A procedure for building product models

The application of product modeling in manufacturing companies raises the important question of how to model product knowledge in a comprehensible and efficient way. An important challenge is to qualify engineers to model and specify IT-systems (product models) to support their specification activities. A basic assumption is that engineers have to take the responsibility for building product models to be used in their domain. To do that they must be able to carry out the modeling task on their own without any need for support from computer science experts. This paper presents a set of simple, easily adaptable concepts and methods for modeling product knowledge. The concepts and methods are based on well-defined concepts and methods from data modeling (object oriented analysis) and domain modeling (product modeling). The concepts are general and can be used for modeling all types of specifications in the different phases in the product life cycle. The modeling techniques presented have been tested in different companies and have proved to work.     

Modular ABM development for improved dissemination and training

Agent-based models (ABMs) have become an important tool for advancing scientific understanding in a variety of disciplines and more specifically have contributed gains to natural resource management in recent decades. However, a key challenge to their utility is the lack of convergence upon a common set of assumptions for representing key processes (such as agent decision structure), with the outcome that published ABM tools are rarely (if ever) used beyond their original development team. While a number of ABM frameworks are publicly available for use, the continued development of models from scratch is a signal of the continuing difficulty in capturing sufficient modeling flexibility in a single package. In this study we examine ABM sharing by comparing co-citation networks from several well-known ABM frameworks to those used in the land-use change modeling community. We then outline a different publication paradigm for the ABM community that could improve the sharing of model structure and help move toward convergence on a common set of tools and assumptions.     

An approach to integrating shape and biomedical attributes in vascular models

Computational models have been used widely in tissue engineering research and have proven to be powerful tools for bio-mechanical analysis (i.e., blood flow, growth models, drug delivery, etc). This paper focuses on developing higher-fidelity models for vascular structures and blood vessels that integrate computational shape representations with biomedical properties and features. Previous work in computer-aided vascular modeling comes from two communities. For those in biomedical imaging, the goal of past research has been to develop image understanding techniques for the interpretation of x-ray, magnetic resonance imaging (MRI), or other radiological data. These representations are predominantly discrete shape models that are not tied to physiological properties. The other corpus of existing work comes from those interested in developing physiological models for vascular growth and behavior based on bio-medical attributes. These models usually either have a highly simplified shape representation, or lack one entirely. Further, neither of these representations are suitable for the kind of interactive modeling required by tissue engineering applications.This paper aims to bridge these two approaches and develop a set of mathematical tools and algorithms for feature-based representation and computer-aided modeling of vascular trees for use in computer-aided tissue engineering applications. The paper offers a multi-scale representation based on swept volumes and a feature-based representation that can attribute the geometric representation with information about blood flow, pressure, and other biomedical properties. The paper shows how the resulting representation can be used as part of an overall approach for designing and visualizing vascular scaffolds. As a real-world example, we show how this computational model can be used to develop a tissue scaffold for liver tissue engineering. Such scaffolds may prove useful in a number of biomedical applications, including the growth of replacement tissue grafts and in vitro study of the pharmacological affects of new drugs on tissue cultures.     

Strategic business modeling: representation and reasoning

Business intelligence (BI) offers tremendous potential for business organizations to gain insights into their day-to-day operations, as well as longer term opportunities and threats. However, most of today’s BI tools are based on models that are too much data-oriented from the point of view of business decision makers. We propose an enterprise modeling approach to bridge the business-level understanding of the enterprise with its representations in databases and data warehouses. The business intelligence model (BIM) offers concepts familiar to business decision making—such as goals, strategies, processes, situations, influences, and indicators. Unlike many enterprise models which are meant to be used to derive, manage, or align with IT system implementations, BIM aims to help business users organize and make sense of the vast amounts of data about the enterprise and its external environment. In this paper, we present core BIM concepts, focusing especially on reasoning about situations, influences, and indicators. Such reasoning supports strategic analysis of business objectives in light of current enterprise data, allowing analysts to explore scenarios and find alternative strategies. We describe how goal reasoning techniques from conceptual modeling and requirements engineering have been applied to BIM. Techniques are also provided to support reasoning with indicators linked to business metrics, including cases where specifications of indicators are incomplete. Evaluation of the proposed modeling and reasoning framework includes an on-going prototype implementation, as well as case studies.     

Integration of FMS performance evaluation models using patterns for an information system design

The objective of our work is to create an information system able to integrate different view points concerning the design and the control of a Flexible Manufacturing System. Numerous methods based on generic reference frameworks have been proposed for the modeling of all the aspects of production systems. These models have to be instantiated in order to be applied to specific systems. The difficulties are then to integrate pre-existing models of the studied systems with those obtained by the instantiation of the generic reference framework.

The proposed approach tackles the problem from the information system point of view. A meta-modeling bottom-up approach is presented based on the notion of patterns in order to facilitate the integration step.

An example concerned with the performance evaluation and scheduling of a production system is presented to show how the product viewpoint can be built in order to be integrated later with other viewpoints.     

面向信息化整体解决方案的集成化企业建模框架

针对信息化整体解决方案的目标、内容，分析了整体解决方案对模型的需求，给出面向信忠化整体解决方案的集成化企业建模框架EMITS．提出模型内容和结构随生命周期阶段不同而不同的观点，分析了各阶段的模型组成、模型之间的关系和模型演化过程，并给出基于EMITS的建模系统功能框架．     

Entity-Centric Operations Modeling for Business Process Management: A Multidisciplinary Review of the State-of-the-Art

The entity-based approach for operations modeling was published for the first time three decades ago. Specifically, the notion of entities as the main subjects of processes and entity life-cycle as a technique for dynamic modeling of operations were introduced independently by K. Robinson in 1979, C. Rosenquist in 1982 and M. Jackson in 1983. This modeling work emerged in clear contrast with static entity-relationship modeling found in the data-base tradition. These three pioneer contributions and other substantial research done at the realm of information engineering, structured systems analysis and social sciences in the 80''s and 90''s have established an important foundation for business operations modeling. On the other hand, Business Process Management (BPM) has continued to receive great attention from practitioners and scholars. Being one of the main hinges between theory and practice of business operations, BPM enjoys contributions from several domains of research such as economics, social sciences, engineering and computing. In spite of its steady growth, the industry side of BPM seems to have evolved somewhat unaware of related progress in the above sister disciplines. Specifically, recent claims on the need to integrate information and activities in process modeling and some rediscoveries of core ideas from entity-based dynamic modeling offer some examples of the disconnection. These and other findings suggest that the BPM field may not have yet fully benefited from the work done in the tradition of structured analysis, information engineering and process theory schools. Furthermore, the possibility of using entity life-cycle for modeling operations addressed by Case Management is an important byproduct. Entity-based life cycle offers a conceptual framework to integrate different types of enterprise operations whose modeling has not yet been reconciled in the BPM tradition. This paper presents an in-depth, multidisciplinary review of the state-of-the-art on entity life cycle modeling. The focus of this review is exclusively on modeling concepts and methodology while tools, programming models and other aspects of entity-life life cycle implementation will be addressed in companion papers. This review should also help pave more holistic approaches to business process modeling.     

Toward reference models for requirements traceability

Requirements traceability is intended to ensure continued alignment between stakeholder requirements and various outputs of the system development process. To be useful, traces must be organized according to some modeling framework. Indeed, several such frameworks have been proposed, mostly based on theoretical considerations or analysis of other literature. This paper, in contrast, follows an empirical approach. Focus groups and interviews conducted in 26 major software development organizations demonstrate a wide range of traceability practices with distinct low-end and high-end users of traceability. From these observations, reference models comprising the most important kinds of traceability links for various development tasks have been synthesized. The resulting models have been validated in case studies and are incorporated in a number of traceability tools. A detailed case study on the use of the models is presented. Four kinds of traceability link types are identified and critical issues that must be resolved for implementing each type and potential solutions are discussed. Implications for the design of next-generation traceability methods and tools are discussed and illustrated     

Data Mining of Software Development Databases

Software quality models can predict which modules will have high risk, enabling developers to target enhancement activities to the most problematic modules. However, many find collection of the underlying software product and process metrics a daunting task.Many software development organizations routinely use very large databases for project management, configuration management, and problem reporting which record data on events during development. These large databases can be an unintrusive source of data for software quality modeling. However, multiplied by many releases of a legacy system or a broad product line, the amount of data can overwhelm manual analysis. The field of data mining is developing ways to find valuable bits of information in very large databases. This aptly describes our software quality modeling situation.This paper presents a case study that applied data mining techniques to software quality modeling of a very large legacy telecommunications software system's configuration management and problem reporting databases. The case study illustrates how useful models can be built and applied without interfering with development.     

Exploring the CSCW spectrum using process mining

Process mining techniques allow for extracting information from event logs. For example, the audit trails of a workflow management system or the transaction logs of an enterprise resource planning system can be used to discover models describing processes, organizations, and products. Traditionally, process mining has been applied to structured processes. In this paper, we argue that process mining can also be applied to less structured processes supported by computer supported cooperative work (CSCW) systems. In addition, the ProM framework is described. Using ProM a wide variety of process mining activities are supported ranging from process discovery and verification to conformance checking and social network analysis.