Secure and cost-effective power generation has become very important nowdays. Care must be taken while designing and operating modern steam power plants. There are regulations such as German boiler regulations (Technische Regeln für Dampfkessel 301) or European Standards that guide the user how to operate the steam power plants. However, those regulations are based on the quasi-steady state assumption and one dimensional temperature distribution in the entire element. This simplifications may not guarantee that the heating and cooling operations are conducted in the most efficient way. Thus, it was important to find an improved method that can allow to establish optimum parameters for heating and cooling operations. The optimum parameters should guarantee that the maximum total stresses in the construction element are in the allowable limits and the entire process is conducted in the shortest time. This paper summarizes mathematical descriptions how to optimize shut down process of power block devices. The optimization formulation is based on the assumption that the maximum total stresses in the whole construction element should be kept within allowable limits during cooling operation. Additionally, the operation should be processed in the shortest time possible.
One of the major concerns of the power energy industries is a proper operation of steam power blocks. Pressurized working medium and high temperature cause very high stresses in the construction elements such as collectors, separators or steam valves. They are exposed to sudden temperature and pressure changes that cause high stresses at certain points. Additionally, the cyclic character of loading causes material fatigue, known as low-cyclic fatigue, which may lead to the formation of fracture. Thus, methodologies offered by many companies should ensure reliable and safe operation of steam power blocks. The advanced numerical solutions for determining time-optimum medium temperature changes are presented. They are based on Levenberg-Marquardt and nonlinear programming by quadratic Lagrangian methods. The methods allow us to find parameters for start-up and shut-down operation that can reduce total stresses to limits governed by European regulations. Furthermore, the heating and cooling operations are conducted in a shortest time possible.
Modern supercritical power plants operate at very high temperatures and pressures. Thus the construction elements are subjected to both high thermal and mechanical loads. As a result high stresses in those components are created. In order to operate safely, it is important to monitor stresses, especially during start-up and shut-down processes. The maximum stresses in the construction elements should not exceed the allowable stresses that are defined according to boiler regulations. It is important to find optimum operating parameters, that can assure safe heating and cooling processes. The optimum parameters define temperature and pressure histories that can keep the highest stresses within allowable limit and reduce operation time as much as possible. In this paper a new numerical method for determining optimum working fluid parameters is presented. In this method, properties of steel can be assumed as constant or temperature dependent. The constant value is taken usually at the average temperature of the operation cycle. For both cases optimal parameters are determined. Based on these parameters start-up operations for both cases are conducted. During entire processes stresses in the heated element are monitored. The results obtained are compared with German boiler regulations - Technische Regeln fur Dampfkessel 301.
Construction elements of supercritical power plants are subjected to high working pressures and high temperatures while operating. Under these conditions high stresses in the construction are created. In order to operate safely, it is important to monitor stresses, especially during start-up and shut-down processes. The maximum stresses in the construction elements should not exceed the allowable stress limit. The goal is to find optimum operating parameters that can assure safe heating and cooling processes [1-5]. The optimum parameters should guarantee that the allowable stresses are not exceeded and the entire process is conducted in the shortest time. In this work new numerical method for determining optimum working parameters is presented. Based on these parameters heating operations were conducted. Stresses were monitored during the entire processes. The results obtained were compared with the German boiler regulations - Technische Regeln für Dampfkessel 301.
The paper presents a novel Iterated Local Search (ILS) algorithm to solve multi-item multi-family capacitated lot-sizing problem with setup costs independent of the family sequence. The model has a direct application to real production planning in foundry industry, where the goal is to create the batches of manufactured castings and the sequence of the melted metal loads to prevent delays in delivery of goods to clients. We extended existing models by introducing minimal utilization of furnace capacity during preparing melted alloy. We developed simple and fast ILS algorithm with problem-specific operators that are responsible for the local search procedure. The computational experiments on ten instances of the problem showed that the presence of minimum furnace utilization constraint has great impact on economic and technological conditions of castings production. For all test instances the proposed heuristic is able to provide the results that are comparable to state-of-the art commercial solver.
The problem considered in the paper is motivated by production planning in a foundry equipped with the furnace and casting line, which provides a variety of castings in various grades of cast iron/steel for a large number of customers. The quantity of molten metal does not exceed the capacity of the furnace, the load is a particular type of metal from which the products are made in the automatic casting lines. The goal is to create the order of the melted metal loads to prevent delays in delivery of goods to customers. This problem is generally considered as a lot-sizing and scheduling problem. The paper describes two computational intelligence algorithms for simultaneous grouping and scheduling tasks and presents the results achieved by these algorithms for example test problems.
In the paper, we present a coordinated production planning and scheduling problem for three major shops in a typical alloy casting foundry, i.e. a melting shop, molding shop with automatic line and a core shop. The castings, prepared from different metal, have different weight and different number of cores. Although core preparation does not required as strict coordination with molding plan as metal preparation in furnaces, some cores may have limited shelf life, depending on the material used, or at least it is usually not the best organizational practice to prepare them long in advance. Core shop have limited capacity, so the cores for castings that require multiple cores should be prepared earlier. We present a mixed integer programming model for the coordinated production planning and scheduling problem of the shops. Then we propose a simple Lagrangian relaxation heuristic and evolutionary based heuristic to solve the coordinated problem. The applicability of the proposed solution in industrial practice is verified on large instances of the problem with the data simulating actual production parameters in one of the medium size foundry.
Mathematical programming, constraint programming and computational intelligence techniques, presented in the literature in the field of operations research and production management, are generally inadequate for planning real-life production process. These methods are in fact dedicated to solving the standard problems such as shop floor scheduling or lot-sizing, or their simple combinations such as scheduling with batching. Whereas many real-world production planning problems require the simultaneous solution of several problems (in addition to task scheduling and lot-sizing, the problems such as cutting, workforce scheduling, packing and transport issues), including the problems that are difficult to structure. The article presents examples and classification of production planning and scheduling systems in the foundry industry described in the literature, and also outlines the possible development directions of models and algorithms used in such systems.
The article presents a study on the effectiveness of the foundries using Data Envelopment Analysis (DEA) method. The aim of the article is to analyze the usefulness of DEA method in the study of the relative efficiency of the foundries. DEA is a benchmarking technique based on linear programming to evaluate the effectiveness of the analyzed objects. The research was conducted in four Polish and two foreign plants. Evaluated foundries work in similar markets and have similar production technology. We created a DEA model with two inputs (fixed assets and employment) and one output (operating profit). The model was produced and solved using Microsoft Excel together with its Solver add-in. Moreover, we wrote a short VBA script to perform automating calculations. The results of our study include a benchmark and foundries’ ranking, and directions to improve the efficiency of inefficient units. Our research has shown that DEA can be a very valuable method for evaluating the efficiency of foundries.
A novel approach for treating the uncertainty about the real levels of finished products during production planning and scheduling process is presented in the paper. Interval arithmetic is used to describe uncertainty concerning the production that was planned to cover potential defective products, but meets customer’s quality requirement and can be delivered as fully valuable products. Interval lot sizing and scheduling model to solve this problem is proposed, then a dedicated version of genetic algorithm that is able to deal with interval arithmetic is used to solve the test problems taken from a real-world example described in the literature. The achieved results are compared with a standard approach in which no uncertainty about real production of valuable castings is considered. It has been shown that interval arithmetic can be a valuable method for modeling uncertainty, and proposed approach can provide more accurate information to the planners allowing them to take more tailored decisions.
The problem considered in the paper is motivated by production planning in a foundry equipped with a furnace and a casting line, which provides a variety of castings in various grades of cast iron/steel for a large number of customers. The goal is to create the order of the melted metal loads to prevent delays in delivery of goods to customers. This problem is generally considered as a lot-sizing and scheduling problem. However, contrary to the classic approach, we assumed the fuzzy nature of the demand set for a given day. The paper describes a genetic algorithm adapted to take into account the fuzzy parameters of simultaneous grouping and scheduling tasks and presents the results achieved by the algorithm for example test problem.
In this paper, the influence of impact damage to the induction motors on the zero-sequence voltage and its spectrum is presented. The signals detecting the damages result from a detailed analysis of the formula describing this voltage component which is induced in the stator windings due to core magnetic saturation and the discrete displacement of windings. Its course is affected by the operation of both the stator and the rotor. Other fault detection methods, are known and widely applied by analysing the spectrum of stator currents. The presented method may be a complement to other methods because of the ease of measurements of the zero voltage for star connected motors. Additionally, for converter fed motors the zero sequence voltage eliminates higher time harmonics displaced by 120 degrees. The results of the method application are presented through measurements and explained by the use of a mathematical model of the slip-ring induction motor.
The paper presents a production scheduling problem in a foundry equipped with two furnaces and one casting line, where the line is a bottleneck and furnaces, of the same capacity, work in parallel. The amount of produced castings may not exceed the capacity of the line and the furnaces, and their loads determine metal type from which the products are manufactured on the casting line. The purpose of planning is to create the processing order of metal production to prevent delays in the delivery of the ordered products to the customers. The problem is a mix of a lot-sizing and scheduling problems on two machines (the furnaces) run in parallel. The article gives a mathematical model that defines the optimization problem, and its relaxed version based on the concept of a rolling-horizon planning. The proposed approaches, i.e. commercial solver and Iterated Local Search (ILS) heuristic, were tested on a sample data and different problem sizes. The tests have shown that rolling horizon approach gives the best results for most problems, however, developed ILS algorithm gives better results for the largest problem instances with tight furnace capacity.
In this paper it is shown that M class PMU (Phasor Measurement Unit) reference model for phasor estimation recommended by the IEEE Standard C37.118.1 with the Amendment 1 is not compliant with the Standard. The reference filter preserves only the limits for TVE (total vector error), and exceeds FE (frequency error) and RFE (rate of frequency error) limits. As a remedy we propose new filters for phasor estimation for M class PMU that are fully compliant with the Standard requirements. The proposed filters are designed: 1) by the window method; 2) as flat-top windows; or as 3) optimal min-max filters. The results for all Standard compliance tests are presented, confirming good performance of the proposed filters. The proposed filters are fixed at the nominal frequency, i.e. frequency tracking and adaptive filter tuning are not required, therefore they are well suited for application in lowcost popular PMUs.
The problem considered in the paper is motivated by production planning in a foundry equipped with the furnace and casting line, which provides a variety of castings in various grades of cast iron/steel for a large number of customers. The quantity of molten metal does not exceed the capacity of the furnace, the load is a particular type of metal from which the products are made. The goal is to create the order of the melted metal loads to prevent delays in delivery of goods to customers. This problem is generally considered as a lot-sizing and scheduling problem. The paper describes a mathematical programming model that formally defines the optimization problem and its relaxed version that is based on the conception of rolling-horizon planning
The size and complexity of decision problems in production systems and their impact on the economic results of companies make it necessary to develop new methods of solving these problems. One of the latest methods of decision support is business rules management. This approach can be used for the quantitative and qualitative decision, among them to production management. Our study has shown that the concept of business rules BR can play at most a supporting role in manufacturing management, but alone cannot form a complete solution for production management in foundries.
Modern production technology requires new ways of surface examination and a special kind of surface profile parameters. Industrial quality inspection needs to be fast, reliable and inexpensive. In this paper it is shown how stochastic surface examination and its proper parameters could be a solution for many industrial problems not necessarily related with smoothing out a manufactured surface. Burnishing is a modern technology widely used in aircraft and automotive industries to the products as well as to process tools. It gives to the machined surface high smoothness, and good fatigue and wear resistance. Every burnished material behaves in a different manner. Process conditions strongly influence the final properties of any specific product. Optimum burnishing conditions should be preserved for any manufactured product. In this paper we deal with samples made of conventional tool steel – Sverker 21 (X153CrMoV12) and powder metallurgy (P/M) tool steel – Vanadis 6. Complete investigations of product properties are impossible to perform (because of constraints related to their cost, time, or lack of suitable equipment). Looking for a global, all-embracing quality indicator it was found that the correlation function and the frequency analysis of burnished surface give useful information for controlling the manufacturing process and evaluating the product quality. We propose three new indicators of burnishing surface quality. Their properties and usefulness are verified with the laboratory measurement of material samples made of the two mentioned kinds of tool steel.
Clinker burning process has a decisive influence on energy consumption and the cost of cement production. A new problem is to use the process of decarbonization of alternative fuels from waste. These issues are particularly important in the introduction of a two-stage combustion of fuel in a rotary kiln without the typical reactor-decarbonizator. This work presents results of numerical studies on thermal-hydraulic phenomena in the riser chamber, which will be designed to burn fuel in the system where combustion air is supplied separately from the clinker cooler. The mathematical model is based on a combination of two methods of motion description: Euler description for the gas phase and Lagrange description for particles. Heat transfer between particles of raw material and gas was added to the numerical calculations. The main aim of the research was finding the correct fractional distribution of particles. For assumed particle distribution on the first stage of work, authors noted that all particles were carried away by the upper outlet to the preheater tower, what is not corresponding to the results of experimental studies. The obtained results of calculations can be the basis for further optimization of the design and operating conditions in the riser chamber with the implementation of the system.
The requirements for environmentally friendly refrigerants promote application of CO2and water as working fluids. However there are two problems related to that, namely high temperature limit for CO2in condenser due to the low critical temperature, and low temperature limit for water being the result of high triple point temperature. This can be avoided by application of the hybrid adsorption-compression system, where water is the working fluid in the adsorption high temperature cycle used to cool down the CO2compression cycle condenser. The adsorption process is powered with a low temperature renewable heat source as solar collectors or other waste heat source. The refrigeration system integrating adsorption and compression system has been designed and constructed in the Laboratory of Thermodynamics and Thermal Machine Measurements of Cracow University of Technology. The heat source for adsorption system consists of 16 tube tulbular collectors. The CO2compression low temperature cycle is based on two parallel compressors with frequency inverter. Energy efficiency and TEWI of this hybrid system is quite promising in comparison with the compression only systems.