Peter O. Denno

An Analysis of Existing Ontological Systems for Applications in Manufacturing and Healthcare

The objective of the work described in this paper is to move closer to the ultimate goal of seamless system integration using the principle behind ontological engineering to unambiguously define domain-specific concepts. A major challenge facing industry today is the lack of interoperability between heterogeneous systems. This challenge is apparent in many sectors, including both healthcare and manufacturing. Current integration efforts are usually based solely on how information is represented (the syntax) without a description of what the information means (the semantics). With the growing complexity of information and the increasing need to completely and correctly exchange information among different systems, the need for precise and unambiguous capture of the meaning of concepts within a given system is becoming apparent.

Lessons learned developing protocols for the industrial virtual enterprise

Abstract The protocols selected and developed by the NIIIP Consortium have been validated in three end-of-cycle demonstrations. In each cycle, a team with expertise in technical product data, object modeling, workflow management, security, and knowledge representation came together and demonstrated how technical barriers to the dynamic creation, operation and dissolution of “virtual enterprises” are overcome by the NIII protocols. This paper describes the protocols that were selected and developed by the product data team and makes predictions about how they will affect the future development and deployment of standard product data.

An analysis and approach to using existing ontological systems for applications in manufacturing

This paper reports on the results of an analysis of existing ontological systems to determine which is most appropriate for the manufacturing domain. In particular, this involved the exploration of efforts that are studying both the uses of ontologies in the general sense and those that are using ontologies for domain-specific purposes. Eleven ontological systems were analyzed and, using a set of analysis criteria, it was determined that the Cyc (Cyc is a registered trademark of Cycorp Inc.) system was most appropriate for modeling concepts in the manufacturing domain. After the analysis is described, examples are given to show how manufacturing concepts could be modeled in the Cyc system. This work is part of a larger project whose objective is to move closer to the ultimate goal of seamless manufacturing systems integration using the principle behind ontological engineering to unambiguously define domain-specific concepts. The output of this work will be a taxonomy of manufacturing terms and concepts along with formal definitions of exactly what each of those terms and concepts mean and how they interrelate.

Model-driven integration using existing models

Models can describe business transactions in terms of business entities and help automate some systems integration tasks. The joint action model describes a new business transaction motivating systems integration.

Using Semantic Web Technologies for Integrating Domain Specific Modeling and Analytical Tools

Abstract This paper discusses the potential advantages and pitfalls of using semantic web technologies for representing and integrating modeling and analysis tools. Analytical tools are often not designed to be integrated with information sources and general-purpose modeling tools, and often do not support detection of problems across domains. Additionally, these modeling tools may not capture and represent explicitly the information needed to leverage the capabilities of analysis tools. The method described uses semantic web technology as the integrating mechanism between domain specific modeling (DSM) tools and analytical tools. We describe a method and tool set for representing the analytical knowledge through semantic web ontologies that map between the metamodels of both the DSM and analytical tools. We compare an earlier tool-chain prototype with a significantly revised prototype to reflect on the benefits from using semantic web technologies as an integrating mechanism. A potential advantage is the ability to represent the relationships between modeling and analytical tools explicitly and transparently.

Multi-job production systems: definition, problems, and product-mix performance portrait of serial lines

Abstract This paper pursues two goals: (a) Define a class of widely used in practice flexible manufacturing systems, referred to as Multi-Job Production (MJP) and formulate industrially motivated problems related to their performance. (b) Provide initial results concerning some of these problems pertaining to analysis of the throughput and bottlenecks of MJP serial lines as functions of the product-mix. In MJP systems, all job-types are processed by the same sequence of manufacturing operations, but with different processing time at some or all machines. To analyse MJP with unreliable machines, we introduce the work-based model of production systems, which is insensitive to whether single- or multi-job manufacturing takes place. Based on this model, we investigate the performance of MJP lines as a function of the product-mix. We show, in particular, that for the so-called conflicting jobs there exists a range of product-mixes, wherein the throughput of MJP is larger than that of any constituent job-type manufactured in a single-job regime. To characterise the global behaviour of MJP lines, we introduce the Product-Mix Performance Portrait, which represents the system properties for all product-mixes and which can be used for operations management. Finally, we report the results of an application at an automotive assembly plant.

Integrating views of properties in models of unit manufacturing processes

This paper investigates the potential advantages and difficulties of integrating predictive model equations in models of unit manufacturing processes. The method described uses metamodels and semantic web technology to relate equations, as objects, to downstream activities. The potential advantages of this include enhanced knowledge refinement and reuse, traceability, model verification and agility in production activities. In an example usage, the authors apply the method to the development and downstream usage of predictive models of a selective laser sintering process. Use of equations as objects enables linking them with supporting evidence, property definitions and dimensions in an engineering notebook paradigm. Model-based interpretation of the equations enables composition in trade studies and mapping to downstream process parameter optimisation.

Virtual Design and Verification of Cyber Physical Systems: Industrial Process Plant Design

Abstract This paper discusses a research project to support virtual design and verification of industrial process plant designs. Process plants are a class of cyber-physical systems (CPS), and these research results should generally apply to other types of CPS such as those associated with the Smart Grid. Modeling is an essential part of process plant design and integral in other applications such as manufacturing. Models produced in design have obvious roles in system implementation, deployment and certification. For manufacturing systems, models also have use in downstream activities including system certification, performance optimization, real-time diagnostics and prognostics, and maintenance. The paper discusses the results associated with a prototype that uses domain-specific models of different views of a system design that improves collaboration through integrated models and aligned semantics and provides examples of how the integration with formal methods can identify defects in designs, and automatically generate test vectors with requirement-to-test traceability.

Requirements on information technology for product lifecycle management

Good decision-making is founded on good information. Information technology supporting product lifecycle management ought to provide a high degree of information cohesion and traceability – knowledge of the interrelations among data, and basis for belief. Providing cohesion and traceability is made difficult by differences in viewpoint and ontology employed by the various disciplines and organisations involved in the product lifecycle. This paper describes an analysis of cohesion and traceability into its constituents properties. The paper suggests that process-aware integration schema can improve the cohesion and traceability among product data.

Systems Engineering Foundations of Software Systems Integration

This paper considers systems engineering processes for software systems integration. Systems engineering processes, as intended here, concern how engineering capability should be factored into problem-solving agencies for performance of software systems integration tasks. Systems engineering processes also concern how the results produced by these agencies should be communicated and integrated into a system solution. The environment in which systems integration takes place is assumed to be model-driven. In the proposed solution, problemsolving agencies, working from various viewpoints, employ differing notations and analytical skills. In the course of identifying the systems engineering process, the paper presents a conceptual model of systems engineering, and reviews a classification of impediments to software systems integration.