Developing A Dialogue Based Knowledge Acquisition Method For Automatically Acquiring Expert Knowledge To Diagnose Mechanical Assemblies
Mechanical assembly is an important step during product realization, which is an integrative process that brings together the parts of the assembly, the people performing the assembly and the various technologies that are involved. Assembly planning involves deciding on the assembly sequence, the tooling and the processes to be used. Assembly planning should enable the actual assembly process to be as effective as possible.Assembly plans may have to be revised due to issues arising during assembly. Many of these revisions can be avoided at the planning stage if assembly planners have prior knowledge of these issues and how to resolve them. General guidelines to make assembly easier (e.g. Design for Assembly) are usually suited for mass-manufactured assemblies and are applied where similar issues are faced regularly. However, for very specific issues that are unique to some domains only, such as aircraft assembly, only expert knowledge in that domain can identify and resolve the issues. Assembly experts are the sources of knowledge for identifying and resolving these issues. If assembly planners could receive assembly experts’ advice about the potential issues and resolutions that are likely to occur in a given assembly situation, they could use this advice to revise the assembly plan in order to avoid these issues. This link between assembly experts and planners can be provided using knowledge based systems. Knowledge-based systems contain a knowledge base to store experts’ knowledge, and an inference engine that derives certain conclusions using this knowledge. However, knowledge acquisition for such systems is a difficult process with substantial resistance to being automated. Methods reported in literature propose various ways of addressing the problem of automating knowledge acquisition. However, there are many limitations to these methods, which have been the motivations for the research work reported in this thesis. This thesis proposes a dialog-like method of questioning an expert to automatically acquire knowledge from assembly experts. The questions are asked in the context of an assembly situation shown to them. During the interviews, the knowledge required for diagnosing potential issues and resolutions are identified. The experts were shown a situation, and asked to identify issues and suggest solutions. The above knowledge is translated into the rules for a knowledge based system. This knowledge based system can then be used to advise assembly planners about potential issues and solutions in an assembly situation. After a manual verification, the questioning procedure has been implemented on computer as a software named EXpert Knowledge Acquisition and Validation (ExKAV). A preliminary evaluation of ExKAV has been carried out, in which assembly experts interacted with the tool using the researcher as an intermediary. The results of these sessions have been discussed in the thesis and assessed against the original research objectives. The current limitations of the procedure and its implementation have been highlighted, and potential directions for improving the knowledge acquisition process are discussed.
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