In the present era of Industry 4.0, organizations are transforming from traditional production systems to digital production systems. This transformation is in terms of additional deployment of technologies that lead to digitization and integration of products and services, business processes and customers, etc. A high volume of unstructured data is being created across different processes due to digitization. The digitization captures the data that includes text, images, multimedia, etc., due to multiplicity of platforms, e.g., machine-to-machine communications, sensors networks, cyber-physical systems, and Internet of Things. Managing this huge data generated from different sources has become a challenging task. Big data analytics (BDA) may be helpful in managing this unstructured data for effective decision making and sustainable operations. Many organizations are struggling to integrate BDA with their manufacturing processes for sustainable operations. The application of BDA from a sustainability perspective is not extensively researched in the current literature. Therefore, firstly this study explores the contribution of BDA in sustainable manufacturing operations. It further identifies strategic factors for the successful application of BDA in manufacturing for sustainable operations. For a detailed analysis of strategic factors in manufacturing, a hybrid approach comprising the analytic hierarchy process, fuzzy TOPSIS and DEMATEL is used. Results revealed that development of contract agreement among all stakeholders, engagement of top management, capability to handle big data, availability of quality and reliable data, developing team of knowledgeable, and capable decision-makers have emerged as major strategic factors for the application of BDA in the manufacturing sector for sustainable operations. Major contribution of this study is in analyzing BDA benefits for manufacturing sector, identifying major strategic factors in implementation and categorization of these factors into cause and effect group. These findings may be used by managers as guidelines for successful implementation of BDA across different functions in their respective organization to achieve sustainable operations goal. The results of this study will also motivate industry professionals to integrate BDA with their manufacturing functions for effective decision making and sustainable operations.

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中文翻译：

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大数据分析应用程序用于可持续制造运营：战略因素分析

在当今的工业4.0时代，组织正在从传统的生产系统转变为数字生产系统。这种转变是根据技术的额外部署导致产品和服务，业务流程和客户等的数字化和集成。由于数字化，正在跨不同的流程创建大量的非结构化数据。由于平台的多样性，例如机器对机器通信，传感器网络，网络物理系统和物联网，数字化捕获的数据包括文本，图像，多媒体等。管理从不同来源生成的海量数据已成为一项艰巨的任务。大数据分析（BDA）可能有助于管理这些非结构化数据，以进行有效的决策和可持续运营。许多组织都在努力将BDA与他们的制造流程集成以实现可持续运营。从可持续性的角度来看，BDA的应用在当前文献中并未得到广泛研究。因此，本研究首先探讨了BDA在可持续制造运营中的贡献。它还进一步确定了在可持续发展的制造业中成功应用BDA的战略因素。为了详细分析制造中的战略因素，使用了一种包括层次分析法，模糊TOPSIS和DEMATEL的混合方法。结果表明，所有利益相关者之间都建立了合同协议，高层管理人员参与，处理大数据的能力，质量和可靠数据的可用性，知识渊博的开发团队，明智的决策者已成为BDA在制造业中为可持续运营应用的主要战略因素。这项研究的主要贡献在于分析BDA对制造业的好处，确定实施中的主要战略因素并将这些因素归类为因果组。管理人员可以将这些发现用作成功实施BDA的指导原则，以实现其各自组织中不同职能部门的可持续发展目标。这项研究的结果还将激励行业专业人员将BDA与他们的制造功能集成在一起，以进行有效的决策和可持续运营。这项研究的主要贡献在于分析BDA对制造业的好处，确定实施中的主要战略因素并将这些因素归类为因果组。管理人员可以将这些发现用作成功实施BDA的指导原则，以实现其各自组织中不同职能部门的可持续发展目标。这项研究的结果还将激励行业专业人员将BDA与他们的制造功能集成在一起，以进行有效的决策和可持续运营。这项研究的主要贡献在于分析BDA对制造业的好处，确定实施中的主要战略因素并将这些因素归类为因果组。管理人员可以将这些发现用作成功实施BDA的指导原则，以实现其各自组织中不同职能部门的可持续发展目标。这项研究的结果还将激励行业专业人员将BDA与他们的制造功能集成在一起，以进行有效的决策和可持续运营。管理人员可以将这些发现用作成功实施BDA的指导原则，以实现其各自组织中不同职能部门的可持续发展目标。这项研究的结果还将激励行业专业人员将BDA与他们的制造功能集成在一起，以进行有效的决策和可持续运营。管理人员可以将这些发现用作成功实施BDA的指导原则，以实现其各自组织中不同职能部门的可持续发展目标。这项研究的结果还将激励行业专业人员将BDA与他们的制造功能集成在一起，以进行有效的决策和可持续运营。

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