The Role of Cloud Computing in Industry 4.0 and Beyond

Summary

Cloud computing is transforming the fast-moving manufacturing world. For those leading the charge in industrial manufacturing, understanding cloud computing’s role is not just beneficial—it’s essential. Due to its scalability, flexibility and cost effectiveness, cloud computing helps manufacturers reach their business goals of efficiency and innovation.

In simple terms, cloud computing means using the Internet to access and use information technology (IT) services such as storage, servers, databases and software. Instead of having these resources inhouse, which requires significant investment and maintenance, cloud computing lets users use them as needed through service providers with usually pay-as-you-go pricing. This approach saves money, allows for simple adjustments to operations and reduces the burden of managing complex IT infrastructures.

Cloud computing affects industrial manufacturers by enabling real-time data collection and analysis directly from various data sources on the shop floor, which turns vast amounts of data into actionable insights. This capability allows many insights to inform, describe and predict an event and even prescribe an action to prevent an event such as machine downtime or a quality defect. Cloud computing also makes it easier for manufacturing professionals to collaborate remotely by sharing expertise and solving problems without geographical limits. Additionally, it supports flexible operations, which allows manufacturers to adapt quickly to market demands or operational changes.

According to the Hackett Group’s research report on the business impact of cloud adoption in the industrial manufacturing sector, cloud computing has enhanced operational efficiency, which is evidenced by a 16% increase in overall equipment effectiveness (OEE) and a 39% reduction in unplanned IT downtime. Supplier management has seen a 33% increase in sourcing savings and a 20% reduction in staffing needs per million dollars of spending. Sales efficiency and customer satisfaction improved notably, with a 42% increase in revenue per salesperson and a 34% boost in customer satisfaction. In addition, there’s a 22% improvement in new product time to market and a 21% reduction in lead times, which demonstrates increased business agility and innovation. These results highlight the critical role that cloud computing is playing in transforming the manufacturing industry.

This article offers a guide on how cloud computing is transforming the manufacturing industry by enhancing operational efficiency, driving innovation and enabling Industry 4.0 initiatives. It also emphasizes the benefits of cloud computing such as scalability, cost savings and real-time data insights (Figure 1). It explores deployment and access models (IaaS, PaaS, SaaS), provides case studies from leading companies and highlights challenges like data security and compliance. It also provides actionable steps for successful cloud adoption, such as the leadership alignment, migration planning and skill development that empowers manufacturers to navigate their digital transformation journeys effectively.

Main cloud benefits for manufacturers

In manufacturing, financial strategy is as crucial as the efficiency of the manufacturing operation. Cloud computing reshapes this strategy through shifting capital expenses to operational expenses, leveraging economies of scale, ensuring responsive capacity management, improving speed and operational agility, freeing up resources to spend on innovation, easily expanding globally and accessing new technologies.

Capital expenses to operational expenses. Traditionally, manufacturers have had to invest heavily in physical infrastructure before knowing the full scope of its utility. Cloud computing transformed this model. Users pay for computing power as they use it, much like electricity or water utilities. This shift to a pay-as-you-go model means users only pay for the computing resources they use, which offers a flexible financial approach that aligns with production demands.

Leverage economies of scale. The scale of providers amplifies the cost savings of cloud computing. Their vast network and customer base mean the benefits of large-scale operations are passed down to users, which reduces the cost of services compared to hosting their own data center.

Responsive capacity management. Guessing the right amount of IT infrastructure can lead to wastage or bottlenecks. Cloud computing eliminates this issue. Users can scale resources up or down in response to their manufacturing operations, which ensures they have the capacity they need without overcommitting resources.

Improve speed and operational agility. Time is of the essence in manufacturing. Cloud computing dramatically reduces the time it takes to make IT resources available from weeks to minutes. This accelerates innovation and the ability to respond to market changes.

Free up resources to spend on innovation. Running a data center is a significant overhead cost involving maintenance and staff. Cloud computing allows users to offload these tasks and expenses, which frees up capital and resources to invest in areas directly contributing to product innovation and customer satisfaction.

Global expansion with ease. Manufacturers looking to expand their reach can use the cloud to deploy applications globally efficiently. This capability means users can leverage the same IT applications and serve global teams and customers with reduced latency, which improves the employee and customer experience without a proportional cost increase.

Access to new technologies. Cloud computing enables manufacturers to tap into new technologies such as big data analytics, artificial intelligence (AI) and the Internet of Things (IoT). These technologies can be accessed and integrated into their operations without the need for heavy upfront investment or expert resources, which allows them to gather, analyze and act on data to optimize efficiency and innovation.

Cloud computing deployment models
The cloud deployment model refers to the location of physical infrastructure and who maintains, manages and controls it. Users can choose the deployment model for each application or a business unit based on business needs and goals. It is not uncommon for an organization to use all deployment models simultaneously. Typical cloud deployment models are clout deployment, public versus private cloud, hybrid deployment and on-premises deployment.

Cloud deployment. In the cloud deployment model, applications are fully hosted in the cloud, which benefits from its agility and scalability. The cloud provider solely maintains the infrastructure. This deployment model is ideal for manufacturers looking to innovate without constraints in physical infrastructure. This model works well where Internet connectivity is not an issue or applications are not latency sensitive.

Public versus private cloud. In a private cloud, cloud computing resources are isolated and dedicated to a single organization. The infrastructure could be maintained by the same organization or a third-party cloud provider. In the public cloud, those resources may be shared with other organizations and infrastructure is maintained by a third-party cloud provider.

Hybrid deployment. The hybrid model connects on-premises infrastructure with cloud resources. This model offers a balance of control and flexibility. It suits applications that will gradually transition to the cloud while maintaining some components onsite.

On-premises deployment. This model uses virtualization for resource management, which appeals to those who require dedicated resources within their control. Some applications sensitive to latency or have regulatory data residency requirements must stay on-premises. However, leading public cloud vendors enable cloud services on shared infrastructure or provide dedicated hardware to extend the cloud to your premises. The examples are AWS Outpost, MS Azure Stack and Google Anthos.

Each model offers varying degrees of control, which allows manufacturers to select an approach that aligns with their strategic and operational application objective.

Cloud Computing access models
Users can access cloud resources in a few ways that depend on the exact nature of the use case (Figure 2). The main models for offering cloud computing are infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS).

Cloud computing and Industry 4.0

Cloud computing is a critical enabling technology for Industry 4.0, the fourth industrial revolution focused on interconnectivity, automation, machine learning and real-time data. By providing on demand network access to a shared pool of computing resources, such as servers, storage, applications and services, cloud computing allows businesses to provision resources rapidly, deploy applications and scale services as needed. This agility and flexibility support the data-driven, highly connected systems central to Industry 4.0.

With cloud computing, manufacturers can leverage IoT sensor data, analyze it in real time using advanced analytics and integrate it with enterprise applications and machines on the factory floor. The cloud’s scalability also allows manufacturers to apply computing-heavy capabilities such as AI and machine learning for optimizations and predictive maintenance.
 

Leading cloud providers

All large public clouds provide a variety of services for manufacturing and industrial companies, which facilitates advances in industrial IoT, factory automation and supply chain optimization. Their solutions support a connected infrastructure that enables real-time data collection and analysis from factory equipment. Machine learning and analytics services empower predictive maintenance and operational insights. For supply chains, they offer services that enhance visibility and forecasting, which contributes to more resilient operations. These tools allow manufacturers to harness the power of data to streamline processes, innovate and maintain competitiveness in the modern industrial landscape. Due to their ability to provide extensive scalability, their public clouds are also referred to as “hyperscalers.”

Each cloud hyperscaler—Azure, AWS and GCP—varies in range and specialization and differentiates its services. This offers unique strengths across various aspects of IoT, automation and supply chain management to cater to distinct manufacturing needs.
 

More hyperscaler information

For detailed information on how hyperscaler cloud providers support these industrial use cases, please each provider’s web page:

• Amazon Web Services (AWS): AWS for Industrial
• Microsoft Azure: Microsoft Azure Industry
• Google Cloud Platform: Google Cloud for Manufacturing.

For more study on hyperscalers by independent analyst:

• Gartner Magic Quadrant for Strategic Cloud Platform Services
• The IoT Cloud.

Case studies

The following sections are case studies about how the aforementioned hyperscalers were of benefit to manufacturers.

AWS case study. Global biopharmaceutical company, Merck, leveraged AWS to enhance the efficiency of its manufacturing operations through a centralized data and analytics platform named “MANTIS.” By migrating its legacy data platform to AWS, Merck achieved a threefold increase in performance and a 50% reduction in operating costs. The platform unifies data from more than 120 manufacturing systems that provided real-time insights into more than 3,000 users, which significantly improved decision making, reduced data ingestion time and increased supply chain visibility. This transformation enabled Merck to become more data driven by optimizing manufacturing processes and ensuring timely delivery of high-quality medications.
Source: AWS - Merck Case Study

Microsoft Azure case study. Husky Injection Molding Systems used Azure IoT Hub for its digital solution “Shot Scope NX,” which dramatically improved the monitoring and operation of their injection molding machines. This implementation led to a notable increase in operational efficiency that offered real-time insights for proactive maintenance and enhanced customer service. By adopting Azure IoT Hub, Husky experienced significant advances in machine uptime and operational productivity, thereby revolutionizing their manufacturing process and customer support.

Source: MS Azure – Husky Case Study


Google Cloud case study. AB InBev, the world’s largest brewer, collaborated with Pluto7 and Google Cloud to enhance its demand forecasting. By leveraging Google Cloud’s AI and machine learning capabilities, they achieved a 95% accuracy rate in demand forecasting, which led to more efficient inventory management and a significant waste reduction. This advanced forecasting model provided AB InBev with deeper insights into consumer behavior, which enabled more effective and sustainable business decisions.

Source: GCP – AB InBev Case Study
 

Risks and challenges

While using the cloud offers benefits to manufacturers, it does not alleviate the risks and challenges such as data security, compliance and network reliability.

Data security. When using cloud services for IT infrastructure, data travels through external networks to remote data centers, which introduces additional security risks. Ensuring data security in the cloud involves several measures such as authentication, authorization, encryption, identity, access management and more.

The division of security responsibilities between the cloud provider and the user can be complex. The chosen deployment and access models also influence who is responsible for different security tasks. Cloud providers often use a shared responsibility model to define these roles clearly. Users must recognize and understand their security responsibilities when using cloud services. This awareness should guide decisions regarding selecting service and deployment models in the cloud.

Compliance. Compliance with various local, national and international regulations such as ITAR, GDPR and HIPAA is mandatory in manufacturing. When transitioning workloads to the cloud, meticulous due diligence is crucial to maintain compliance. Although cloud providers may offer support for most regulations and compliance laws, the user is ultimately accountable for ensuring that their applications adhere to these legal requirements.

Network reliability. Manufacturing plants—often located in remote locations and spread across vast areas—face challenges with network connectivity, which is crucial for cloud computing. A comprehensive assessment of network infrastructure and related risks is necessary to make informed decisions on deployment models, edge computing needs and balancing latency, performance, cost and other system parameters. To mitigate connectivity risks and maintain business continuity, options such as redundant network paths and offline capabilities should be considered.

Other risks. When transitioning to cloud computing, it’s crucial to recognize risks such as data loss, vendor lock in and fluctuating costs. Mitigating data loss risks involves regular data backups and archiving critical data. It is vital to examine service agreements to achieve an optimal balance between cost and flexibility. Cloud pricing—typically based on a pay-as-you-go model—can vary with multiple tiers, usage-based discounts and options for long-term contracts. Implementing cost management strategies that suit specific use cases is essential. A careful analysis of these risks when designing cloud architecture allows a strategic approach that maximizes the cloud’s benefits.

Challenges. As manufacturers embark on the cloud transformation journey, there will be many milestones to celebrate success, yet the journey is not without challenges. There can be different challenges at different stages of this journey.

• Pilot purgatory. Research and study reports indicate that many manufacturers embark on a cloud transformation journey but are stuck in “pilot purgatory.” It means the projects do not scale beyond initial pilots despite heavy upfront investment with expectation that they would scale. Manufacturers must secure leadership support to prevent such pilot purgatory. Leadership support must envision and ensure business benefit realization and align stakeholders.
• Other challenges. A study named “Clearing the air on cloud” by McKinsey & Company on cloud adoption in the discreet manufacturing industry indicates that approximately two-thirds of industrial firms use cloud solutions. Yet, a minority fully capitalizes on their advantages. The focus often mistakenly rests on infrastructure hosting and IT savings rather than the fully native cloud solution and their ability to boost operational efficiency and market agility. About 74% of cloud projects miss their targets due to complexities and budget excesses. The cloud’s value extends beyond just IT Infrastructure saving into manufacturing, supply chain and procurement, which offers substantial business transformation opportunities.

Preparing for cloud migration and modernization

When users embark on the journey to migrate to the cloud and modernize their operations, it is vital to reduce risks and tackle the aforementioned challenges. For this journey, users can use valuable insights from best practices derived from various sources and successful manufacturing transformation case studies. Users should adopt specific steps to fit their organization’s unique situation.

Leadership alignment. For any manufacturer to succeed in cloud migration, their leadership including CXOs must be aligned and understand the benefits of the cloud, support training and adoption efforts.

Assessment. Begin by evaluating the current IT environment. Inventory all IT assets and understand their roles, importance and dependencies.

Prioritization. Prioritize workloads for migration based on factors like criticality, security and readiness. Start with less critical systems for a proof of concept.

Platform evaluation. Identify the cloud provider (e.g., AWS, Azure, Google Cloud) that best suits your needs; consider functionality, security, compliance and pricing.


Migration plan. Create a phased migration plan with timelines. Include planning, testing, configuration and migration activities; allow room for issue resolution.

Cloud governance. Establish cloud management and governance processes including security policies, monitoring, access controls and financial management.

Software/configuration updates. Make necessary software or configuration changes to adapt applications for the new cloud environment. This will enable them to use cloud-native services.

Execution. Execute the migration plan systematically by moving systems from on-premises to the cloud while continuously testing functionality and dependencies.

Optimization. After the initial migration, focus on optimizing cloud usage and realizing ongoing benefits. Consider modernizing applications for improved performance and flexibility.
 

Acquiring cloud skills

As users begin their journey into cloud computing transformation, it is essential to have the right skills within your team. Different individuals in the organization require varying expertise and skills that depend on their specific roles and interactions with cloud technology.

General awareness. General awareness is the minimum requirement, regardless of your role in the organization. It would be best if you had a fundamental understanding of cloud computing, that you could participate in discussions, understand what cloud computing meant to you and benefit from organization-wide efforts.

In-depth technical training. Users should take a deep dive into technology if their roles require interacting technically with cloud services. Users can equip themselves with the right skills to manage and use cloud resources effectively.

Certifications. Pursue cloud certifications—especially those offered by providers like AWS, Azure or GCP—to validate expertise and commitment to cloud technology. An organization should also incentivize the training and certification of its employees. It motivates employees to invest in their professional development and contribute to the organization’s cloud adoption and innovation goal. Manufacturers can partner with their cloud provider and leverage their training resources. Cloud providers often offer comprehensive training programs and material that aligns with their specific platform.

Important learning resources include:

• AWS Skill Builder
• Microsoft Azure Skills
• Google Cloud Training.

Looking ahead

According to the reports by Deloitte on Manufacturing Industry Outlook and Smart Factory, 86% of participants believe that smart factory solutions will be the primary driver of competitiveness in five years, and 83% believe they will transform the way products are made in five years. Cloud computing plays perhaps the most crucial role in digital transformation and industry 4.0 initiatives by enabling big data processing, high-performance computing and more. The manufacturers who stay ahead of the curve in adopting emerging technologies will have competitive advantages.

_{A version of this article originally appeared in the International Journal of Engineering Research and Technology (IJERT) on March 21, 2024.}