供应链
可追溯性
信息共享
质量(理念)
零浪费
数据质量
计算机科学
数据共享
产品(数学)
工厂(面向对象编程)
过程管理
工程类
业务
营销
医学
公制(单位)
几何学
数学
废物管理
替代医学
程序设计语言
认识论
病理
哲学
万维网
软件工程
作者
Mauro Isaja,Phu H. Nguyen,Arda Göknil,Sagar Sen,Erik Johannes Husom,Simeon Tverdal,Abhilash Anand,Yunman Jiang,Karl John Pedersen,Per Myrseth,Jørgen Stang,Harris Niavis,Simon Pfeifhofer,Patrick Lamplmair
标识
DOI:10.1016/j.compind.2023.103853
摘要
There is a current wave of a new generation of digital solutions based on intelligent systems, hybrid digital twins and AI-driven optimization tools to assure quality in smart factories. Such digital solutions heavily depend on quality-related information within the supply chain business ecosystem to drive zero-waste value chains. To empower zero-waste value chain strategies with meaningful, reliable, and trustful data, there must be a solution for end-to-end industrial data traceability, trust, and security across multiple process chains or even inter-organizational supply chains. In this paper, we first present Product, Process, and Data quality services to drive zero-waste value chain strategies. Following this, we present the Trusted Framework (TF), which is a key enabler for the secure and effective sharing of quality-related information within the supply chain business ecosystem, and thus for quality optimization actions towards zero-defect manufacturing. The TF specification includes the data model and format of the Process/Product/Data (PPD) Quality Hallmark, the OpenAPI exposed to factory system and a comprehensive Identity Management layer, for secure horizontal- and vertical quality data integration. The PPD hallmark and the TF already address some of the industrial needs to have a trusted approach to share quality data between the different stakeholders of the production chain to empower zero-waste value chain strategies.
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