Feng Shaw C, Bernstein William Z, Hedberg Thomas, Feeney Allison Barnard
Systems Integration Division, Engineering Laboratory, National Institute of Standards and Technology, 100 Bureau Drive, MS 8260,
J Comput Inf Sci Eng. 2017 Sep;17(3). doi: 10.1115/1.4037178. Epub 2017 Jul 24.
The need for capturing knowledge in the digital form in design, process planning, production, and inspection has increasingly become an issue in manufacturing industries as the variety and complexity of product lifecycle applications increase. Both knowledge and data need to be well managed for quality assurance, lifecycle-impact assessment, and design improvement. Some technical barriers exist today that inhibit industry from fully utilizing design, planning, processing, and inspection knowledge. The primary barrier is a lack of a well-accepted mechanism that enables users to integrate data and knowledge. This paper prescribes knowledge management to address a lack of mechanisms for integrating, sharing, and updating domain-specific knowledge in smart manufacturing. Aspects of the knowledge constructs include conceptual design, detailed design, process planning, material property, production, and inspection. The main contribution of this paper is to provide a methodology on what knowledge manufacturing organizations access, update, and archive in the context of smart manufacturing. The case study in this paper provides some example knowledge objects to enable smart manufacturing.
随着产品生命周期应用的多样性和复杂性不断增加,在设计、工艺规划、生产和检验中以数字形式获取知识的需求在制造业中日益成为一个问题。为了确保质量、进行生命周期影响评估和改进设计,知识和数据都需要得到妥善管理。目前存在一些技术障碍,阻碍行业充分利用设计、规划、加工和检验知识。主要障碍是缺乏一种被广泛接受的机制,使得用户能够整合数据和知识。本文规定了知识管理,以解决智能制造中缺乏集成、共享和更新特定领域知识的机制的问题。知识结构的方面包括概念设计、详细设计、工艺规划、材料特性、生产和检验。本文的主要贡献是提供一种方法,说明智能制造组织在何种情况下获取、更新和存档知识。本文中的案例研究提供了一些示例知识对象,以实现智能制造。