# Industry 4.0 Technologies for Manufacturing Sustainability:
## 5 Discussion on Review Results
### Main Technologies of Industry 4.0 for Achieving Sustainability
#### 5.2.5 Cloud Computing and Manufacturing  
Cloud computing in Industry 4.0 can be considered a key enabler that offers advantages like computational power required to apply ML, AI approaches and other smart technologies in Industry 4.0 [79]. Few studies reported about the uncertainties regarding the suitability of cloud computing in manufacturing organizations [6,80,81]. Cloud computing and Industry 4.0 enables the services, manufacturing networking and data over the internet in manufacturing activities [82]. Advanced cloud technologies are widely used for data sharing across the organizational boundaries which has resulted in improved flexibility and agility of systems [83]. [PERSON] [79] stated that cloud service providers provide three kind of cloud services for manufacturing industries: (1) software as service i.e., ready to use services; (2) infrastructure as a service i.e., virtual CPUs (central processing unit) or networks; (3) platform as a service i.e., virtual machines and operating systems. [PERSON] et al. [84] proposed a service oriented and computing based cloud manufacturing model for industries to improve resource utilization and reduce energy consumption. [PERSON] et al. [81] proposed a cloud manufacturing model which consists of IoT, AI technologies and services to achieve a life cycle in smart manufacturing. In the study, four applications of the model for large enterprises and small and medium enterprises are discussed. [PERSON] et al.; [PERSON] et al.; [PERSON] et al. [82,85,86] discussed the concept of cloud-based manufacturing for industries and highlighted research issues for the fourth industrial revolution. In the studies, various definitions related to cloud manufacturing is discussed. These studies provides future research directions for both academia and practitioners. [PERSON] et al. [87] stated that both mobile and cloud technologies are important for smart manufacturing. In the study, an android-based manufacturing execution system (MES) is proposed for small manufacturing facilities. The information from MES is used to create factory digital twins. [PERSON] et al. [88] presented a systematic review of cloud-based collaborative manufacturing and highlighted process and scheduling plan generation as the main challenge for industries. [PERSON] et al. [83] highlighted scheduling issues for cloud-based manufacturing and found workshop and supply chain scheduling as the emerging areas in cloud manufacturing. [PERSON] and [PERSON] [89] proposed a generic architecture for cloud-based manufacturing based on big data analytics and cyber-physical systems. It was found that the proposed architecture enables the on-demand manufacturing services via the network. [PERSON] et al. [90] proposed a hierarchical reliability-based assessment model for cloud manufacturing. In the proposed model resources at three level i.e., system, machine and component levels are evaluated. [PERSON] et al. [80] proposed a model for cloud manufacturing to monitor smart diagnosis in manufacturing. It was found that, based on cloud diagnosis corrective action such as tool replacement, parameter changes and process halting can be undertaken by a local server. [PERSON] et al. [91] stated that cloud-based manufacturing is an advanced service-oriented business model in which resources and manufacturing capabilities can be shared on a cloud platform. Cloud manufacturing can provide sustainable and robust route for manufacturing industries to achieve sustainability.