described and the result is given. The study in this paper may be beneficial for avoiding breakdown of electromechanical equipment due to the functional failure of limit switches.

CHALLENGES IN CLINICAL PRACTICE OF CR MAMMOGRAPHY IN TANZANIA.

The aim of this study was to evaluate the clinical practice of CR mammography in Tanzania. The equipment performance and operational conditions were studied; and mean glandular dose (DG) estimated to 75 women undergoing diagnosis at three mammography facilities. All mammograms during this study were reported to be useful for the intended diagnosis. The median DG for craniocaudal and mediolateral oblique projections ranged from 1.27 ± 0.18 mGy to 1.9 ± 0.27 mGy and from 1.3 ± 0.18 mGy to 1.9 ± 0.27 mGy, respectively, and were below the national regulatory guidance of 2.5 mGy. Despite this positive result, unavoidable inappropriate use of beam quality and tube loading settings which could have been through appropriate staff training and performing routine quality control were not uncommon. This work provides an insight of current operational conditions of CR in Tanzania and what strategy should be employed to this service to improve patient care in the country.

Determining the maximally permissible values for the indicators of insulation of sealed entrance bushings with a voltage of 110 kV using the method of minimal risk

A method for determining the maximally permissible values for the indicators of insulation of high-voltage oilfilled entrance bushings that ensure the minimal risk value has been proposed. The proposed method differs in that the maximally permissible values for indicators are determined by minimizing the function of average risk, using the Newton’s method, taking into consideration the actual operating conditions of equipment, which makes it possible to improve the operational reliability of entrance bushings. We have derived an expression to determine the average risk with respect to the distribution law of indicators for the insulation of high-voltage entrance bushings (by Weibull), the minimization of which makes it possible to determine the maximally permissible values for the indicators, taking into consideration the duration of their operation, the values of load currents, the grade of a transformer oil, and other factors. A comparative analysis was performed for risk values, which are accompanied by applying the maximally permissible values for indicators that are regulated in Ukraine, with the maximally permissible values for indicators, which were obtained by using different methods. The analysis revealed that the minimal risk value is ensured by the maximally permissible values for indicators, which are obtained by applying the method of minimal risk, taking into consideration the operating conditions for entrance bushings. We have performed an analysis of impact of the values for probabilities of the proper-functioning and faulty state of entrance bushings, the cost of incorrect decisions, as well as the value for a scale parameter and a shape parameter in the Weibull distribution, on the maximally permissible values for the indicators of insulation of high-voltage oil-filled entrance bushings in an airtight structure. It was established that an increase in the probability of a defect and its conditional cost, as well as prolonging the operation duration of entrance bushings and their loading, leads to a decrease in the maximally permissible values for the indicators. It has been proven that the maximally permissible values for the indicators of insulation of high-voltage entrance bushings, which ensure the minimal economic loss, are not constant. In order to practically implement the method of minimal risk during operation, it has been proposed to apply the likelihood ratios, which make it possible to diagnose the state of high-voltage entrance bushings at a minimal risk, but without determining the maximally permissible values for the indicators.

Analysis of pin milling of pharmaceutical materials

Milling is an important process for tailoring the particle size distribution for enhanced dissolution, content uniformity, tableting, etc., specially for active pharmaceutical ingredients and excipient in pharmaceutical industries. Milling performance of particulate solids depends on the equipment operating conditions (geometry, process conditions and input energy etc.) as well as material properties (particle size, shape, and mechanical properties, such as Young’s modulus, hardness and fracture toughness). In this work, a newly developed approach to assess the breakability of pharmaceutical materials using an aerodynamic dispersion method has been combined with the Discrete Element Method (DEM) to simulate the dynamic behaviour of a number of pharmaceutical materials in a pin mill. A sensitivity analysis is carried out addressing the effect of the milling conditions (rotational speed of the mill and feed particle flow rate) and feed properties on the milled products in terms of the shift in the specific surface area of the milled particles. The outcome of the work is used as a method to predict the breakage of the particles for the milling conditions where chipping takes place.

Design of single mixed refrigerant natural gas liquefaction process considering load variation

This study presents a comprehensive design approach to determine optimal equipment size and operating conditions while considering process load variation. We applied the suggested approach to PRICO® Single Mixed Refrigerant (SMR) process to take account of the feed gas load reduction owing to depletion of natural gas fields. The suggested approach differs from a traditional one in that it performs design and optimization with several steady-state operation regimes depending on the load variation. The economics of each design approach is evaluated by the economic assessment model that reflects the annual profit under the varying production rate according to the actual production profiles of the gas field wells, Maui and Kapuni in New Zealand. The proposed design approach makes a loss in the compressor equipment cost. However, it reduces the operation cost over a wide range of operations, leading to the overall improvement of economics in a gas well along its lifetime production. This study also conducts a quantitative analysis between the load capacity that a single train must bear and the key economic variables through a case study on two-train operation. This provides insight into the economics and operability of the process depending on the number of trains.

Preventive remanufacturing planning of production equipment under operational and imperfect maintenance constraints: A hybrid genetic algorithm based approach

Remanufacturing an equipment before the end of its life may generate substantial profits for both the user and the remanufacturer. However, the equipment operating conditions as well as the quality of maintenance actions undergone throughout the life of equipment largely affect the total life cycle costs from the user’s perspective, and the quality of the recovered equipment from the remanufacturer’s perspective. This research aims at investigating the remanufacturing opportunities of production equipment from the user’s perspective, used to produce a single product in order to meet deterministic and dynamic demands over a finite horizon. Preventive maintenance actions on equipment are assumed to be imperfect. Indeed, when performed, these actions can improve the equipment to reach a state between the “As-good-as-new” level and the “As-bad-as-old” level. It is assumed that the stakeholders (the equipment’s user and the original equipment manufacturer-remanufacturer) are interested by all remanufacturing opportunities. The objective of the present work is to develop an integrated approach to jointly optimize the production plan, the remanufacturing plan and the quality of spare parts used in each remanufacturing action.In order to minimize the total cost during the production horizon, a mixed-integer nonlinear program is developed. The optimization problem is solved using a hybrid genetic algorithm based on a fix-and-relax heuristic. A numerical experiment and a sensitivity analysis are presented to illustrate the applicability of the proposed approach.

Surface charge accumulation on 500kV cone-type GIS spacer under residual DC voltage

In recent years, GIS compact design has gradually been recognized and adopted by the industry. In the trend of the compact design, the insulation performance of the cone-type spacer is getting more and more attention by GIS manufacturers and grid operators and maintenance departments. In particular, under the action of DC residual pressure, the insulation properties of cone-type spacer become the focus of attention of all parties. Based on the field equipment operating conditions, the experimental study of DC residual voltage for the true cone-type spacer insulation performance is significant. In order to obtain the proposed pre-stressed time of DC voltage and distributions of surface charge, for the insulation test of 500 kV cone-type spacer under lightning impulse with DC voltage superimposed. A full scale surface charge measurement platform is build up for 500 kV GIS spacer. Then, long-term DC voltage experiments were carried out to obtain the distributions of surface charge on spacer in stationary state under different voltages. Moreover, the saturation time of surface charge accumulation under different DC electric stress is calculated and discussed. The study results show that (1) the distribution of surface charge on spacer is not uniform. It can be observed that on most areas of 500 kV spacer concave surface is dominated by the electric conduction through the volume with positive charges. (2) The time constant of surface charge accumulation decreases with the residual DC voltage amplitude, it can be estimated that the saturation time of surface charge accumulation on 500 kV cone-type spacer is about 23 h for the residual DC voltage reach to 1.0 p.u. The study results are thought to be helpful to the insulation test of 500 kV conetype spacer under impulse voltage with a superimposed residual DC voltage.

A simplified power consumption model of information technology (IT) equipment in data centers for energy system real-time dynamic simulation

Due to the rapid rise of power consumption of data centers in recent years, much work has been done to develop energy-efficient design, controls and diagnosis of their cooling systems, while the energy system simulation is used as an effective tool. However, existing models of information technology (IT) equipment of data centers cannot well represent the effects of IT equipment design and operation status on the data center cooling demand, and this hinders the development of the energy saving cooling technologies of data centers. To address this issue, this paper introduces a power consumption model of IT equipment in data centers with coefficients and modeling script provided for immediate use in data center energy system simulation. This energy model can be used to simulate energy performance of typical IT equipment in data centers under real-time dynamic operation conditions conveniently and effectively without the need of data other than the specifications of a data center design and IT equipment manuals. Its use with a commonly used building simulation program is demonstrated with a building model of a typical large office in a subtropical area. The results show that the model can represent the change of power consumption of data centers with different IT equipment designs and operation appropriately.

Total productive maintenance

Total Productive Maintenance (TPM) is a holistic approach to equipment maintenance that strives to achieve near perfect production processes. Autonomous maintenance is the process where operators are involved in maintaining their own equipment while emphasising proactive and preventative maintenance. Improved processes and continuous improvement are key fundamentals of TPM. The TPM process ensures fewer breakdowns, stops, and defects while also lowering costs and engaging employees from C-level on down. Effective communication techniques and top management support help the functionality of TPM. TPM improves equipment operating conditions, enables the achievement of Takt time at the highest possible machine effectiveness, and sustains equipment at an optima level of performance and reliability. TPM also lengthens the life expectancy of equipment, reduces or eliminates breakdowns, eliminates slow running or small stoppages, and aims for zero defects and zero accidents while engaging operators to be 100% involved and committed. This article provides an overview, introduction, and implementation guide to TPM.

The effect of energy accumulation and boundary slip on laminar flow between rotating plates

The poor operating conditions of fluid lubrication equipment during the start-up process are due to the resistance of the high-viscosity lubricating liquid. Moreover, the excessive reduction in fluid viscosity due to the elevated temperature resulting from power consumption during prolonged operation is not conducive to the generation of dynamic pressure. In this study, we examine the effect of energy accumulation and boundary slip on the laminar flow of a liquid between a pair of rotating plates. The experiments are conducted using a rotary rheometer, with polymethyl methacrylate (PMMA) as the thermal insulation material and polytetrafluoroethylene (PTFE) as the slip drag reduction material, and a three-dimensional simulation model is established. This model is derived by combining the energy equation including the slip length and the heat conduction equation. Thus, the temperature changes over time are predicted by this model, and the model accuracy is verified by experiments. The results reveal the following points: 1) boundary slips function as a drag reduction mechanism for short-time continuous operation; 2) under prolonged operation, the slip reduces the extent of the oil viscosity decrease and clear control of the elevated temperature by the boundary slip is observed.

An Autonomous Wireless Sensor Network in a Substation Area Using Wireless Transfer of Energy

A smarter power grid can improve the maintenance system by providing a real-time measurement of equipment operating conditions. Such a monitoring system requires the deployment of an increased number of sensors. However, the wiring sensors in a high voltage environment such as power substation is a very expensive procedure. An autonomous wireless sensor network can reduce the installation cost and make sensors more viable throughout the network. In this paper, we study the possibility of deploying an autonomous wireless sensor network in a substation environment. To this end, we merge energy harvesting and wireless transfer of energy to propose a hierarchical energy harvesting model. In this paper, we show that despite of the wasteful nature of the wireless transfer of energy and with an efficiency not more than what existing technologies can provide, a self-sustainable wireless sensor network in a substation area can be accomplished.

Thermodynamic analysis of air-compression refrigerating machine based on the exergy cost theory

On the basis of the exergy cost theory, a procedure has been developed for carrying out an in-depth thermodynamic analysis of air-compression refrigerating machines and thermal pumps taking into consideration nonequivalence of exergy losses in various links of thermotransformation process and their effect on consumption of exergy supplied to the system. A thermoeconomic model of a single-stage air-compression refrigerating machine was proposed which takes into consideration structural and topological features of the process scheme and interrelation between its elements. For an equivalent mapping of structural and topological features of the refrigerating machine scheme, a parametric flow graph was developed. The procedure uses a matrix form of recording exergy balances which is the most convenient for representation of the thermoeconomic models. In order to obtain reference operating mode of the refrigerating machine, the principle of thermodynamic process idealizing was used. Application of the structural theory of thermoeconomics has made it possible to establish the portion of endogenous and exogenous destruction of exergy in the elements of the refrigerating machine. Numerical implementation of the proposed procedure has made it possible to reveal influence of internal irreversibility in the cycle determined by non-isentropic compression processes in the compressor and expansion in the expander. A significant effect of efficiency of the expansion process in the expander on the exergy efficiency of the air-compression refrigerating machine was established. Influence of the change of ambient temperature on the character of consumption of exergy by each element of the refrigeration machine was estimated. It has been revealed that even a slight change of the ambient temperature significantly affects consumption of “fuel” by each element of the system, while the dependence is linear. Generalized dependences of exergy indicators on variable factors have been obtained which enabled finding of unfavorable operating conditions for equipment with increased energy consumption. It was established that the efficiency factor of the turboexpander has the greatest influence on the change of consumption of exergy of “fuel” in the system.

Computational Investigation of Thermal Stress-Strain Behavior and Individual Service Life of the Boiler Pipeline

The issues of record-keeping of the damages caused by the impact of high local gas temperatures and local temperature inhomogeneity and the reliable estimate of the remaining life of high temperature elements are topical and their solution will provide a reliable and long-term operation for power generating equipment. Using the data of numerous investigations of thermal state, stress-strain state and the remaining life of boiler pipelines we developed and substantiated the methods of calculated estimate of the effects of the local inhomogeneity of thermal flows on the damageability and remaining life of the elements to extend the operation life of power equipment. Based on the operation data of industrial power equipment and the data of physical experiments appropriate initial and boundary conditions were selected that enabled an adequate simulation of the influence of the irregular temperature fields of combustion products. Using the Solid Works bundled software we carried out computational investigations that take into account the gas dynamics of the behavior of gas flow streamlining the pipeline. Thermal and stress-strain states were defined and service life of the boiler unit pipeline was determined depending on equipment operation conditions. The obtained research data can be used for high and low power engineering, industry and gas transportation system of Ukraine and other fields of science and engineering to operate equipment elements at high temperatures and high local temperature gradients when the burners of a stabilizing type equipped with the gas temperature field shape control system are used.

Method of Data storing, collection and aggregation for definition of life-cycle resources of electromechanical equipment

Analysis of technical and technological conditions for the emergence of emergency situations during the operation of electromechanical equipment of enterprises of the mineral and raw materials complex shows that when developing the basis for ensuring safe operation, it is necessary to take into account not only the technical condition, but also the non-stationary operation of the operating conditions of equipment, and the nonstationarity of operational operating parameters of technological processes. Violations of the operation of individual parts of the machine, not detected in time, can lead to severe accidents at work, as well as to unplanned downtime and loss of profits. That is why, the issues of obtaining and processing Big data obtained during the life cycle of electromechanical equipment, for assessing the current state of the electromechanical equipment used, timely diagnostics of emergency and pre-emergency modes of its operation, estimating the residual resource, as well as prediction the technical state on the basis of machine learning are very important. This article is dedicated to developing the special method of data storing, collection and aggregation for definition of life-cycle resources of electromechanical equipment. This method can be used in working with big data and can allow extracting the knowledge from different data types: the plants’ historical data and the factory historical data. The data of the plants contains the information about electromechanical equipment operation and the data of the factory contains the information about a production of electromechanical equipment.

Impact of fuel on real diesel injector performance in field test

This work assessed the potential impact of diesel fuel complying with the EN 590 standard on real diesel injector performance in a long-term field test. Injector deposit formation has been attributed to diesel fuel instability during storage in relation to fuel injection equipment (FIE) operating conditions. These deposits can occur at different locations within FIE and impact on fuel spray characteristics, causing threats to the proper functioning of the fuel injectors. The long-term field tests were performed with two new vehicles fitted with an advanced common rail (CR) fuel injection system, meeting the requirements of Euro 5. A high quality diesel fuel meeting the requirements of the EN 590 standard was used for both vehicles. A scanning electron microscope with energy dispersive X-ray spectrometry (EDS) and an electron backscatter diffraction (EBSD) detector was used for observation and imaging of external, coking injector deposits around the nozzle fuel-flow holes and internal diesel injector deposits (IDID) in the area of the nozzle needle. An elemental analysis was performed by energy dispersive X-ray spectroscopy analysis (EDX). Evaluation of the macroscopic characteristics revealed that, despite the formation of external and internal injector deposits, there was no measurable loss of flow through the injectors. As a result, while injector deposits have adverse impacts on some injector macroscopic characteristics, they did not cause a significant deterioration of the injectors’ operating characteristic and their real performance.