Study On Product Design Knowledge Modeling Methods For Decision Making

Engineering product design is fundamentally a decision making process,the principal role of a designer is to make decisions.Design decisions especially those early stage decisions have a great impact on the life-cycle cost and quality of the final product.To augment human designers' decision making ability in order to generate quality designs,relevant decision support is critically important.Effective and adequate decision support depends on the integration of two perspective,namely,analytical decision constructs and knowledge(or information)sources.While,the two most representative research threads,namely,Decision Based Design(DBD)and Knowledge Based Engineering(KBE),that are derived from the aforementioned perspectives respectively have been through two separate paths.DBD emphasizes providing mathematical decision analysis methods without taking into consideration knowledge availability,while KBE concentrates on knowledge management and supply but is short of providing decision making mechanisms.In order to address the gap between DBD and KBE thus provide effective and adequate decision support,this dissertation proposes a systematic knowledge modeling method for engineering design decisions.The resulting knowledge models are created by the integration of analytical decision constructs and domain specific knowledge.Based on the knowledge models a knowledge-based decision support platform is developed.The knowledge models as well as the decision support platform are validated through practical design examples.Contribution of this dissertation lies in the following aspects.(1)A theoretical framework for comprehensive knowledge-based decision support.In order to provide effective and adequate decision support for the diverse and complex decision-based design processes,a theoretical,knowledge-based decision support framework is proposed.Within the framework,an unified description for different decision-based design processes is first provided from a macro perspective using the Design Equation and the Design Process Template.Then,the Decision Support Problem(DSP)constructs are used to model the two basic types of decisions,namely,selection and compromise,and decisions coupled from these two types during the design process.Finally,the decision related knowledge is represented using ontology from a computational level.In this framework,knowledge-based support is provided to design decisions and the macro design process from a bottom-up direction.(2)A knowledge model for selection decisions.In order to provide knowledge support for multi-attribute selection decisions under uncertainty,a knowledge model based on the utility-based selection DSP(u-sDSP)is proposed.The selection decision knowledge model is structured as an executable and reusable template,and represented using a frame-based ontology.In the model,domain dependent declarative knowledge including alternatives,attributes,utility functions,etc.and domain independent procedural knowledge including utility function creation,expected utility calculation,post-solution sensitivity analysis,etc.is separately modeled to ensure knowledge reuse in selection decisions.The effectiveness of the selection decision knowledge model is validated through a light switch cover plate rapid prototyping resource selection example.(3)A knowledge model for compromise decisions.In order to provide knowledge support for multi-objective compromise decisions,a knowledge model based on the compromise DSP(cDSP)is proposed.The compromise decision knowledge model is structured as an executable and reusable template,and represented using a frame-based ontology.In the model,domain dependent declarative knowledge including parameters,variables,constraints,goals and preferences etc.and domain independent procedural knowledge including cDSP resolution,multi-objective tradeoff analysis,and solution space visualization,etc.is separately modeled to ensure knowledge reuse in compromise decisions.The effectiveness of the compromise decision knowledge model is validated through a thin-walled pressure vessel redesign example.(4)A knowledge model for hierarchical coupled decisions.In order to provide knowledge support for multi-level hierarchical coupled decisions,a knowledge model based on the coupled DSP(coDSP)is proposed.The model is built on the basis of the selection and compromise decision templates and ontologies.Key to the model are two Classes,namely,“ Process” which represents the basic hierarchy building blocks where the DSPs are embedded,and “ Interface” which represents the DSP information flows that link different “ Processes” to a hierarchy.The effectiveness of the hierarchical coupled decision knowledge model is validated through a portal frame design example.(5)A Knowledge-Based Platform for Decision Support in the Design of Engineering systems(PDSIDES).PDSIDES is a platform developed based on the framework and knowledge models proposed above.It integrates analytical decision making constructs(inluding u-sDSP,cDSP and coDSP)and domain specific knowledge,and has the repository that stores the knowledge instances instantiated from the decision templates.PDSIDES is supposed to provide decision support for designers of different knowledge levels including domain experts,senior designers and novice designers,in original design,adaptive design and variant design,respectively.The results of the test performed on PDSIDES through three practical examples show that PDSIDES is an effective tool for decision support.