Reusing enterprise models to build platform independent computer models

Enterprises use enterprise models to represent and analyse their processes, products, decisions, organisation, information flows, etc. Nevertheless, the enterprise knowledge that exists in enterprise models is not used beyond these purposes. The main goal of this paper is to present a framework that allows enterprises to reuse enterprise models to build software. The framework includes these dimensions: (1) a methodology that guides the use of the other dimensions in the reutilisation of enterprise models in software generation; (2) a set of metamodels to represent enterprises at the Computation Independent Model (CIM) level; (3) a modelling guide to make enterprise models using the metamodels proposed in this paper; (4) an extraction algorithm to discriminate the part of the CIM model to reuse; and (5) a set of transformation rules to reuse enterprise models to build Platform Independent Models. In addition, a case example is shown to validate the work that was carried out and to identify limitations

SOA and BPM, a Partnership for Successful Organizations

In order to stay effective and competitive, companies have to be able to adapt themselves to permanent market requirements, to improve constantly their business process, to act as flexible and proactive economic agents. To achieve these goals, the IT systems within the organization have to be standardized and integrated, in order to provide fast and reliable data access to users both inside and outside the company. A proper system architecture for integrating company’s IT assets is a service oriented one. A service-oriented architecture (SOA) is an IT architectural style that allows integration of the company’s business as linked, repeatable tasks called services. A subject closely related to SOA is Business Process Management (BPM), an approach that aims to improve business processes. The paper also presents some aspects of this topic, as well as the relationship between SOA and BPM. They complement each other and help companies improve their business performance.Information Systems, SOA, Web Services, BPM

A framework for developing engineering design ontologies within the aerospace industry

This paper presents a framework for developing engineering design ontologies within the aerospace industry. The aim of this approach is to strengthen the modularity and reuse of engineering design ontologies to support knowledge management initiatives within the aerospace industry. Successful development and effective utilisation of engineering ontologies strongly depends on the method/framework used to develop them. Ensuring modularity in ontology design is essential for engineering design activities due to the complexity of knowledge that is required to be brought together to support the product design decision-making process. The proposed approach adopts best practices from previous ontology development methods, but focuses on encouraging modular architectural ontology design. The framework is comprised of three phases namely: (1) Ontology design and development; (2) Ontology validation and (3) Implementation of ontology structure. A qualitative research methodology is employed which is composed of four phases. The first phase defines the capture of knowledge required for the framework development, followed by the ontology framework development, iterative refinement of engineering ontologies and ontology validation through case studies and experts’ opinion. The ontology-based framework is applied in the combustor and casing aerospace engineering domain. The modular ontologies developed as a result of applying the framework and are used in a case study to restructure and improve the accessibility of information on a product design information-sharing platform. Additionally, domain experts within the aerospace industry validated the strengths, benefits and limitations of the framework. Due to the modular nature of the developed ontologies, they were also employed to support other project initiatives within the case study company such as role-based computing (RBC), IT modernisation activity and knowledge management implementation across the sponsoring organisation. The major benefit of this approach is in the reduction of man-hours required for maintaining engineering design ontologies. Furthermore, this approach strengthens reuse of ontology knowledge and encourages modularity in the design and development of engineering ontologies

An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term

Ontology-based patterns for the integration of business processes and enterprise application architectures

Increasingly, enterprises are using Service-Oriented Architecture (SOA) as an approach to Enterprise Application Integration (EAI). SOA has the potential to bridge the gap between business and technology and to improve the reuse of existing applications and the interoperability with new ones. In addition to service architecture descriptions, architecture abstractions like patterns and styles capture design knowledge and allow the reuse of successfully applied designs, thus improving the quality of software. Knowledge gained from integration projects can be captured to build a repository of semantically enriched, experience-based solutions. Business patterns identify the interaction and structure between users, business processes, and data. Specific integration and composition patterns at a more technical level address enterprise application integration and capture reliable architecture solutions. We use an ontology-based approach to capture architecture and process patterns. Ontology techniques for pattern definition, extension and composition are developed and their applicability in business process-driven application integration is demonstrated

Multi-level requirement model and its implementation for medical device

Indiana University-Purdue University Indianapolis (IUPUI)Requirements determine the expectations for a new or modified product. Requirements engineering involves defining, documentation and maintenance of requirements. The rapid improving of technologies and changing of market needs require a shorter time to market and more diversified products. As an important and complex task in product development, it is a huge work to develop new requirements for each new product from scratch. The reusability of requirements data becomes more and more important. However, with the current “copy and paste” approach, engineers have to go through the entire set of requirements (sometimes even more than one set of requirements) to identify the ones which need to be reused or updated. It takes a lot of time and highly relies on the engineers’ experiences. Software tools can only make it easier to capture and locate the requirements, but won’t be able to solve the problem of effective reuse of the existing requirement data. The overall goal of this research is to develop a new model to improve the management of requirements and make the reuse and reconfiguration of existing requirements and requirement models more efficient. Considering the requirements data as an important part of the knowledge body of companies, we followed the knowledge categorization method to classify requirements into groups, which were called levels in the study, based on their changing frequency. There are four levels, the regulatory level, the product line level, the product level and the project level. The regulatory level is the most stable level. Requirements in this level were derived from government and industry regulations. The product line level contains the common requirements for a group of products, the product line. The third level, product level, refers to the specific requirements of the product. And the fourth and most dynamic level, the project level, is about the specific configurations of a product for a project. We chose auto-injector as the application to implement the model, since it is a relatively simple product, but its requirements cover many different categories. There are three major steps in our research approach for the project. The first is to develop requirements and classify them for our model. The development of requirements adopts the goal-oriented model to analyze and SysML, a system modeling language, to build requirements model. And the second step is to build requirements template, connecting the solution of the problem to the information system, standalone requirements management tool or information platform. This step is to find a way to realize the multi-level model in an information system. The final step is to implement the model. We chose two software tools for the implementation, Microsoft Office Excel, a commonly used tool for generating requirements documents, and Siemens PLM suite, Teamcenter, a world leading PLM platform with a requirement module. The results in the study include an auto-injector requirement set, a workflow for using the multi-level model, two requirements templates for implementation of the model in two different software tools, and two automatically generated requirement reports. Our model helps to define the changed part of requirements after analysis of the product change. It could avoid the pitfalls of the current way in reusing requirements. Based on the results from this study, we can draw the following conclusions. A practical multi-level requirements management model can be used for a medical device—the auto-injector; and the model can be implemented into different software tools to support reuse of existing requirement data in creating requirement models for new product development projects. Furthermore, the workflow and guideline to support the application and maintenance of the requirement model can be successful developed and implemented. Requirement documents/reports can be automatically generated through the software tool by following the workflow. And according to our assessment, the multi-level model can improve the reusability of requirements