Abstract

The advent of new technologies alongside the generation of the vast amount of data in the manufacturing processes makes Green Lean Six Sigma (GLSS) approaches very challenging. This paper presents a novel framework termed ‘BDA-GLSS’ that guides companies to effectively integrate Big Data Analytics (BDA) in GLSS to improve their environmental performance. The BDA-GLSS framework is validated using an industrial case study of a leading chemical company. The results suggest measurable benefits of the proposed framework in enhancing technological readiness, problem identification, and analysis with predictive capability. The BDA-GLSS guides the implementation of BDA techniques within the GLSS framework offering real-time quality control, event-based inspection, and predictive maintenance. The BDA-GLSS enhances the environmental capability, process performance and provides a new perspective for researchers and practitioners to support GLSS projects in achieving higher green performance.

摘要

新技术的出现以及制造过程中大量数据的产生使得绿色精益六西格码 (GLSS) 方法变得非常具有挑战性。本文提出了一种名为“BDA-GLSS”的新颖框架，指导公司有效地将大数据分析（BDA）集成到 GLSS 中，以提高其环境绩效。BDA-GLSS 框架通过一家领先化学公司的工业案例研究进行了验证。结果表明，所提出的框架在增强技术准备、问题识别和预测能力分析方面具有可衡量的好处。BDA-GLSS 指导在 GLSS 框架内实施 BDA 技术，提供实时质量控制、基于事件的检查和预测性维护。BDA-GLSS增强了环境能力，