Improving transferability between different engineering stages in the development of automated material flow modules

For improving flexibility and robustness of the engineering of automated production systems (aPS) in case of extending, reducing or modifying parts, several approaches propose an encapsulation and clustering of related functions, e.g. from the electrical, mechanical or software engineering, based on a modular architecture. Considering the development of these modules, there are different stages, e.g. module planning or functional engineering, which have to be completed. A reference model that addresses the different stages for the engineering of aPS is proposed by AutomationML. Due to these different stages and the integration of several engineering disciplines, e.g. mechanical, electrical/electronic or software engineering, information not limited to one discipline are stored redundantly increasing the effort to transfer information and the risk of inconsistency. Although, data formats for the storage and exchange of plant engineering information exist, e.g. AutomationML, fixed domain specific structures and relations of the information, e.g. for automated material flow systems (aMFS), are missing. This paper presents the integration of a meta model into the development of modules for aMFS to improve the transferability and consistency of information between the different engineering stages and the increasing level of detail from the coarse-grained plant planning to the fine-grained functional engineering.Comment: 11 pages, https://ieeexplore.ieee.org/abstract/document/7499821

An Ontological Framework for Representing Clinical Knowledge in Decision Support Systems, Journal of Telecommunications and Information Technology, 2014, nr 1

In the last decades, clinical evidence and expert consensus have been encoded into advanced Decision Support Systems (DSSs) in order to promote a better integration into the clinical workflow and facilitate the automatic provision of patient specific advice at the time and place where decisions are made. However, clinical knowledge, typically expressed as unstructured and free text guidelines, requires to be encoded into a computer interpretable form suitable for being interpreted and processed by DSSs. For this reason, this paper proposes an ontological framework, which enables the encoding of clinical guidelines from text to a formal representation, in order to allow querying, advanced reasoning and management in a well defined and rigorous way. In particular, it jointly manages declarative and procedural aspects of a standards based verifiable guideline model, named GLM-CDS (GuideLine Model for Clinical Decision Support), and expresses reasoning tasks that exploit such a represented knowledge in order to formalize integrity constraints, business rules and complex inference rules

Journal of Telecommunications and Information Technology, 2014, nr 1

kwartalni

Solution Workflows for Model-Based Analysis of Complex Systems

The development and analysis of increasingly complex systems require the intensive use of models and of sophisticated approaches to systems modeling. This paper focuses on workflows supporting the solution of complex, composed, formal models used to study and/or develop real-world systems. The workflows we deal with orchestrate multiple distributed tools and applications in order to provide the user with a powerful, composed solution environment. The aim is to automate and reproduce analysis and simulation tasks starting from a high level, graph-based description of the model to be solved. This paper thus introduces solution workflows and presents the Solution Process Definition Language (SPDL) for the specification of solution workflows processes. One of the key elements of SPDL is its formal semantics, which allow for unambiguous specification of its constructs and validation of the workflows. A workflow pattern analysis of SPDL is also provided. SPDL and its execution environment, the OsMoSys framework, are then applied to a homeland security scenario. The OsMoSys framework and the SPDL language provide a practical contribution to the applicability of model engineering techniques by enabling the semiautomatic solution of complex models