首页> 外文会议>SAMPE conference >CONTEXT AWARE COMPUTING LEVERAGES THE INDUSTRIAL INTERNET OF THINGS (IIOT) TO CREATE A RICH DIGITAL CONTEXT AND WEAVE THE DIGITAL THREAD FOR AUTOMATED AND OPTIMIZED DECISION MAKING IN COMPOSITES MANUFACTURING
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CONTEXT AWARE COMPUTING LEVERAGES THE INDUSTRIAL INTERNET OF THINGS (IIOT) TO CREATE A RICH DIGITAL CONTEXT AND WEAVE THE DIGITAL THREAD FOR AUTOMATED AND OPTIMIZED DECISION MAKING IN COMPOSITES MANUFACTURING

机译:上下文AWARE COMPUTERS利用物联网(IIOT)的工业互联网创建丰富的数字上下文,并编织数字线程,以自动和优化决策方式来制造复合材料

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摘要

Composite component fabrication requires real-time decisions based on a long and growing listrnof variables and constraints. As production volumes and complexity increase, suppliers are facedrnwith more unforeseen problems, and have less time and ability to make optimized decisions.rnTheory and practice show, that the more variables considered in solving a problem, the better thernpotential result. However, in attempts to consider the ‘big picture’, human beings reach theirrnlimit at some point, and resort to solving only parts of the challenge, with or without a softwarerndesigned to address that sub-problem.rnCurrently, integrating this vast and diverse amount of data into a global view of the process isrnvery difficu typically each data set is analyzed in its own software package, limiting the abilityrnto integrate the multiple data types and detect inefficiencies and process issues that might triggerrnproduction delays.rnIntegrating Intelligent, context-aware software, based on the Industrial Internet of Things (IIoT)rnrepresents dramatic opportunities as new sensor technologies collect vast amounts of data in realrntime, creating a rich digital context that starts with design engineers and is continuously builtrnthrough the entire lifecycle of the product.rnThis ‘digital thread’ weaves a single integrated stream of digital data that makes informationrnfrom the entire life cycle available and visible to all stakeholders. This would include – amongrnother information - asset location (including pre-preg rolls, kits and assemblies), assets’ statusrnand availability (including tools, machines, autoclaves and personnel), exposure timerninformation of parts, kits and assemblies, as well as full genealogical information for each assetrnor resource, from the moment it was first created, throughout production and beyond into MROrn(maintenance, repair, and overhaul). The digital thread model is enabled by the IIoT abilities andrnsupports full traceability of each part, starting at the raw material phase and through itsrnfabrication on the production floor, for later stage auditability and significantly shorter crisisrnmanagement should a defect occur or be discovered along the way. This paper will demonstrate how greater digital context enables better decision making, whilernreducing risk and pushing the productivity envelope; how weaving the digital thread is crucialrnfor reducing rework, scrap, as well as enhancing quality & quality control to ensure compliancernwith strict OEM’s (Original Equipment Manufacturer) regulations and on-time delivery.
机译:复合组件制造需要基于长期不断增长的listrnof变量和约束条件的实时决策。随着生产量和复杂性的增加,供应商面临更多无法预见的问题,并且他们做出最佳决策的时间和能力也更少。理论和实践表明,解决问题时考虑的变量越多,潜在的效果就越好。但是,在尝试考虑“大局面”时,人们在某种程度上达到了自己的极限,并且无论是否设计了专门用于解决该子问题的软件,人们都只能解决部分挑战。将数据放入流程的全局视图非常困难;通常,每个数据集都在其自己的软件包中进行分析,从而限制了集成多种数据类型并检测可能导致生产延迟的低效率和流程问题的能力。随着新的传感器技术实时收集大量数据,创造了巨大的机遇,创建了一个丰富的数字环境,从设计工程师开始,并在产品的整个生命周期中不断构建。这个``数字线程''编织了单个集成的数字数据流,使整个生命周期中可用的信息,所有利益相关者都可以看到。除其他信息外,这将包括资产位置(包括预浸料卷,套件和组件),资产状态和可用性(包括工具,机器,高压灭菌器和人员),零件,套件和组件的暴露时间信息以及完整的家谱信息从每种资产的资源创建之初起,贯穿整个生产直至MROrn(维护,维修和大修)的信息。数字线程模型具有IIoT功能,并支持每个零件的完全可追溯性,从原材料阶段开始,直至在生产车间进行制造,以实现后期可审核性,并在发生或发现缺陷时显着缩短危机管理时间。本文将展示更大的数字环境如何实现更好的决策,同时降低风险并提高生产率。如何编织数字线程对于减少返工,报废以及增强质量和质量控制以确保遵守严格的OEM(原始设备制造商)法规和按时交货至关重要。

著录项

  • 来源
    《SAMPE conference》|2016年|1-13|共13页
  • 会议地点 Long Beach CA(US)
  • 作者

    Avner Ben-Bassat;

  • 作者单位

    Plataine Inc. 465 Waverley Oaks Road, Suite 420 Waltham, MA 02452;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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