Cloud Computing: The Number One Enabler of Digital Manufacturing and Industry 4.0 Applications

By < Metodi Amov >

January 4, 2021

Cloud Computing: The Number One Enabler of Digital Manufacturing and Industry 4.0 Applications

The promise of Industry 4.0 and Digital Manufacturing is to provide increased production flexibility based on a complete virtualization of manufacturing processes. This virtualization is destined to facilitate manufacturers to increase the efficiency of their plants and of their production processes, both inside the factory and across the supply chain. In this direction, Industry 4.0 facilitates the real-time orchestration of production systems towards supporting end-to-end production processes. This orchestration happens at the cyber (i.e., the IT) layer of digital manufacturing systems, which alleviates the complexity of managing low-level Operational Technology (OT) resources such as PLCs (Programmable Logic Controllers), SCADA (Supervisory Control and Data Acquisition) systems and DCS (Distributed Control Systems).

Cloud Computing Value Proposition for Manufacturing Enterprises

In this context, cloud computing technology is the digital key to enabling the end-to-end virtualization of complex manufacturing processes. Specifically, cloud computing infrastructures enable the seamless and scalable integration of IT services from different CPPS (Cyber Physical Production Systems), along with their real-time orchestration in-line with the needs of production processes. Cloud computing infrastructures come with the following compelling value-propositions for manufacturing enterprises:

  • Scalability: Cloud computing facilitates manufacturers to access the needed resources without limitations. For instance, it is common for Industry 4.0 applications like predictive maintenance to have high demands for storing BigData stemming from sensors and CPPS systems. Cloud computing infrastructures ensure that these resources will be available as needed.
  • Elasticity: Cloud computing infrastructures scale elastically and seamlessly. Whenever more resources are required for an Industry 4.0 application, the cloud infrastructure scales automatically and makes them available. Likewise, in cases where lesser resources are required, cloud services can automatically release resources and scale down elastically.
  • Pay-as-you-go: Manufacturers accessing cloud computing infrastructures pay exactly for the computing resources they use and at the time when these resources are used. This obviates the need for significant upfront investments on IT resources i.e., significant CAPEX (Capital Expenditure). Rather, manufacturers pay for computing resources as part of the regular OPEX (Operational Expenditure) e.g., monthly.

The Benefits of Cloud Computing for Digital Manufacturing and Industry 4.0

These properties of cloud computing are sources of competitive advantage for modern manufacturers. Specifically, leveraging cloud services, manufacturers can enjoy the following business benefits:

  • Increased business flexibility and production agility: The Cloud provides access to the computing resources needed by production processes, including computing power, network bandwidth and storage capacity resources. Furthermore, the elasticity of the cloud ensures that these resources will be available even in cases of sudden or unexpected peaks to the demand for computing resources, such as for example seasonal peaks in customer demand and subsequent peaks in production orders. Furthermore, cloud computing infrastructures enable manufacturers to scale them up and down according to the number and complexity of their production processes. With cloud computing manufacturers are no longer bound to rigorous contracts and SLA (Service Level Ageement). Likewise, they need not engage in significant upfront IT investments. For instance, a manufacturer can gradually scale the computing resources it uses, as the number of its Industry 4.0 deployments increases. This provides significant flexibility and avoids paying for IT resources that remain underexploited.
  • Increased operational efficiency and productivity: Cloud environments enable manufacturers to configure their production processes at IT timescales using IT services, rather than having to engage in complex manual configurations of OT systems. Hence, cloud services enable manufacturers and plant operators to achieve almost zero deployment times for their IT-based production processes. Likewise, they can benefit from a considerable reduction of enterprise maintenance and other operational activities.
  • Shorter innovation cycles and continuous improvement: Cloud computing infrastructures simplify the deployment of new production processes and the configuration of production recipes. This facilitates experimentation with alternative production configurations and the deployment of innovative production workflows. In this way, innovation cycles become shorter and manufacturers become able to implement continuous improvement processes. In essence, cloud computing eases the transition to the vision of agile and lean manufacturing.
  • Cost savings: With cloud computing manufacturers can save significant costs and improve their bottom lines. For example, they can save on infrastructure management costs through reducing systems management complexity and subsequently the amount of human resources required. As another example, they save on IT computing costs thanks to the elasticity of the cloud resources. Finally, they benefit from the conversion of CAPEX investments to OPEX costs that are spread over longer timeframes.

Edge Computing: When the Cloud is not enough

Despite the above-listed benefits of cloud computing, cloud services fall short when it comes to implementing specific types of Industry 4.0 use cases. For instance, cloud computing environments are not very suitable for low-latency use cases that must be executed close to the field, such as real-time actuation and control applications. This is because moving data and services from the field to the cloud and vice versa is usually associated with significant latency. Likewise, transferring sensitive data to the cloud is not always the best option from a privacy and data protection standpoint. Cloud data transfers are susceptible to adversarial attacks that could lead to data breaches and privacy leaks. Moreover, cloud computing does not always make optimal use of storage and bandwidth resources. For example, it is not very practical to move raw data from the field to the cloud, especially when only a fraction of these data is used for BigData analytics.

The Edge Computing paradigm comes to alleviate these limitations. Edge computing introduces a new layer of edge devices between the field (e.g., the OT and CPPS systems) and the cloud. This layer provides the means for executing low-overhead, low-latency operations close to the field, which makes it suitable for real-time operations. Moreover, edge computing facilitates the pre-processing of data in the edge devices and the subsequent transmission of selected datasets to the cloud. This reduces the amount of data that is transferred to the cloud, which economizes on network bandwidth and cloud storage. Furthermore, the processing of sensitive data can be done on the edge devices, which reduces privacy and data protection risks.

In the edge computing paradigm, most of the edge devices are resource constrained. They interact with the cloud when increased storage capacity and computing resources are required. This is the reason why edge computing is commonly used in conjunction with cloud computing as part of the so-called “edge/cloud” computing paradigm. In many cases edge functionalities are executed within edge computing clusters that sit between the cloud and the field devices. This is an alternative flavour of the edge computing paradigm, which is called fog computing. In the scope of a fog computing deployment, specialized edge computers or computing clusters act as “fog” nodes that aggregate data from many edge devices and execute real-time operations close to the field. Fog nodes reside in the same LAN (Local Area Network) as the edge devices and are typically separated from the cloud through a Wide Area Network (WAN).

Cloud Computing and Edge Computing in the Microsoft Azure Ecosystem

State of the art platforms for digital manufacturing are cloud based. In most cases they are platforms built over mainstream cloud computing infrastructures. Specifically, there is currently a clear separation of concerns in the industry:

  • Cloud providers ensure access to the cloud computing resources of any manufacturing platform. Hence, cloud resources are considered as “digital plumbing” i.e., as a layer of infrastructural resources that enables and supports digital manufacturing functionalities.
  • Manufacturing automation experts build value-added functionalities over the cloud computing infrastructure. Such functionalities come in various forms such as connectors to CNC machines, management of historians’ data in the cloud, development of machine learning algorithms for predictive maintenance, as well as calculation of Key Performance Indicators (KPIs).

To learn more about the Azure infrastructure visit the respective Microsoft site.

Upkip and Microsoft’s Azure Cloud Platform – the Easy Way to Get Started with Industry 4.0

In-line with industry trends, the Upkip platform has been built over Microsoft’s Azure cloud platform. The latter is a trusted cloud infrastructure that provides security from the ground up and supports a wide array of cloud configurations, including multi-cloud deployments and edge/cloud deployments. Azure comes with a rich set of tools that facilitate the management of cloud environments despite the heterogeneity of resources and configurations that they comprise. Azure provides support for all mainstream programming languages and frameworks, which facilitates application development and deployment. Many manufacturers around the globe are currently leveraging Azure to implement Industry 4.0 use cases, including predictive maintenance, remote monitoring of assets and machines, as well as supply chain applications across connected plants.

Azure supports edge computing deployments thanks to its Azure Edge Zones i.e., local extensions of the Azure cloud that enable the provision of resources close to the customers. Based on Azure Edge Zones manufacturers support use cases like local data processing of sensitive data, latency-sensitive data analytics, real-time actuation, as well as mixed reality applications.

Upkip is powered by Azure’s novel functionalities and leverages the scalability, capacity, trustworthiness, and quality of service of the Azure platform. The Upkip product implements a rich set of digital manufacturing functionalities over the Azure cloud, including manufacturing performance monitoring, production optimization, and predictive maintenance. Overall, the partnership between Upkip experts and the world-class Azure infrastructure has resulted in a scalable, robust, and intelligent digital manufacturing platform that helps manufacturers ride the Industry 4.0 wave in the fastest and most cost-effective way.

 

To access more information about Upkip’s digital manufacturing functionalities visit this page.


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