Towards Industrial Strength Business Performance Management

Abstract. Business performance management today does not possess a rigorous and grounded engineering methodology capable of delivering reliably measured values to backing up decision making. Much more it is the art of executive gurus who listen to their backbone experience and take their decisions using intuitive and heuristic approaches. This vagueness appears to be one of the main reasons for current dissatisfaction in industry. In this paper we express our vision of how a rigorous engineering methodology for business performance management in engineering design may look like. Our research work in PSI 1 and PRODUKTIV+ 2 projects strongly suggests that the underlying modeling framework has to be holonic. We consider that the solution has to: (i) be based on a sound Domain ontology of performance; (ii) use dynamic distributed planning technique and simulations to predict the performance of a design system; (iii) use the methodology which is sensitive to the specificities of a particular design system.

Evaluating PSI Ontologies by Mapping to the Common Sense

Abstract: The paper presents the results of mapping of PSI Ontologies family to the foundational ontologies: WordNet, SUMO and DOLCE. The two main outcomes of the presented research are: reported manual technique may be used as initial evaluation of ontology claiming to be gold standard for a new domain; and: usage of mentioned foundational ontologies for alignment of ontologies family of a given domain has shown differences between SUMO and DOLCE, two formal upper-level ontologies of common sense knowledge. The research reported was performed in the frame of our PSI project 1.

AN APPROACH FOR ASSESSING DESIGN SYSTEMS Design System Simulation and Analysis for Performance Assessment

design process, ontology, multi-agent system, microelectronics Abstract: This position paper presents our work in assessing engineering design systems in the field of microelectronics with respect to their performance and, more specifically, to productivity. Current mainstream process assessment systems show deficiencies of the representation and analysis when dealing with dynamic, self-optimizing processes. To overcome this, a project called PRODUKTIV+ has been created with the goal to develop a new approach. This approach is to create a model of a design system and simulate the colaborative behavior of the involved engineers using a system of cooperating, intelligent software agents. The assessment of a design system is then done based on the detailed simulation results.

Automated Instance Migration between Evolving

Abstract: An ontology, if used for practical purposes like in information systems, contains its controlled vocabulary (TBox) describing the semantics of the domain and the set of facts (ABox) about this domain. The elements of the ABox are ontology instances. If a domain is described by two or more different ontologies or if ontologies evolve, TBoxes are the first place to analyze the differences. However, even if the corresponding TBoxes are mapped to each other, ABox alignment is still required to be done. Though TBoxes may be aligned manually, the size of the corresponding ABoxes may well be a serious obstacle for feasibly finishing the job by hand. The paper presents our approach and recent research accomplishments in developing a methodology for solving this complex task semiautomatically. We call it Ontology Instance Migration Methodology (OIMM). It allows reducing the bulk of manual work in aligning one ontology to another one. Our simplified task is to populate the second one with the instances taken from the first one. We first build mappings between the TBoxes, then we proceed with creating an Ontology Instance Migration Scenario (OIMS) using the algorithm presented in this paper and the previously created mappings. We review the OIMS to validate it, edit incomplete and add missed transformations. Such manual additions are necessary to encode complex transformations. We finally execute the OIMS using the environment which performs the instance migration.