Michalis Miatidis

Ontology-Based information management in design processes

Abstract Engineering design processes are highly creative and knowledge-intensive tasks that involve extensive information exchange and communication among diverse developers. In such dynamic settings, traditional information management systems fail to provide adequate support due to their inflexible data structures and hard-wired usage procedures, as well as their restricted ability to integrate processes and product information. In this paper, we advocate the idea of Process Data Warehousing as a means to provide an information management and integration platform for such design processes. The key idea behind our approach is a flexible ontology-based schema with formally defined semantics that enables the capture and reuse of design knowledge, supported by advanced computer science methods.

Using Developers' Experience in Cooperative Design Processes

The process industries are characterized by continuous or batch processes of material transformation with the aim of converting raw materials or chemicals into more useful and valuable forms. The design of such processes is a complex process itself that determines the competitiveness of these industries, as well as their environmental impact. Especially the early phases of such design processes, the so-called conceptual design and basic engineering, reveal an inherent creative character that is less visible in other engineering domains, such as in mechanical engineering. This special character constitutes a key problem largely impacting final product quality and cost. As a remedy to this problem, in cooperation with researchers and industrial partners from chemical and plastics engineering, we have developed an approach to capture and reuse experiences captured during the design process. Then, fine-grained method guidance based on these experiences can be offered to the developer through his process-integrated tools. In this section, we describe the application of our approach on the case study of the IMPROVE project. We first report on experiments made with a prototypical implementation of an integrated design support environment in the early project phases, and successively describe how it has been reengineered and extended based on additional requirements and lessons learned.

Media-assisted product and process traceability in supply chain engineering

Many engineering domains involve an intricate interplay of conceptual synthesis of alternative requirements and design configurations, preliminary impact analysis of these alternatives using complex simulations and multimedia visualizations, and human decision-making. Design traceability in such settings must be both product-oriented and process-oriented: it must enable an efficient media-based comparison of product alternatives from the current project or related experiences, and it must facilitate reuse of modeling experiences to avoid unnecessary repetition of negative experiences. We have studied these problems in a large interdisciplinary project whose aim it is to optimize supply chains linking chemical engineering, plastics engineering, and related application demands e.g. in the automotive industry. A number of novel experience reuse tools have been designed and implemented as part of a process-integrated modeling environment.

Media-assisted product and process requirements traceability in supply chains

Requirements engineering for technical systems involves an intricate interplay of conceptual synthesis of alternative requirements and design configurations, preliminary impact analysis of these alternatives using complex simulations and multimedia visualizations, and human decision-making based on goal trade-offs. Requirements traceability in such settings must be both product- and process-oriented: it must enable an efficient media-based comparison of product alternatives from the current project or related experiences, and it must facilitate reuse of analysis process experiences to avoid unnecessary repetition of negative experiences. We study these problems in a large interdisciplinary project whose aim it is to optimize the innovation supply chains linking chemical engineering, plastics engineering, and application goals e.g. in the automotive industry.

Work Processes and Process-Centered Models and Tools

The first vertical column of the layered process/product model (PPM) addresses the direct, experience-based support at the technical workplaces of designers. More specifically, we demonstrate the transition from application domain models to executable tool models, focussing on the process perspective of the PPM. This vertical column is jointly realized by the A1 subproject, providing the fine-grained application domain models, and the B1 subproject, dealing with their conversion to executable tool models to be used by process-integrated tools. In this contribution, we provide an outline of the cooperation results.

Process integration and media-assisted traceability in cross-organisational engineering

Many engineering domains involve an intricate interplay of conceptual synthesis of alternative requirements and design configurations, preliminary impact analysis of these alternatives using complex simulations and multimedia visualisations and human decision-making. Design traceability in such settings must be both product-oriented and process-oriented: it must enable an efficient media-based comparison of product alternatives from the current project or related experiences, and it must facilitate the reuse of modelling experiences to avoid unnecessary repetition of costly experiences. We have studied these problems in a large interdisciplinary project. Its aim is to optimise cross-organisational engineering tasks linking chemical engineering, plastics engineering and related application demands, for example, in the automotive industry. The solution presented in this paper integrates ideas from scenario-based modelling, process integration and ontology-based management of multimedia artefacts.

Management and Reuse of Experience Knowledge in Extrusion Processes

Extrusion of rubber profiles, e.g., for the automotive industry, is a highly complex continuous production process which is nevertheless influenced strongly by variability in input materials and other external conditions. As analytical models exist only for small parts of such processes, experience continues to play an important role here, very similar to the situation in the early phases of process engineering studied in CRC IMPROVE. This section therefore describes a transfer research project called MErKoFer conducted jointly with an industrial application partner and a software house founded by former CRC members. In MErKoFer, results from the CRC projects on direct process support (B1, see Sect. 3.1), process data warehousing (C1, Sect. 4.1), and plastics engineering (A3, see Sect. 5.4) were applied and extended. Specifically, knowledge about extrusion processes is captured by ontology-based traceability mechanisms for both direct process support of extrusion operators, and for process analysis and improvement based on an integration of data mining techniques. The accumulated knowledge assists in ensuring defined quality standards and in handling production faults efficiently and effectively. The approach was experimentally implemented and evaluated in the industrial partners site, and some generalizable parts of the environment were taken up by the software house partner in their aiXPerience software environment for process automation and process information systems.

Toward improvement-oriented reuse of experience in engineering design processes

Engineering design processes are hard to support. The creativity, complexity and unpredictability characterizing them complicate the identification and formalization of their fine-grained process knowledge. Process support should therefore alleviate this shortcoming by eliciting new engineering ways of working and improving the existing ones based on substantial experiences captured during process execution. This paper discusses a process improvement approach pointing toward this direction. An adapted experience factory infrastructure, by continuously monitoring the process execution, infers new ways of working using a case-based approach and provides improvement support on both a project and a corporate basis. The presented solution integrates ideas from case-based reasoning, requirements engineering and software engineering.