A novel energy demand modelling approach for CNC machining based on function blocks

Energy efficiency remains one of the major issues in the machining domain. Today's machining systems are confronted with a number of new challenges, such as turbulent product demand and variations in production resources. Rapid and flexible energy modelling in a distributed and collaborative machining environment emerges as a new research area. Energy demand models in such an environment need to be practical, accurate, effective, scalable and reusable. Energy analysis and optimisation cannot be carried out once for all at the beginning. Instead, it is an on-going process. In this paper, the function block technique, i.e. IEC 61499, is used for the development of energy demand models as it brings advantages such as modularity, encapsulation, extensibility and reusability. A brief review on energy modelling and research on function blocks are given in the first part. A novel energy demand modelling approach based on function blocks is then proposed and elaborated. Three types of function blocks have been developed, i.e. machine tool dependent function blocks, state transition function blocks, and service interface function blocks. The first type, as the fundamental building blocks, is divided into two sub-types, machine component function block and machining state function block. Two case studies, based on a small 3-axis milling machine and an industrial production line respectively, are presented to demonstrate the possible applications using the function block-based model. Comprehensive discussions are given thereafter, including a pilot application of a distributed process planning system and a unique energy evaluation scheme. A confidence level associated energy rating system is proposed as the first step to turn energy consumption figures into useful indicators. The energy demand model based on function blocks developed here enhances the energy modelling and their practical implementations.     

From conceptual modelling to requirements engineering

Conceptual modelling is situated in the broader view of information systems requirements engineering. Requirements Engineering (RE) explores the objectives of different stakeholders and the activities carried out by them to meet these objectives in order to derive purposeful system requirements and therefore lead to better quality systems, i.e., systems that meet the requirements of their users. Thus RE product models use concepts for modelling these instead of concepts like data, process, events, etc., used in conceptual models. Since the former are more stable than the latter, requirements engineering manages change better. The paper gives the rationale for extending traditional conceptual models and introduces some RE product models. Furthermore, in contrast to conceptual modelling, requirements engineering lays great stress on the engineering process employed. The paper introduces some RE process models and considers their effect on tool support. This revised version was published online in June 2006 with corrections to the Cover Date.     

Fuzzy inductive reasoning for variable selection analysis and modelling of biological systems

Fuzzy inductive reasoning (FIR) is a qualitative inductive modelling and simulation methodology for dealing with dynamical systems. It has proven to be a powerful tool for qualitative model identification and prediction of future behaviour of various kinds of dynamical systems, especially from the soft sciences, such as biology, biomedicine and ecology. This paper focuses on modelling aspects of the FIR methodology. It is shown that the FIR variable selection analysis is a useful tool not only for FIR but also for other classical quantitative methodologies such as nonlinear autoregressive moving average modelling with external inputs (NARMAX). The tool allows us to obtain models that interpret a system under study in optimal ways, in the sense that these models are well suited for predicting the future behaviour of the system they represent. The FIR variable selection analysis turns out to work well even in those applications where standard statistical variable selection analysis does not provide any useful information. In this paper, the FIR variable selection analysis is applied to a real system stemming from biology, namely, shrimp farming. The main goal is the identification of a growth model for occidental white shrimp (Penaeus vannamei), which allows farmers to plan the dates for seeding and harvesting the ponds in order to maximise their profits. FIR and NARMAX shrimp growth models are identified, and their prediction capabilities are compared to each other.     

Systems featuring chain structures – a generalized Bond Graph modelling

ABSTRACT

The study presents power flow modelling for dynamic systems featuring chain structures. For this purpose, the Bond Graph method is particularly suitable. This tool describes engineering systems in different fields via domain-independent graphical representation using general dynamic modelling for any physical system. Even repetitive constructions called chains can be modelled. This paper aims for power flow based dynamical models of serial type chain structures. Further graphical systematization identifies four basic scalar segments which again correlate with four general vectorial total model structures. Examples and general algorithms, to obtain the scalar segment model and the vectorial overall model, support the proposed modeling. The main vectorial modelling element is identified as a relative coordinate transformation. The approach includes usage for open and closed chains plus rings of ring structures. It aims at universal usage independent of serial chain structure type, application domain or software tool. Moreover, it can be used beneficially in various non-physical fields.     

CHEOPS: A tool-integration platform for chemical process modelling and simulation

A large number of modelling tools exist for the construction and solution of mathematical models of chemical processes. Each (chemical) process modelling tool provides its own model representation and model definition functions as well as its own solution algorithms, which are used for performing computer-aided studies for the process under consideration. However, in order to support reusability of existing models and to allow for the combined use of different modelling tools for the study of complex processes, model integration is needed. This paper presents a concept for an integration platform that allows for the integration of modelling tools, combining their models to build up a process model and performing computer-aided studies based on this integrated process model. In order to illustrate the concept without getting into complicated algorithmic issues, we focus on steady-state simulation using models comprising only algebraic equations. The concept is realized in the component-based integration platform CHEOPS, which focuses on integrating and solving existing models rather than providing its own modelling capabilities.     

Automated guided vehicle systems and their Petri-net properties

This paper defines clearly and presents the fundamental properties of automated guided vehicle systems (AGVS) and their relationship to Petri nets. The objective is to develop an intelligent modelling tool to allow the design of robust AGVS models using some invariant Petri-net properties. The Petri-net properties of the system are presented in terms of safeness, boundedness, strict conservation, reachability and liveness. The robustness of the system at floor-level is embedded into the model by introducing system traffic collision-free, constant numbers of vehicles and traffic control signals, path reachability, and system traffic deadlock-free. Two different merge structures are presented to illustrate the effectiveness of the present approach. The result shows the strength of Petri-net theory in the modelling of complex AGVS. The AGVS models thus built are robust.     

Coloured Petri Nets and CPN Tools for modelling and validation of concurrent systems

Coloured Petri Nets (CPNs) is a language for the modelling and validation of systems in which concurrency, communication, and synchronisation play a major role. Coloured Petri Nets is a discrete-event modelling language combining Petri nets with the functional programming language Standard ML. Petri nets provide the foundation of the graphical notation and the basic primitives for modelling concurrency, communication, and synchronisation. Standard ML provides the primitives for the definition of data types, describing data manipulation, and for creating compact and parameterisable models. A CPN model of a system is an executable model representing the states of the system and the events (transitions) that can cause the system to change state. The CPN language makes it possible to organise a model as a set of modules, and it includes a time concept for representing the time taken to execute events in the modelled system. CPN Tools is an industrial-strength computer tool for constructing and analysing CPN models. Using CPN Tools, it is possible to investigate the behaviour of the modelled system using simulation, to verify properties by means of state space methods and model checking, and to conduct simulation-based performance analysis. User interaction with CPN Tools is based on direct manipulation of the graphical representation of the CPN model using interaction techniques, such as tool palettes and marking menus. A license for CPN Tools can be obtained free of charge, also for commercial use.     

Physics guided neural network for machining tool wear prediction

Tool wear prediction is of significance to improve the safety and reliability of machining tools, given their widespread applications in nearly every branch of manufacturing. Mathematical modelling, including data driven modelling and physics-based modelling, is an important tool to predict the degree of tool wear. Howerver, the performance of conventional data driven models is restricted by the absent representation of physical inconsistency. The physics-based models usually fail to consider the complex tool cutting conditions and dynamic changes of physical parameters in practice. To address these issues, a novel physics guided neural network model is presented for tool wear prediction. Firstly, a cross physics-data fusion (CPDF) scheme is proposed as the modelling strategy to fuse the hidden information explored by a physics-based model and a data driven model. Secondly, the information hidden in the unlabelled sample is explored by the physics-based model of tool cutting, inspired by semi-supervised learning. Thirdly, a novel loss function which takes the physical discipline into account is proposed to evaluate the physical inconsistency quantitatively. The advantage of the developed method is that it explores sufficient information from both physics and data domains to eliminate the physical inconsistency existing in conventional data driven models.     

CITY DRAIN © – An open source approach for simulation of integrated urban drainage systems

In the last years design procedures of urban drainage systems have shifted from end of pipe design criteria to ambient water quality approaches requiring integrated models of the system for evaluation of measures. Emphasis is put on the improvement of the receiving water quality and the overall management of river basins, which is a core element of the Water Framework Directive (WFD) as well.Typically, it is not necessary to model the whole variety of effects on the receiving water but to focus on the few dominating ones. Only pollutants and processes that have a direct and significant influence on the selected impacts need to be described quantitatively, whereas all other processes can be neglected. Hence, pragmatism is required to avoid unnecessary complexity of integrated models. This is as well true for software being used in daily engineering work, requiring simplicity in handling and a certain flexibility to be adjusted for different scenarios.CITY DRAIN © was developed to serve these needs. Therefore it was developed in the Matlab/Simulink © environment, enabling a block wise modelling of the different parts of the urban drainage system (catchment, sewer system, storage devises, receiving water, etc.). Each block represents a system element (subsystem) with different underlying modelling approaches for hydraulics and mass transport. The different subsystems can be freely arranged and connected to each other in order to describe an integrated urban drainage system. The open structure of the software allows to add own blocks and/or modify blocks (and underlying models) according to the specific needs.The application of CITY DRAIN is shown within the integrated modelling case study Vils/Reutte. Further additional applications for CITY DRAIN, including batch simulations, real time control (RTC) and model based predictive control (MBPC) are presented and discussed.     

Condition-based diagnosis of mechatronic systems using a fractional calculus approach

While fractional calculus (FC) is as old as integer calculus, its application has been mainly restricted to mathematics. However, many real systems are better described using FC equations than with integer models. FC is a suitable tool for describing systems characterised by their fractal nature, long-term memory and chaotic behaviour. It is a promising methodology for failure analysis and modelling, since the behaviour of a failing system depends on factors that increase the model’s complexity. This paper explores the proficiency of FC in modelling complex behaviour by tuning only a few parameters. This work proposes a novel two-step strategy for diagnosis, first modelling common failure conditions and, second, by comparing these models with real machine signals and using the difference to feed a computational classifier. Our proposal is validated using an electrical motor coupled with a mechanical gear reducer.     

Investigations on the dynamic coupling in AUV-manipulator system and the manipulator trajectory errors using bond graph method

This article presents the modelling and simulation of the dynamic coupling in an autonomous underwater vehicle (AUV)-manipulator system, used for subsea intervention tasks. Bond graph, a powerful tool in multi-domain dynamic system modelling, is used for the first time to model the coupled dynamics of the AUV-manipulator system. This method enables the development of the system model in a modular form by creating sub-system models and connecting these models together at energy interactions ports, thus overcoming many of the computational difficulties encountered in conventional modelling methods. The effects of gravity, buoyancy, added mass and fluid drag on the dynamics of a 3 degrees of freedom (DoF) manipulator mounted on a 6 DoF AUV are analysed. The manipulator trajectory errors due to the interaction forces and moments between the vehicle and the manipulator have also been investigated and the results are presented. The dynamic model predicts the reaction forces on the vehicle under various operating conditions of the manipulator and their influence on the manipulator trajectory. The percentage errors of manipulator tip trajectory for different initial configurations and operating conditions are analysed. The estimation of resulting errors in the manipulator path due to dynamic coupling effect on the manipulator trajectory helps in the design of suitable trajectory controller for the system. Cartesian space transpose Jacobian controller for trajectory control of manipulator has been implemented and results are presented.     

“It was an artefact not the result”: A note on systems dynamic model development tools

Environmental modelling is done more and more by practising ecologists rather than computer scientists or mathematicians. This is because there is a broad spectrum of development tools available that allows graphical coding of complex models of dynamic systems and help to abstract from the mathematical issues of the modelled system and the related numerical problems for estimating solutions. In this contribution, we study how different modelling tools treat a test system, a highly non-linear predator–prey model, and how the numerical solutions vary. We can show that solutions (a) differ if different development tools are chosen but the same numerical procedure is selected; (b) depend on undocumented implementation details; (c) vary even for the same tool but for different versions; and (d) are generated but with no notifications on numerical problems even if these could be identified. We conclude that improved documentation of numeric methods used in the modelling software is essential to make sure that process based models formulated in terms of these modelling packages do not become “black box” models due to uncertainty in integration methods.     

A complete approach for CIM modelling and model formalising

ContextComputation Independent Model (CIM) as a business model describes the requirements and environment of a business system and instructs the designing and development; it is a key to influencing software success. Although many studies currently focus on model driven development (MDD); those researches, to a large extent, study the PIM-level and PSM-level model, and few have dealt with CIM-level modelling for case in which the requirements are unclear or incomplete.ObjectiveThis paper proposes a CIM-level modelling approach, which applies a stepwise refinement approach to modelling the CIM-level model starting from a high-level goal model to a lower-level business process model. A key advantage of our approach is the combination of the requirement model with the business model, which helps software engineers to define business models exactly for cases in which the requirements are unclear or incomplete.MethodThis paper, based on the model driven approach, proposes a set of models at the CIM-level and model transformations to connect these models. Accordingly, the formalisation approach of this paper involves formalising the goal model using the category theory and the scenario model and business process model using Petri nets.ResultsWe have defined a set of metamodels and transformation rules making it possible to obtain automatically a scenario model from the goal model and a business process model from the scenario model. At the same time, we have defined a mapping rule to formalise these models. Our proposed CIM modelling approach and formalisation approach are implemented with an MDA tool, and it has been empirically validated by a travel agency case study.ConclusionThis study shows how a CIM modelling approach helps to build a complete and consistent model at the CIM level for cases in which the requirements are unclear or incomplete in advance.     

UML的形式化描述语义

本文提出了一种新的定义UML形式化语义的方法。我们将建模语言的语义区分为描述语义和功能语义两个方面。描述语义定义哪些系统满足模型,功能语义定义模型中的基本概念。本文用一阶逻辑定义了UML的类图、交互图和状态图的描述语义,并介绍我们实现的将UML模型转换成逻辑系统的软件工具LAMBDES,该工具集成了定理证明器SPASS,可以对模型进行自动推理。我们成功地将此方法和工具应用于模型的一致性检查。     

Direct 3D Manipulation Techniques for Interactive Constraint-based Solid Modelling

This paper presents a novel constraint-based 3D manipulation approach to interactive constraint-based solid modelling. This approach employs a constraint recognition process to automatically recognise assembly relationships and geometric constraints between entities from 3D manipulation. A technique referred to as allowable motion is used to achieve accurate 3D positioning of a solid model by automatically constraining its 3D manipulation without menu interaction. A set of virtual design tools, which can be used to construct constraint-based solid models within a virtual environment, are also supported. These tools have been implemented as functional 3D objects associated with several pre-defined modelling functions to simulate physical tools such as a drilling tool and T-square. They can be directly manipulated by the user, and precisely positioned relative to other solid models through the constraint-based 3D manipulation approach. Their modelling functions can be automatically triggered, depending upon their associated constraints and the user's manipulation manner. A prototype system has been implemented to demonstrate the feasibility of these techniques for model construction and assembly operations.     

Neural networks and genetic algorithms can support human supervisory control to reduce fossil fuel power plant emissions

Artificial neural networks and genetic algorithms are two intelligent approaches initially targeted to model human information processing and natural evolutionary process, with the aim of using the models in problem solving. During the last decade these two intelligent approaches have been widely applied to a variety of social, economic and engineering systems. In this paper, they have been shown as modelling tools to support human supervisory control to reduce fossil fuel power plant emissions, particularly NO_x emissions. Human supervisory control of fossil fuel power generation plants has been studied, and the need of an advisory system for operator support is emphasized. Plant modelling is an important block in such an advisory system and is the key issue of this study. In particular, three artificial neural network models and a genetic algorithm-based grey-box model have been built to model and predict the NO_x emissions in a coal-fired power plant. In non-linear dynamic system modelling, training data is always limited and cannot cover all system dynamics; therefore the generalization performance of the resultant model over unseen data is the focus of this study. These models will then be used in the advisory system to support human operators on aspects such as task analysis, condition monitoring and operation optimization, with the aim of improving thermal efficiency, reducing pollutant emissions and ensuring that the power system runs safely.     

CIMOSA modelling processes

Engineering, integrating and managing complex enterprises requires the understanding, and the ability to partition and simplify their operational complexity. Enterprise modelling supports these requirements by providing means for describing process oriented systems and decomposing those into manageable pieces. However, enterprise modelling requires both a common modelling language and a sufficient modelling methodology. The language provides for common understanding on enterprise models across the industrial community. Modelling methodologies will guide users through the rather complex enterprise modelling tasks. Depending on the skills and the tasks of the modelling person, different methodologies will be implemented in the supporting modelling tool. The paper presents both a methodology for the modelling expert and one for the business user. Whereas the modelling expert will be involved in creating new models, structuring the model contents and developing new modelling components, the business user will use process models for decision support. The latter therefore has a need to modify and adapt enterprise models to represent operational alternatives. A methodology for this type of work has to be based on menus. Menus which are created and maintained by the modelling expert. The business user will mostly work with existing process models. He will evaluate process alternatives and will implement the best solution as the new model of his tasks. This mode of operation will thereby provide for automatic update of the models and will keep the models in sync with the changing reality.