Integrating part and assembly modelling

Current modelling systems adequately support either modelling of parts or modelling of assemblies, whereas ideal modelling systems should adequately support both. To achieve this, a new modelling system has been developed, which uses enhanced multiple-view feature modelling. This advanced modelling approach provides specialised interpretations of a product for different development phases, by means of so-called feature views, and ways to keep these interpretations consistent, i.e. to make sure that they all represent the same product. The paper concentrates on the views that support detail design of parts and assembly design of the whole product, and the way these views are related and kept consistent. It describes the features and the tools that can be used to build and maintain the feature models of the views. An example modelling session is given to illustrate the benefits of such integrated modelling.     

New perspectives in ontological analysis: Guidelines and rules for incorporating modelling languages into UEML

Ontological analysis of modelling languages has been mainly used for evaluating quality of modelling language w.r.t. one specific upper ontology. Generally speaking this evaluation has been done by identifying the coverage of the modelling language constructs w.r.t. the ontology and vice-versa. However, a quite limited support has been developed for performing the ontological analysis task. Specifically, various ontologies used for ontological analysis are not associated to a machine readable format; the coverage of modelling language constructs is mostly provided by informal tables mapping one construct on to one ontological concept; the way in which this coverage task is undertaken is poorly specified (resulting in distinct results for distinct experts involved), and finally, preventing any ontology enrichment for dealing with some specialised language constructs. This limited support also prevents application of ontological analysis outcomes to problems and domains dealing with interoperability, integration and integrated usage of enterprise and IS models, which is today one of the key aspects for making interoperable, maintainable and evolvable inter and intra enterprise software systems. The paper provides an overview of the Unified Enterprise Modelling Language (UEML) approach, which introduces advanced support to ontological analysis of modelling languages. The paper is specifically focused on the task of ontological analysis of modelling languages (named incorporation of modelling languages) by introducing and explaining several guidelines and rules for driving the task: therefore, not all the aspects of the UEML approach will be discussed through the paper. The guidelines and rules are illustrated by incorporation of three selected modelling constructs from IDEF3, a well known language for specifying enterprise processes.     

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.     

二次拟合：一种提高软件可靠性模型精度的新方法

针对软件可靠性模型精度不高的问题,提出了"一次建模 + 二次拟合"的方法,通过误差补偿机制来提高模型精度,并将该方法应用于航天软件失效数据集.实践结果表明,提出的方法对于提高软件可靠性模型精度是有效的.     

MDA环境下可变性元建模方法研究

为模型提供可变性支持对于模型驱动软件开发的实践具有重要意义。可变性建模有利于捕捉领域概念及其特征的共性和差异性,为构造应用模型簇提供了一种模型复用的途径。在研究特征建模的可变性机制和MDA标准建模语言对可变性表示不足的基础上,提出了一种可变性元建模方法,构造可变性概要以支持原子、成组等可变性描述,开发了可变性验证和模型转换算法。通过实际项目的验证,该方法为基于可变性建模的模型内容复用提供了有效支持。     

When do aquatic systems models provide useful predictions,what is changing,and what is next?

This article considers how aquatic systems modelling has changed since 1995 and how it must change in future if we are to continue to advance. A distinction is made between mechanistic and statistical models, and the relative merits of each are considered. The question of “when do aquatic systems models provide accurate and useful predictions?” is addressed, implying some guidelines for model development. It is proposed that, in general, ecological models only provide management-relevant predictions of the behaviour of real systems when there are strong physical (as opposed to chemical or ecological) drivers. Developments over the past 15 years have included changes in technology, changes in the modelling community and changes in the context in which modelling is conducted: the implications of each are briefly discussed. Current trends include increased uptake of best practice guidelines, increasing integration of models, operationalisation, data assimilation, development of improved tools for skill assessment, and application of models to new management questions and in new social contexts. Deeper merging of statistical and mechanistic modelling approaches through such techniques as Bayesian Melding, Bayesian Hierarchical Modelling and surrogate modelling is identified as a key emerging area. Finally, it is suggested that there is a need to systematically identify areas in which our current models are inadequate. We do not yet know for which categories of problems well-implemented aquatic systems models can (or cannot) be expected to accurately predict observational data and system behaviour. This can be addressed through better modelling and publishing practices.     

COSA – A generic cognitive system architecture based on a cognitive model of human behavior

This article presents an overview of COSA, a cognitive system architecture, which is a generic framework proposing a unified architecture for cognitive systems. Conventional automation and similar systems lack the ability of cooperation and cognition, leading to serious deficiencies when acting in complex environments, especially in the context of human-computer interaction. Cognitive systems based on cognitive automation can overcome these deficiencies. Designing such artificial cognitive systems can be considered a very complex software development process. Although a number of developments of artificial cognitive systems have already demonstrated great functional potentials in field tests, the engineering approach of this kind of software is still a candidate for further improvement. Therefore, wide-spread application of cognitive systems has not been achieved yet. This article presents a new engineering approach for cognitive systems, implemented by the COSA framework, which may be a crucial step forward to achieve a wide-spread application of cognitive systems. The approach is based on a new concept of generating cognitive behaviour, the cognitive process (CP). The CP can be regarded as a model of the human information processing loop whose behaviour is solely driven by "a-priori knowledge". The main features of COSA are the implementation of the CP as its kernel and the separation of architecture from application leading to reduced development time and increased knowledge reuse. Additionally, separating the knowledge modelling process from behaviour generation enables the knowledge designer to use the knowledge representation that is best suited to his modelling problem. A first application based on COSA implements an autonomous unmanned air vehicle accomplishing a military reconnaissance mission. Some of the application experiences with the new approach are presented.     

General-purpose software for intertemporal economic models

Intertemporal modelling is becoming increasingly important in general equilibrium policy analysis. Issues such as natural resource management, pollution control, investment, the promotion of technical change, and the accumulation of foreign debt all involve explicit intertemporal behavior and thus require intertemporal models to address adequately. Applied researchers have been slow to adopt the intertemporal paradigm because it can impose formidable computational requirements. In this paper we address this problem by presenting flexible, efficient new software which can solve complex intertemporal models in a fraction of the time required by conventional approaches.Our intertemporal software is an extension of GEMPACK, a suite of general-purpose computer programs developed to streamline the implementation and solution of a wide class of applied partial or general equilibrium models. This paper describes GEMPACK's new intertemporal modelling capabilities which make it straightforward for modellers to implement and solve their models. Because GEMPACK operates on models written in a syntax similar to ordinary algebra, it is easy for researchers to revise their models whenever necessary.In summary, this new software removes the computational impediments to intertemporal modelling, thereby allowing modellers to concentrate on the economics of their models.Industry Commission     

Building a production planning process with an approach based on CIMOSA and workflow management systems

Nowadays, one of the major challenges for enterprises is to stay competitive in today's changing market environment. This can be supported by business process models which on one hand are consistent and adequate (requirement #1), and on the other hand can be enacted and operated in an easy, fast, straightforward and integrated way (requirement #2). The CIMOSA architecture provides the basis for business process modelling to fulfil both of the above requirements. It supports the creation of consistent process models and allows to identify almost all the information required for the development of a workflow model. These models can be implemented using one of the commercial workflow management systems. In this paper we present the methodology based on the CIMOSA architecture that we have developed to build a workflow model in ©Lotus Notes for the forecasting and production planning processes in a tiles manufacturing enterprise. The CIMOSA approach has also been used to design the necessary software applications for processing the information of the resulting workflow system.     

Automatic fuzzy-rule assessment and its application to the modelling of nitrogen leaching for large regions

 Diffuse nutrient emissions from agricultural land is one of the major sources of pollution for ground water, rivers and coastal waters. The quantification of pollutant loads requires mathematical modelling of water and nutrient cycles. The deterministic simulation of nitrogen dynamics, represented by complicated highly non-linear processes, requires the application of detailed models with many parameters and large associated data bases. The operation of those models within integrated assessment tools or decision support systems for large regions is often not feasible. Fuzzy rule based modelling provides a fast, transparent and parameter parsimonious alternative. Besides, it allows regionalisation and integration of results from different models and measurements at a higher generalised level and enables explicit consideration of expert knowledge. In this paper an algorithm for the assessment of fuzzy rules for fuzzy modelling using simulated annealing is presented. The fuzzy rule system is applied to simulate nitrogen leaching for selected agricultural soils within the 23687 km² Saale River Basin. The fuzzy rules are defined and calibrated using results from simulation experiments carried out with the deterministic modelling system SWIM. Monthly aggregated time series of simulated water balance components (e.g. percolation and evapotranspiration), fertilization amounts, resulting nitrogen leaching and crop parameters are used for the derivation of the fuzzy rules. The 30-year simulation period was divided into 20 years for training and 10 years for validation, with the latter taken from the middle part of the period. Three specific fuzzy rule systems were created from the simulation experiments, one for each selected soil profile. Each rule system includes 15 rules as well as one prescribed rules from expert knowledge and 7 input variables. The performance of the fuzzy rule system is satisfactory for the assessment of nitrate leaching on annual to long term time steps. The approach allows rapid scenario analysis for large regions and has the potential to become part of decision support systems for generalised integrated assessment of water and nutrients in macroscale regions.     

The application of information systems for the design and operation of flexible machining cells

The use of information systems in manufacturing applications has dramatically changed over the last few years. The design and implementation of somewhat dated relational databases has been replaced by the generation of information models, that can be simultaneously used for the development of information systems and satisfy their integration requirements. Over the last ten years the authors have been involved in a series of research programmes focusing on the design and operation of flexible machining cells. The use of information systems has been a central theme and the enabling technology to achieve a number of novel design concepts and operational strategies for such cells. The initial research was based on the utilization of relational databases to integrate a variety of modelling and design tools. However, the additional effort required to integrate such databases to manufacturing software tools, in the form of developing file translators, information gateways and interfac es, has made the authors adopt a new approach. With this approach the information requirements are represented in a neutral format within a data model, using a formal data specification language developed by the Standards for the Exchange of Product (STEP) committee. This paper describes these changes in the design and implementation of information systems in manufacturing applications, and provides an initial view of future research requirements.     

Development of an oil palm cropping systems model: Lessons learned and future directions

Oil palm has become one of the most important crops in the world with questions being raised about its economic and environmental sustainability. Agricultural systems models are regularly employed in studying sustainable crop management but no detailed model is currently available for oil palm systems.We developed a production systems model for oil palm within the Agricultural Production Systems Simulator (APSIM) framework and tested it using data across a range of environments within Papua New Guinea (PNG). The model captured key growth responses to climate and management. This demonstrates that modern modelling frameworks do allow for rapid model development for new agricultural systems.However, whilst application of the model is promising, the availability of key data is likely to restrict its use. Local soil and weather data are not available in adequate detail for many of the major oil palm production areas, although some methods exist to address this.     

Design and demonstration of a data model to integrate agent-based and field-based modelling

Dynamic environmental modelling of spatio-temporal systems often requires the representation of both fields and agents. Fields are continuous with values in the whole spatio-temporal domain of a model, while agents are bounded in space and often mobile. It is currently difficult for environmental modellers with limited software engineering background to construct such field-agent models, as modelling frameworks mostly do not support the integration of fields and agents. To overcome this issue, we describe a data model combining fields and agents in a single concept. This data model represents fields, agents and relations by grouping items sharing properties into a phenomenon. The concepts domain, property set and value handle spatio-temporal attribute representations. The data model is implemented in a software prototype that shows how data on fields and agents is stored and manipulated.     

Reusing knowledge in embedded systems modelling

Model‐based design is a promising technique to improve the quality of software and the efficiency of the software development process. We are investigating how to efficiently model embedded software and its environment to verify the requirements for the system controlled by the software. The software environment consists of mechanical, electrical and other parts; modelling it involves learning how these parts work, deciding what is relevant to model and how to model it. It is not possible to fully automate these steps. There are general guidelines, but given that every modelling problem differs, much is left to the modeller's own preference, background and experience. Still, when the next generation of a system is designed, the new system will have common elements with its previous version. Therefore, lessons learned from the current model could inform future models. We propose a framework for identifying the non‐formal elements of knowledge, insights and a model itself, which can support modelling of the next system generation. We will present the application of our framework on an action research case – modelling mechanical parts of a paper‐inserting machine.     

Model-based reasoning: a principled approach for software engineering

The software engineering industry suffers from almost unmanageable complexity both in the products it produces and in the processes of production. One of the current shortcomings in the software production process is the weakness of the models used. This paper makes observations on the role of knowledge in engineering and examines the central role of models and simulation. We develop an argument for the application of certain new forms of modelling methods in software engineering in order to impose more discipline and give a principled framework for building models that can support the software life-cycle. The concept of a model is examined in depth and different characteristics and types of model are defined. This introduces the relatively new concept of qualitative models and their use in the field known as model-based reasoning. Unlike previous knowledge-based methods, model-based reasoning has several important advantages. Although very few model-based software projects exist, we illustrate how this approach can be developed by drawing on applications from traditional engineering. It is argued that, because qualitative modelling offers great power for addressing the issue of complexity, such models have considerable potential as high-level abstractions of software products. These could form the core of tools for the management and support of the software development process through the whole product life-cycle.     

Evaluation of techniques for manufacturing process analysis

In the last 20 years, several methodologies, models and tools have been developed for the analysis and optimisation of manufacturing systems in order to propose general improvements. Many of these techniques make extensive use of data modelling, simulation, decision-making support, expert systems and reference models. This paper presents the first outcome of a piece of research work to integrate manufacturing process analysis into an integrated modelling framework covering all aspects related to the shop-floor as it really is. The main methodologies and software tools have been identified and evaluated and the results tested on industrial examples. As a result of this evaluation it has been possible to identify the inefficiencies of the techniques. These problems are connected with integrating the different types of data to be analysed—such as quality, time, costs, resource capacity, productivity, flexibility or improvements—into a single analysis environment. The inefficiencies detected enable us to present a general framework for making better use of modelling techniques for manufacturing process analysis. Received July 2005 / Accepted January 2006     

Automatic generation of IDEF0 models

This paper looks into a new area for knowledge-based system application, that of manufacturing modelling. Manual generation of IDEF0 models of manufacturing systems is time-consuming and inconsistent. However, the process can be automated to improve timeliness and consistency. In this paper, a knowledge-based manufacturing modelling system for the automatic generation of IDEF0 models is proposed. The system will not only greatly reduce the IDEF0 modelling time but will also eliminate the inconsistency problem of conventional IDEF0 modelling systems. The paper explains the knowledge-based approach and identifies the kinds of domain knowledge that are required for the construction of the knowledge-based manufacturing modelling system.     

Numeric and curve parameters for freeform surface feature models

The success of feature modelling systems depends to a large extent on offering user-friendly ways for specifying and varying feature models. In this paper, several new facilities are introduced for this.Numeric and curve parameters are presented for specification and variation of freeform surface feature models. Several properties of the parameters can be defined, such as the direction of evaluation for a curve parameter. In addition to parameters present in features, other parameters can be added to a feature model, including intersection curves between features.To provide these facilities, a new three-level structure is introduced, which includes a partially evaluated model that can capture new generic model entities, including feature intersection curves. The work has been implemented in a prototype surface feature modelling system with functionality for feature class definition, feature model creation, and advanced feature model variation through the new types of parameters.     

An application of CIMOSA concepts in the development of change capable manufacturing cells

A new approach to the design and reconfiguration of change capable manufacturing cells is described. The approach is based on (i) the development of particular models of cells, where the use of CIMOSA modelling constructs is structured and informed by a semi-generic model of similar manufacturing cells and (ii) the use of new constructs and tools that operationalise particular models in the form of an explicit, model-based configuration of cell resources and software components. The paper describes key elements of the semi-generic model and a case study application of the approach when designing and prototyping a case study manufacturing cell.