Large Industrial Systems Research Articles

Agricultural application of life cycle iNdeX (LInX) for effective decision making

Mechanisms for evaluating system sustainability should allow for the consideration of three main parameters: social, economic and environmental. While, there are methods for comparing processes, projects or systems on the basis of environmental impact or cost, few incorporate all three parameters into the decision process. Life cycle index (LInX) is an indexing system that is meant to simplify the decision making process by incorporating a life cycle based approach with components of sustainability and safety. Although LInX was designed for large industrial systems, this paper presents the application on a small anaerobic digestion (AD) unit on a dairy farm in Clymer, New York. An AD unit can be used to generate electricity from the combustion of biogas produced from organic waste. From the analysis, the AD unit performed well on environmental and cost parameters, but not as well on risk and social parameters. However, the AD unit performed similar to natural gas and biomass-based production. One recommendation for the method is that consideration be given to modifying parameters and weightings to suit agriculture and location specific needs.

Methods for finding frequent items in data streams

The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in data stream mining, dating back to the 1980s. Many applications rely directly or indirectly on finding the frequent items, and implementations are in use in large scale industrial systems. However, there has not been much comparison of the different methods under uniform experimental conditions. It is common to find papers touching on this topic in which important related work is mischaracterized, overlooked, or reinvented. In this paper, we aim to present the most important algorithms for this problem in a common framework. We have created baseline implementations of the algorithms and used these to perform a thorough experimental study of their properties. We give empirical evidence that there is considerable variation in the performance of frequent items algorithms. The best methods can be implemented to find frequent items with high accuracy using only tens of kilobytes of memory, at rates of millions of items per second on cheap modern hardware.

Comparing the effectiveness of several modeling methods for fault prediction

We compare the effectiveness of four modeling methods--negative binomial regression, recursive partitioning, random forests and Bayesian additive regression trees--for predicting the files likely to contain the most faults for 28 to 35 releases of three large industrial software systems. Predictor variables included lines of code, file age, faults in the previous release, changes in the previous two releases, and programming language. To compare the effectiveness of the different models, we use two metrics--the percent of faults contained in the top 20% of files identified by the model, and a new, more general metric, the fault-percentile-average. The negative binomial regression and random forests models performed significantly better than recursive partitioning and Bayesian additive regression trees, as assessed by either of the metrics. For each of the three systems, the negative binomial and random forests models identified 20% of the files in each release that contained an average of 76% to 94% of the faults.

New Technologies in Ammonia Refrigerating and Air-Conditioning Systems

This review paper describes a brief historic perspective of transition from natural refrigerants to synthetic and now back to natural refrigerants. The thermodynamic, physical and safety properties of ammonia are presented. The advantages and disadvantages of ammonia refrigerant are discussed. The heat exchanger technology has seen introduction of compact and efficient equipment both in shell and tube and plate technologies. The micro-channel exchangers are being introduced in the automotive industry and it could soon enter into the commercial and industrial refrigeration markets. Compact heat exchangers are of interest due to their low refrigerant inventory features. A new electromotor technology is being developed now, using encapsulated copper windings or aluminum windings for semi-hermetic ammonia compressors. A hermetic scroll compressor for ammonia small refrigerating systems is also in the offing. In the last several years large numbers of air conditioning systems with ammonia chillers have been installed in commercial and public facilities. In large industrial systems where there is a need for low evaporating temperatures, Ammonia/Carbon Dioxide cascade systems are being proposed and installed.

Constrained Balancing of Two Industrial Rotor Systems: Least Squares and Min-Max Approaches

Rotor vibrations caused by rotor mass unbalance distributions are a major source of maintenance problems in high-speed rotating machinery. Minimizing this vibration by balancing under practical constraints is quite important to industry. This paper considers balancing of two large industrial rotor systems by constrained least squares and min-max balancing methods. In current industrial practice, the weighted least squares method has been utilized to minimize rotor vibrations for many years. One of its disadvantages is that it cannot guarantee that the maximum value of vibration is below a specified value. To achieve better balancing performance, the min-max balancing method utilizing the Second Order Cone Programming (SOCP) with the maximum correction weight constraint, the maximum residual response constraint as well as the weight splitting constraint has been utilized for effective balancing. The min-max balancing method can guarantee a maximum residual vibration value below an optimum value and is shown by simulation to significantly outperform the weighted least squares method.

Constrained balancing of two industrial rotor systems: Least squares and min-max approaches

Rotor vibrations caused by rotor mass unbalance distributions are a major source of maintenance problems in high- speed rotating machinery. Minimizing this vibration by balancing under practical constraints is quite important to industry. This paper considers balancing of two large industrial rotor systems by constrained least squares and min-max balancing methods. In current industrial practice, the weighted least squares method has been utilized to minimize rotor vibrations for many years. One of its disadvantages is that it cannot guarantee that the maximum value of vibration is below a specified value. To achieve better balancing performance, the min-max balancing method utilizing the Second Order Cone Programming (SOCP) with the maximum correction weight constraint, the maximum residual response constraint as well as the weight splitting constraint has been utilized for effective balancing. The min-max balancing method can guarantee a maximum residual vibration value below an optimum value and is shown by simulation to significantly outperform the weighted least squares method.

New Control System Aspects for Supporting Complex Data and High Performance System

The data in automation and control systems can be achieved not only from different field devices but also from different OPC (OLE for Process Control) servers. However, current OPC clients can only read and decode the simple data from OPC servers. They will have some problems to acquire structured data and exchange the structured data. In addition to the large network control systems, the OPC clients can read, write, and subscribe to thousands of data points from/to OPC servers. Due to that, the most important factor for building a high performance and scalable industrial control system is the ability to transfer the process data between server and client in the most efficient and fastest way. In order to solve these problems, we propose a means to implement the OPC DA (Data Access) server supporting the OPC complex data, so that the OPC DA clients are able to read and decode any type of data from OPC servers. We also propose a method for caching the process data in large industrial control systems to overcome the limitation of performance of the pure OPC DA system. The performance analysis and discussion indicate that the proposed system has an acceptable performance and is feasible in order for applying to real-time industrial systems today.

Optimization of solar water heating systems through water replenishment

In a typical solar water heating system, cold water is replenished into the storage tank as soon as the load is served. However, it is possible to determine the water replenishment profile (i.e., the quantity of the cold makeup water to be supplied to the storage tank over a day) that optimizes the overall system. In this paper, the effect of water replenishment on the system sizing is studied and a novel strategy for water replenishment is proposed to improve the design and performance of solar water heating systems. Based on an analytical technique, an approximate water replenishment profile is proposed to size a solar water heating system near-optimally. The problem is analyzed using a methodology called design space approach. Design space of a solar water heating system identifies all possible and feasible designs on a collector area vs. storage volume diagram. For illustration of the proposed methodology, an example problem is solved. It is observed that the annualized system cost can be reduced by 13.7%. For the cost-optimal system configuration, a reduction of 12.7% in the collector area and 10.2% reduction in the storage volume are observed. The proposed methodology is particularly important and advantageous for large commercial and industrial solar water heating systems.

Finding frequent items in data streams

The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in data stream mining, dating back to the 1980s. Many applications rely directly or indirectly on finding the frequent items, and implementations are in use in large scale industrial systems. However, there has not been much comparison of the different methods under uniform experimental conditions. It is common to find papers touching on this topic in which important related work is mischaracterized, overlooked, or reinvented. In this paper, we aim to present the most important algorithms for this problem in a common framework. We have created baseline implementations of the algorithms, and used these to perform a thorough experimental study of their properties. We give empirical evidence that there is considerable variation in the performance of frequent items algorithms. The best methods can be implemented to find frequent items with high accuracy using only tens of kilobytes of memory, at rates of millions of items per second on cheap modern hardware.

Dynamic compensation of an rf cavity failure in a superconducting linac

An accelerator driven system (ADS) for transmutation of nuclear waste typically requires a 600 MeV--1 GeV accelerator delivering a proton flux of a few mA for demonstrators, and of a few tens of mA for large industrial systems. Such a machine belongs to the category of the high-power proton accelerators, with an additional requirement for exceptional ``reliability'': because of the induced thermal stress to the subcritical core, the number of unwanted ``beam trips'' should not exceed a few per year, a specification that is several orders of magnitude above usual performance. In order to meet this extremely high reliability, the accelerator needs to implement, to the maximum possible extent, a fault-tolerance strategy that would allow beam operation in the presence of most of the envisaged faults that could occur in its beam line components, and in particular rf systems' failures. This document describes the results of the simulations performed for the analysis of the fault-tolerance capability of the XT-ADS superconducting linac in the case of an rf cavity failure. A new simulation tool, mixing transient rf behavior of the accelerating cavities with full 6D description of the beam dynamics, has been developed for this purpose. Fast fault-recovery scenarios are proposed, and required research and development is identified.

Bacillus Spore Inactivation Differences after Combined Mild Temperature and High Pressure Processing Using Two Pressurizing Fluids

Spores of six species (28 strains) of dairy Bacillus isolates were added to sterile reconstituted skim milk and pressure processed (600 MPa for 60 s at 75°C) using either a water-based pressurizing fluid or silicon oil. Processing temperatures peaked at 88 and 90°C, respectively, for both fluids. For all strains, the log inactivation was consistently higher in the silicon oil than in the water-based fluid. This has potential implications for food safety assessment of combined pressure-temperature processes. High pressure processing causes mild heating during pressurization of both the target sample (i.e., spores) and the pressurizing fluid used for pressure delivery. Primarily, the adiabatic heat of compression of the fluids as well as other heat-transfer properties of the fluids and equipment determines the magnitude of this heating. Pressure cycles run with silicon oil were 7 to 15°C higher in temperature during pressurization than pressure cycles run with the water-based pressurizing fluid, due to the greater adiabatic heat of compression of silicon oil. At and around the target pressure, however, the temperatures of both pressurizing fluids were similar, and they both dropped at the same rate during the holding time at the target pressure. We propose that the increased spore inactivation in the silicon oil system can be attributed to additional heating of the spore preparation when pressurized in oil. This could be explained by the temperature difference between the silicon oil and the aqueous spore preparation established during the pressurization phase of the pressure cycle. These spore-inactivation differences have practical implications because it is common practice to develop inactivation kinetic data on small, jacketed laboratory systems pressurized in oil, with extensive heat loss. However, commercial deployment is invariably on large industrial systems pressurized in water, with limited heat loss. Such effects should be considered in food safety assessments of combined pressure-temperature processes.

Using communication coverage criteria and partial model generation to assist software integration testing

This paper considers the problem of integration testing the components of a timed distributed software system. We assume that communication between the components is specified using timed interface automata and use computational tree logic (CTL) to define communication-based coverage criteria that refer to send- and receive-statements and communication paths. The proposed method enables testers to focus during component integration on such parts of the specification, e.g. behaviour specifications or Markovian usage models, that are involved in the communication between components to be integrated. A more specific application area of this approach is the integration of test-models, e.g. a transmission gear can be tested based on separated models for the driver behaviour, the engine condition, and the mechanical and hydraulical transmission states. Given such a state-based specification of a distributed system and a concrete coverage goal, a model checker is used in order to determine the coverage or generate test sequences that achieve the goal. Given the generated test sequences we derive a partial test-model of the components from which the test sequences were derived. The partial model can be used to drive further testing and can also be used as the basis for producing additional partial models in incremental integration testing. While the process of deriving the test sequences could suffer from a combinatorial explosion, the effort required to generate the partial model is polynomial in the number of test sequences and their length. Thus, where it is not feasible to produce test sequences that achieve a given type of coverage it is still possible to produce a partial model on the basis of test sequences generated to achieve some other criterion. As a result, the process of generating a partial model has the potential to scale to large industrial software systems. While a particular model checker, UPPAAL, was used, it should be relatively straightforward to adapt the approach for use with other CTL based model checkers. A potential additional benefit of the approach is that it provides a visual description of the state-based testing of distributed systems, which may be beneficial in other contexts such as education and comprehension.

On thermoeconomics of energy systems at variable load conditions: Integrated optimization of plant design and operation

Abstract Thermoeconomics has been assuming a growing role among the disciplines oriented to the analysis of energy systems, its different methodologies allowing solution of problems in the fields of cost accounting, plant design optimisation and diagnostic of malfunctions. However, the thermoeconomic methodologies as such are particularly appropriate to analyse large industrial systems at steady or quasi-steady operation, but they can be hardly applied to small to medium scale units operating in unsteady conditions to cover a variable energy demand. In this paper, the fundamentals of thermoeconomics for systems operated at variable load are discussed, examining the cost formation process and, separately, the cost fractions related to capital depreciation (which require additional distinctions with respect to plants in steady operation) and to exergy consumption. The relevant effects of the efficiency penalty due to off design operation on the exergetic cost of internal flows are also examined. An original algorithm is proposed for the integrated optimization of plant design and operation based on an analytical solution by the Lagrange multipliers method and on a multi-objective decision function, expressed either in terms of net cash flow or primary energy saving. The method is suitable for application in complex energy systems, such as “facilities of components of a same product” connected to external networks for power or heat distribution. For demonstrative purposes, the proposed thermoeconomically aided optimization is performed for a grid connected trigeneration system to be installed in a large hotel.

Convective phenomena in large melts including magnetic fields

The set of characteristic parameters which describe modern large industrial CZ silicon single crystal growth systems is introduced. The main melt flow driving mechanisms are considered, and the characteristic density values of various in the melt acting forces are estimated. The analysis is illustrated with examples of numerical simulation and comparisons with experiments.

Design and Optimization of Flexible Utility Systems Subject to Variable Conditions: Part 1: Modelling Framework

Industrial utility systems offer many degrees of freedom to improve their design and operation to achieve substantial savings in capital and/or operating costs. However, minimizing such expenditure also represents a challenging task due to the complex and highly-combinatorial nature of the optimization problem. While conventional approaches have simplified the problem by addressing operational and design (synthesis) issues in a separate or iterative way, the present work proposes a novel computational tool for both the design and operation of industrial utility systems in which their inherent flexibility is fully exploited through different operating scenarios. In order to consider the design and operational parameters of these systems as (continuous) mathematical variables to be optimised simultaneously, a new generic modelling framework for energy equipment has been developed and validated in which performance depends on both unit size and operational load. The first part of this paper describes the linear models developed to solve this problem for multi-fuel boilers, steam and gas turbines and heat recovery steam generators. These are employed to build a robust (multiperiod) MILP formulation to tackle grassroots design, retrofit or operational problems of the size and complexity commonly found in large industrial systems.

Dynamic multiobjective optimization of large-scale industrial production systems: An emerging strategy

The large industrial production systems face several conflicting challenges of energy efficiency improvements, lower consumption of raw materials per unit of production, extending the product durability, minimizing the environmental impacts, and cautious use of natural resources. In this context it is well obvious that the optimization problem is multiobjective in nature. The paper emphasizes critical review of optimization methods of large-scale industrial production systems and presentation of a novel systematic multiobjective and multiscale optimization methodology based mainly on a combined local optimality search with global optima determination, and advanced system decomposition and constraint handling.

A reference accelerator scheme for ADS applications

Accelerator Driven Systems (ADS) for transmutation of nuclear waste typically require 350 MeV–1 GeV accelerators delivering proton fluxes of 5–10 mA for demonstrators, and 20–50 mA for large industrial systems. Thus, such machines belong to the category of the so-called HPPA (High-Power Proton Accelerators), with multi-megawatt beam power. HPPA are presently developed and constructed at great pace for their broad utility in fundamental or applied science. Compared to other HPPA, many features and requirements are similar for the ADS driver. However, there is a need for exceptional reliability: because of the induced thermal stress to the sub-critical core, the number of unwanted “beam-trips” should not exceed a few per year, a requirement that is several orders of magnitude above usual performance. Consecutive to the work of the European Technical Working Group (ETWG) on ADS, the Preliminary Design Study of an Experimental ADS (PDS-XADS) was launched in 2001 as a 5th Framework Program EC project. 1 1 EC Contract No FIKW-CT-2001-00179. A special Working Package (WP3) was dedicated to the accelerator design, taking especially into account that the issue of “beam-trips” could be a potential “show-stopper” for ADS technology in general. A reference solution, based on a linear superconducting accelerator with its associated doubly achromatic beam line, has been worked out to some detail. For high reliability, the proposed design is intrinsically fault tolerant, relying on highly modular “de-rated” components associated to a fast digital feedback system. The proposed solution also appears to be robust concerning operational aspects like maintenance and radioprotection. A roadmap for construction as well as the required consolidated budget was elaborated. A program for the remaining R&D, focused on experimental reliability demonstration of prototypical components has been elaborated. This R&D will be performed in the 6th Framework Program EC project EUROTRANS, 2 2 EC Contract No FI6W-516520. which presently is just starting.

RESEARCH NEEDS IN LARGE SCALE INDUSTRIAL SYSTEMS

In today's industry, the requirements concerning the cost effectiveness of the production as well as end product quality are becoming even harder. Companies operating at real time in globalized business require agile production that quickly responds to changes in the business environment.The build-up, operation and maintenance of large scale industrial production systems require a whole network of experts of different domains. In setting up such a network, one must carefully design the roles of the actors in a manner that the network supports the overall performance of the system. Also the views through which each actor accesses the system must be designed to efficiently support his decision making.Recent research has made great advancement in data mining and information discovery in large sets of data. Also the modelling and simulation is slowly but surely being taken up in different phases of the plant life span. The standardization of plant life cycle data as well as on-line interfaces for the exchange of data and events has taken steps forward. Furthermore, mobile solutions and advanced visualization are entering the industry. All of this is surely helpful in managing large scale industrial systems. Often the question remains: what is the overall good performance of the system.What is now needed from the research is practical methods for selecting appropriate performance metrics and for implementing decision support systems for managing and controlling of the operative state in a large scale industrial system. The methods must take into account the network nature of the organization and the human-technology interaction of each actor in the network.

A LSIS CASE STUDY: COMPUTER INTEGRATED MANUFACTURING AND MANAGEMENT SYSTEMS

AbstractAn approach to development of pioneering large scale industrial systems is described for a case study of computer integrated manufacturing and management systems. The paper presents some experience in large scale systems and the current state of art for the domain. A feasible approach is proposed, based on prospective user expectations and the system development with use of so called first thread on which the standards facilitating development of subsequent systems should be developed and people acquainted with both manufacturing and management problems should be educated. The approach proposed is particularly suitable for big metallurgical plants and IFAC seems to be a good choice for an organisation preparing the first implementation.

Dynamic analysis of java applications for multithreaded antipatterns

Formal verification is not always applicable to large industrial software systems due to scalability issues and difficulties in formal model and requirements specification. The scalability and model derivation problems could be alleviated by runtime trace analysis, which combines both testing and formal verification. We implement and compare an ad-hoc custom approach and a formal approach to detect common bug patterns in multithreaded Java software. We use the tracing platform of the Eclipse IDE and state-of-the-art model checker Spin.