Manufacturing Intelligence for Industrial Engineering: by Zude Zhou

By Zude Zhou

The producing has skilled dramatic swap through the years with growing to be developments, implementations, and functions in know-how. production Intelligence for commercial Engineering: tools for process Self-Organization, studying, and variation makes a speciality of the newest techniques for constructing, describing, integrating, sharing, and processing clever actions within the means of production in engineering. Containing examine from best foreign specialists, this e-book presents readers with medical foundations, theories, and key applied sciences of producing intelligence.

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For example, in the rule-based expert system for the diagnosis of infectious blood diseases, MYCIN, the relative experts act as teachers in knowledge acquisition, ask questions to the system MYCIN which is in student-mode, checks the answers that MYCIN gives out, find reasons for any error, and then amend the rules in the knowledge base. , 1979), also uses the knowledge editing tools. A knowledge acquisition system in teaching style requires a strong knowledge compiler, but general knowledge acquisition tools can only be described as ‘knowledge editor’.

21 Knowledge-Based System Table 1. A frame for lathe Lathe Type Structure The number of shafts Uniaxial, Multiaxial, etc The degree of automation Automatic, semi-automatic, manual, etc The largest swing diameter 320mm, 400mm, 600mm, etc Headstock Frame for headstock Electrical control cabinet Frame for Electrical control cabinet Lathe bed Frame for lathe bed Tool carrier Frame for tool carrier Tailstock Frame for tailstock … The content of the frame is a list of slots that define relationships to other frames which play significant roles in a particular situation.

If the formal evaluation is satisfactory and users can accept the system, then continue to Step 6: run the system in the prototype environment for a very long time. Evaluation during this period achieves extensive testing experience through carefully observing the program’s performance. If the operation in the prototype environment is ‘smooth’, then large-scale availability of the system should be further studied (Step 7). Before the system is introduced to user groups, relevant parameters, such as the system’s efficiency, cost-efficiency and so on, should be measured to determine the impact of the new environment on the system.

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