Recommendation Framework for on-Demand Smart Product Customization

Leila Esheiba, Amal Elgammal, M. El-Sharkawi
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引用次数: 7

Abstract

Product-service systems (PSSs) are being revolutionized into smart, connected products, which changes the industrial and technological landscape and unlocks unprecedented opportunities. The intelligence that smart, connected products embed paves the way for more sophisticated data gathering and analytics capabilities ushering in tandem a new era of smarter supply and production chains, smarter production processes, and even end-to-end connected manufacturing ecosystems. This vision imposes a new technology stack to support the vision of smart, connected products and services. In a previous work, we have introduced a novel customization PSS lifecycle methodology with underpinning technological solutions that enable collaborative on-demand PSS customization, which supports companies to evolve their product-service offerings by transforming them into smart, connected products. This is enabled by the lifecycle through formalized knowledge-intensive structures and associated IT tools that provide the basis for production actionable “intelligence” and a move toward more fact-based manufacturing decisions. This paper contributes by a recommendation framework that supports the different processes of the PSS lifecycle through analysing and identifying the recommendation capabilities needed to support and accelerate different lifecycle processes, while accommodating with different stakeholders’ perspectives. The paper analyses the challenges and opportunities of the identified recommendation capabilities, drawing a road-map for R&D in this direction.
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按需智能产品定制的推荐框架
产品服务系统(pss)正在转变为智能互联产品,这将改变工业和技术格局,并带来前所未有的机遇。智能互联产品所嵌入的智能为更复杂的数据收集和分析能力铺平了道路,开创了一个更智能的供应链和生产链、更智能的生产流程,甚至是端到端互联制造生态系统的新时代。这一愿景要求新的技术栈来支持智能互联产品和服务的愿景。在之前的工作中,我们介绍了一种新颖的定制PSS生命周期方法,其基础技术解决方案支持协作式按需PSS定制,支持公司通过将产品服务转换为智能、连接的产品来发展其产品服务。这是通过形式化的知识密集型结构和相关的IT工具在生命周期中实现的,这些工具为生产可操作的“智能”提供了基础,并向更基于事实的制造决策迈进。本文通过分析和识别支持和加速不同生命周期过程所需的推荐功能,同时适应不同利益相关者的观点,提供了一个支持PSS生命周期不同过程的推荐框架。本文分析了识别推荐能力的挑战和机遇,并绘制了该方向的研发路线图。
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