From the last decade, additive manufacturing (AM) has been evolving speedily and has revealed the great potential for energy-saving and cleaner environmental production due to a reduction in material and resource consumption and other tooling requirements. In this modern era, with the advancements in manufacturing technologies, academia and industry have been given more interest in smart manufacturing for taking benefits for making their production more sustainable and effective. In the present study, the significant techniques of smart manufacturing, sustainable manufacturing, and additive manufacturing are combined to make a unified term of sustainable and smart additive manufacturing (SSAM). The paper aims to develop framework by combining big data analytics, additive manufacturing, and sustainable smart manufacturing technologies which is beneficial to the additive manufacturing enterprises. So, a framework of big data-driven sustainable and smart additive manufacturing (BD-SSAM) is proposed which helped AM industry leaders to make better decisions for the beginning of life (BOL) stage of product life cycle. Finally, an application scenario of the additive manufacturing industry was presented to demonstrate the proposed framework. The proposed framework is implemented on the BOL stage of product lifecycle due to limitation of available resources and for fabrication of AlSi10Mg alloy components by using selective laser melting (SLM) technique of AM. The results indicate that energy consumption and quality of the product are adequately controlled which is helpful for smart sustainable manufacturing, emission reduction, and cleaner production.

从上个十年开始，增材制造（AM）一直在快速发展，并且由于减少了材料和资源消耗以及其他工装要求，已显示出在节能和清洁环境生产方面的巨大潜力。在这个现代时代，随着制造技术的进步，学术界和工业界对智能制造产生了更多的兴趣，因为它们受益于使他们的生产更加可持续和有效。在本研究中，将智能制造，可持续制造和增材制造的重要技术相结合，以形成可持续和智能增材制造（SSAM）的统一术语。本文旨在通过结合大数据分析，增材制造，可持续的智能制造技术，对增材制造企业有利。因此，提出了一个大数据驱动的可持续和智能增材制造（BD-SSAM）框架，该框架可帮助AM行业领导者为产品生命周期的生命周期（BOL）阶段做出更好的决策。最后，提出了增材制造行业的应用场景，以证明所提出的框架。由于可用资源的限制以及通过使用AM的选择性激光熔化（SLM）技术制造AlSi10Mg合金组件，该框架在产品生命周期的BOL阶段得以实施。结果表明，产品的能耗和质量得到了充分控制，这有助于实现可持续的智能制造，减少排放，