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Expert system selection method for SMT placement equipment.

机译：SMT贴装设备的专家系统选择方法。

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摘要

Introduction. Until recently, evaluation of Surface Mount Technology (SMT) placement equipment consisted of selecting the machine capable of meeting requirements without regard to price or other factors. Today, several manufacturers offer capable and reliable equipment making additional analysis necessary. No comprehensive evaluation model exists for SMT and mistakes in equipment selection are often made. Common evaluation errors are: limiting analysis to financial factors, use of inappropriate methods, use of incomparable specifications, evaluation with missing information, and overestimation of equipment capacity. Incorrect selection analysis leads to disappointment with equipment capabilities and performance.; Methodology. A selection method has been developed for SMT. The evaluation uses a multi-attribute approach consisting of financial and non-financial factors. Financial evaluation is performed with a modified cost per placement calculation. Non-financial and multi-attribute ratings are determined using an aggregated utility function. Several heuristic rules are applicable to SMT equipment evaluation making traditional computer languages inappropriate. An artificial intelligence language and expert system methodology is used to manage the heuristic rules. The system works in three steps: capability matching, quantifiable performance assessment, and non-monetary performance assessment. The system determines the multi-attribute machine ratings, sorts by that rating, and presents a listing of recommended equipment. The program is in a decision support system format that performs calculations and makes recommendations but leaves the user in control to make the selection.; Results. Equipment recommendations made by the system differ from those of simpler evaluation methods. SMT experts surveyed agree that the system recommendations reflect expertise in the subject domain and that the financial model is a significant improvement to the cost per placement rating commonly used. The system has three significant advantages over current selection methods for SMT. First, the evaluation method is more accurate than current models. Second, knowledge of SMT machine capabilities is available through a system database which eliminates the need for prior research. Third, the system is the first fully functional expert system for equipment selection or justification in any domain.
机译：介绍。直到最近，对表面贴装技术（SMT）贴装设备的评估包括选择能够满足要求而无需考虑价格或其他因素的机器。如今，一些制造商提供了功能强大且可靠的设备，因此有必要进行额外的分析。没有针对SMT的综合评估模型，并且经常会在设备选择上犯错误。常见的评估错误包括：将分析限制于财务因素，使用不合适的方法，使用无法比拟的规格，在缺少信息的情况下进行评估以及对设备容量的高估。错误的选择分析会导致对设备功能和性能的失望。方法。已经为SMT开发了一种选择方法。评估使用了由财务和非财务因素组成的多属性方法。财务评估是根据修改后的每次展示费用计算进行的。使用汇总效用函数确定非财务和多属性评级。一些启发式规则适用于SMT设备评估，从而使传统计算机语言不合适。人工智能语言和专家系统方法用于管理启发式规则。该系统分三个步骤工作：能力匹配，可量化的绩效评估和非货币绩效评估。系统确定多属性机器的等级，按该等级排序，并显示推荐设备的列表。该程序采用决策支持系统格式，可以执行计算并提出建议，但让用户可以控制选择。结果。系统提出的设备建议与较简单的评估方法不同。接受调查的SMT专家同意，系统建议反映了主题领域的专业知识，并且财务模型对常用的每次安置费用进行了重大改进。与当前的SMT选择方法相比，该系统具有三个重要优势。首先，评估方法比当前模型更准确。其次，可通过系统数据库获得SMT机器功能的知识，从而无需进行先前的研究。第三，该系统是在任何领域进行设备选择或证明的第一个全功能专家系统。

著录项

  • 作者

    Price, Donald D.;

  • 作者单位

    State University of New York at Binghamton.;

  • 授予单位 State University of New York at Binghamton.;
  • 学科 Engineering Industrial.
  • 学位 Ph.D.
  • 年度 1992
  • 页码 169 p.
  • 总页数 169
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 一般工业技术;
  • 关键词

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