Functional and Behavioral Product Information Representation and Consistency Validation for Collaboration in Product Lifecycle Activities

Information models that represent the function, assembly and behavior of artifacts are critical in the conceptual development of a product and its evaluation. Much research has been conducted in this area; however, existing models do not relate function, behavior and structure in a comprehensive and consistent way. In this work, NIST\u27s Core Product Model (CPM) and the Open Assembly Model (OAM) are extended to integrate product information including function and behavior, with an emphasis on assembly, throughout all phases of product development. For function and flow classification, the NIST functional taxonomy is used to maintain consistency with the literature. The consistency validation of product information, and the verification of modified product information are discussed; these processes ensure that the product information has no contradictions and allows tracing through associations without any deficiency or disconnection. In other words, the information model has to be complete in terms of traceability of function, behavior, spatial relationships, etc., in order to support all information exchange activities. The product information representation provides a mechanism for capturing product information and storing it in a database. This representation schema also provides necessary information for any future decision making activities in the End of Life (EOL) environment, such as the replacement or reuse of any part or subassembly. When there is a need to replace one artifact with another, one must consider all of the associations of the existing artifact with other artifacts and the environment, not just functional and space requirements, and the relevant modification(s) of the associated objects has to verified. So one can manage product lifecycle activities in different perspectives by knowing how the product information is interconnected in various domains and how its characteristics affect each other

Powertrain Assembly Lines Automatic Configuration Using a Knowledge Based Engineering Approach

Technical knowledge and experience are intangible assets crucial for competitiveness. Knowledge is particularly important when it comes to complex design activities such as the configuration of manufacturing systems. The preliminary design of manufacturing systems relies significantly on experience of designers and engineers, lessons learned and complex sets of rules and is subject to a huge variability of inputs and outputs and involves decisions which must satisfy many competing requirements. This complicated design process is associated with high costs, long lead times and high probability of risks and reworks. It is estimated that around 20% of the designer’s time is dedicated to searching and analyzing past available knowledge, while 40% of the information required for design is identified through personally stored information. At a company level, the design of a new production line does not start from scratch. Based on the basic requirements of the customers, engineers use their own knowledge and try to recall past layout ideas searching for production line designs stored locally in their CAD systems [1]. A lot of knowledge is already stored, and has been used for a long time and evolved over time. There is a need to retrieve this knowledge and integrate it into a common and reachable framework. Knowledge Based Engineering (KBE) and knowledge representation techniques are considered to be a successful way to tackle this design problem at an industrial level. KBE is, in fact, a research field that studies methodologies and technologies for capturing and re-using product and process engineering knowledge to achieve automation of repetitive design tasks [2]. This study presents a methodology to support the configuration of powertrain assembly lines, reducing design times by introducing a best practice for production systems provider companies. The methodology is developed in a real industrial environment, within Comau S.p.A., introducing the role of a knowledge engineer. The approach includes extraction of existing technical knowledge and implementation in a knowledge-based software framework. The macro system design requirements (e.g. cycle time, production mix, etc.) are taken as input. A user driven procedure guides the designer in the definition of the macro layout-related decisions and in the selection of the equipment to be allocated within the project. The framework is then integrated with other software tools allowing the first phase design of the line including a technical description and a 2D and 3D CAD line layout. The KBE application is developed and tested on a specific powertrain assembly case study. Finally, a first validation among design engineers is presented, comparing traditional and new approach and estimating a cost-benefit analysis useful for future possible KBE implementations

Manufacturing systems interoperability in dynamic change environments

The benefits of rapid i.e. nearly real time, data and information enabled decision making at all levels of a manufacturing enterprise are clearly documented: the ability to plan accurately, react quickly and even pre-empt situations can save industries billions of dollars in waste. As the pace of industry increases with automation and technology, so the need for accurate, data, information and knowledge increases. As the required pace of information collection, processing and exchange change so to do the challenges of achieving and maintaining interoperability as the systems develop: this thesis focuses on the particular challenge of interoperability between systems defined in different time frames, which may have very different terminology. This thesis is directed to improve the ability to assess the requirement for systems to interoperate, and their suitability to do so, as new systems emerge to support this need for change. In this thesis a novel solution concept is proposed that assesses the requirement and suitability of systems for interoperability. The solution concept provides a mechanism for describing systems consistently and unambiguously, even if they are developed in different timeframes. Having resolved the issue of semantic consistency through time the analysis of the systems against logical rules for system interoperability is then possible. The solution concept uses a Core Concept ontology as the foundation for a multi-level heavyweight ontology. The multiple level ontology allows increasing specificity (to ensure accuracy), while the heavyweight (i.e. computer interpretable) nature provides the semantic and logical, rigour required. A detailed investigation has been conducted to test the solution concept using a suitably dynamic environment: Manufacturing Systems, and in particular the emerging field of Manufacturing Intelligence Systems. A definitive definition for the Manufacturing Intelligence domain, constraining interoperability logic, and a multi-level domain ontology have been defined and used to successfully prove the Solution Concept. Using systems from different timeframes, the Solution concept testing successfully identified systems which needed to interoperate, whether they were suitable for interoperation and provided feedback on the reasons for unsuitability which were validated as correct against real world observations