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Current expert system technology tends to rely on the use of shallow empirically based experiential knowledge. With only this type of knowledge available, expert systems have been capable of reaching a high level of agreement with human experts in a limited area of expertise. However, due to the nature of their knowledge, such systems fall short of human expertise in many ways. The human diagnostic process is examined as it relates to the malfunction of mechanical and electrical devices. An expert system design is presented, called the integrated diagnostic model (IDM), that attempts to address some of the issues involved in bridging the gap between human and computer expertise. The IDM contains two different types of knowledge, one based on experience and one based on how the device to be diagnosed functions. These two types of knowledge are used together during a diagnostic session to determine what is wrong with the device. To demonstrate how the IDM works, an interaction with a prototype system that was built using the IDM is described; then research on extensions to the IDM is discussed.