Combined manufacturing and cost complexity scores-based process selection for hybrid manufacturing

M. Tlija, A. Al-Tamimi
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引用次数: 1

Abstract

Smart manufacturing involves the use of emergent technologies and requires dynamic feedback of customer’s demands. These concerns need a rapid Decision Support System (DSS) considering emergent manufacturing processes such as Additive (AM) and Hybrid (HM) Manufacturing and tracking the product changes. This paper proposes a DSS for process selection based on manufacturing complexity and cost. The complexity parameters, deduced from design for manufacturing (DFM), design for additive manufacturing (DFAM) and design for hybrid manufacturing (DFHM) rules, are automatically extracted from computer aided design (CAD) model to follow the product changes. Cost models are defined for each manufacturing process type. In design phase, the manufacturing cost estimation allows considering the cost as a selection factor. The combined complexity based on manufacturing difficulty and cost represents a new paradigm for process selection. The case studies show the reliability of the proposed DSS and its ability to respect the company resources and strategy.
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基于成本复杂性分数的混合制造工艺选择
智能制造涉及新兴技术的使用,需要对客户需求进行动态反馈。这些问题需要一个快速决策支持系统(DSS)来考虑紧急制造过程,如增材制造(AM)和混合制造(HM),并跟踪产品变化。提出了一种基于制造复杂性和成本的工艺选择决策支持系统。从制造设计(DFM)、增材制造设计(DFAM)和混合制造设计(DFHM)规则中推导出的复杂性参数,从计算机辅助设计(CAD)模型中自动提取,以跟踪产品的变化。为每种制造过程类型定义了成本模型。在设计阶段,制造成本估算允许将成本作为一个选择因素来考虑。基于制造难度和成本的复合复杂性代表了工艺选择的新范式。案例研究表明了所提出的决策支持系统的可靠性和尊重公司资源和战略的能力。
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来源期刊
CiteScore
5.10
自引率
30.80%
发文量
167
审稿时长
5.1 months
期刊介绍: Manufacturing industries throughout the world are changing very rapidly. New concepts and methods are being developed and exploited to enable efficient and effective manufacturing. Existing manufacturing processes are being improved to meet the requirements of lean and agile manufacturing. The aim of the Journal of Engineering Manufacture is to provide a focus for these developments in engineering manufacture by publishing original papers and review papers covering technological and scientific research, developments and management implementation in manufacturing. This journal is also peer reviewed. Contributions are welcomed in the broad areas of manufacturing processes, manufacturing technology and factory automation, digital manufacturing, design and manufacturing systems including management relevant to engineering manufacture. Of particular interest at the present time would be papers concerned with digital manufacturing, metrology enabled manufacturing, smart factory, additive manufacturing and composites as well as specialist manufacturing fields like nanotechnology, sustainable & clean manufacturing and bio-manufacturing. Articles may be Research Papers, Reviews, Technical Notes, or Short Communications.
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