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A Comprehensive Guide to Manufacturing Cyber Security

Securing critical manufacturing sectors from today’s cyber risks & threats.

The manufacturing sector is one of the largest, most diverse, and rapidly changing segments of the global economy. And it is a top target for cyber adversaries. Robotics, automation, machinery, IoT/IIoT, smart devices — it’s time to secure manufacturing from threats, hackers, and risks.

New sections in the Comprehensive Guide to Manufacturing Cyber Security will be published over the next several weeks. Don’t forget to subscribe to get notifications!

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Cybersecurity in Action

Learn how improved cybersecurity helped a paper mill manufacturer extend control system lifespan.

View Case Study
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Table of Contents

    Key manufacturing segments include aerospace and defense, automotive, chemicals, computer hardware, electronics, construction, consumer packaged goods (CPG), food and beverage, transportation, pharmaceuticals, and industrial manufacturing.”

    What is Critical Manufacturing, and Where is it Going?

    Many manufacturing segments of the economy are classified as critical infrastructure in the United States and elsewhere in the world. This is understandable given that manufacturers create the infrastructure needed by so many other sectors of the economy. Manufacturing is, therefore, foundational to other areas of the economy, and a vibrant manufacturing base is viewed by many countries as a particularly important metric of overall national strength and vitality.

    The manufacturing sector is, in fact, one of the largest, most diverse, and rapidly changing segments of the global economy. Key manufacturing segments include aerospace and defense, automotive, chemicals, computer hardware, electronics, construction, consumer packaged goods (CPG), food and beverage, transportation, pharmaceuticals, and industrial manufacturing.

     

    Industry 4.0

    This revolution is driving a wholesale re-evaluation of how to approach cybersecurity in manufacturing and has created a consensus that a complete migration to this new manufacturing environment cannot be successful without cybersecurity itself becoming a foundational pillar of this new era.”

    We are in the midst of a fourth Industrial Revolution that is upending traditional notions of best practice in operations, supply chain management, cybersecurity, disaster recovery, and other aspects of manufacturing. This revolution is driving a wholesale re-evaluation of how to approach cybersecurity in manufacturing and has created a consensus that a complete migration to this new manufacturing environment cannot be successful without cybersecurity itself becoming a foundational pillar of this new era.

    What has become known as Industry 4.0 has been evolving and consolidating for almost a decade, with Germany driving innovation and investment. (Aspects of this idea are also found in Japan’s Society 5.0 initiative and China’s Made in China 2025 industrial plan.) The number of technologies finding their way onto manufacturing floors, into supply chains, and new categories of connected objects is both impressive and bewildering. There truly is a revolution underway, and it is global in its reach and increasingly in its impact. Early adopters have included automotive, mechanical and plant engineering, electronics, and high technology manufacturers.

    Industry 4.0 refers to a combination of hardware, software, and services that is modernizing manufacturing infrastructure to improve efficiencies in all aspects of manufacturing processes. Technologies that are being applied to create smart factories include: robotics, sensor technology, additive manufacturing (3-D printing), augmented and virtual reality, wearables, artificial intelligence and machine learning, big data analytics, and cloud computing.

    The goal of integrating these technologies into manufacturing is to deliver smart, more aware, more agile, and more resilient infrastructure to design, optimize, and create manufactured goods. This is all done while delivering a safer work environment that uses fewer resources and optimizes maintenance practices to limit downtime.

    Industry 4.0 adoption is reaching down into small- and medium-sized businesses (SMB) and across all types of manufacturing. Many of these technologies do not require large capital investments. Not every manufacturer needs expensive robotics, for example. The most important technologies being deployed broadly by manufacturers are robotics, wearables, connected devices (IoT), additive manufacturing (3-D printing), virtual reality (VR) and augmented reality (AR), artificial intelligence (AI) and machine learning (ML), and big data analytics.

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    Robotics

    The first industrial robot was deployed in 1961. While the use of robots in manufacturing has continued to expand over the decades, the majority are still used in automotive plants, where they represent more than half the “labor” needed to build automobiles and trucks. Robotics has advanced to the point that 100% automated “lights-out” factories have been operational for several decades in sectors such as computer manufacturing.

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    Wearables

    Wearable computing and sensor devices are finding numerous applications in manufacturing environments. Devices fall into several categories, many of which are focused on employee safety, such as fall prevention, sleep prevention, noise reduction, or improved respiration. Many wearables are also focused on enabling better communication, potentially including access control — between employees and between machinery — as well as on providing easier access to information through a host of delivery mechanisms.

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    Internet of Things/ Industrial Internet of Things

    The Internet of Things (IoT)/ Industrial Internet of Things (IIoT) references a broad set of physical devices that combine embedded sensors, processing power, software, and often analytic capabilities to communicate real-time information about aspects of the physical world, such as temperature, pressure, motion, etc. Consumer applications can include smart home devices, among many others. A subcategory of more hardened devices generally termed the Industrial Internet of Things (IIoT) has also developed and found its way into manufacturing plants. IIoT devices can include an actuation component and, therefore, can function as industrial control system (ICS) devices. The manufacturing applications of IIoT are almost limitless.

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    3-D Printing

    Additive, or 3-D, printing enables the creation of three-dimensional objects directly from a CAD drawing by building up an object one layer of material at a time. 3-D printing is particularly useful in the prototyping phase of product development. Still, the size, speed, and quality of 3-D printing have improved to the degree that the technique is used in space, aerospace, wind turbine, and many other critical manufacturing sectors.

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    Virtual Reality/Augmented Reality

    Virtual reality (VR) describes a self-contained, computer-simulated environment and is another technology with broad application in product development applications for manufacturers. It is also an important tool for worker training. Augmented reality (AR) is a less immersive experience and involves superimposing digital information into the real world. This information can be as simple as a heads-up display of written material, for example, repair manuals, or it can be much more immersive and include other senses such as hearing and touch.

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    Machine Learning/Artificial Intelligence

    Machine learning (ML) is a subset of artificial intelligence (AI). ML is a technique where computer algorithms can be trained to “improve” through experience. AI and ML can improve manufacturing techniques in a host of ways and are being applied to generate general process improvements, accelerate product development, and improve quality control. Manufacturers today are using AI/ML to improve manufacturing yields, optimize asset management, manage supply chain and inventory, improve predictive maintenance and demand forecasting, among many other applications.

    Big Data Analytics

    Many technologies, particularly IIoT, are driving the need for better analysis of large data sets. Big data analytics is a field of research that addresses techniques for analyzing data sets that are too large to be dealt with in traditional data processing application software. Big data and IIoT work in tandem to monitor, analyze, and react to environmental data in manufacturing environments. Again, the applications are almost unlimited, but an early use case was predictive maintenance.

    5G

    5G is the fifth-generation technology standard for broadband cellular networks. Telecommunications providers began rolling out this successor to 4G in 2019. 5G is designed to deliver massive bandwidth improvements over its predecessor, with maximum download speeds of 10 Gbps. This should allow the networks to not only act as a traditional network for cellular calls but also to become general-purpose networks for internet service providers. This ubiquitous, global, wireless bandwidth is expected to enable further a multitude of IIoT use cases, as well as traditional industrial control system (ICS) applications.

    Building a Framework

    There is a lot of effort underway to provide a framework that encompasses all of the technological changes currently underway in manufacturing. For example, the German Electrical and Electronic Manufacturers’ Association published the Reference Architecture Model for Industry 4.0 (RAMI 4.0) in July 2015. The RAMI 4.0 model maps hierarchical levels (e.g., the Purdue model) against functional communication levels that run from high-level business concerns to individual assets. Finally, the model considers the life cycle of a product under development or in manufacturing.

    The big-picture approaches are welcome, and organizations should certainly be considering the strategic implications of each new technology purchase and how those technologies can best be deployed, integrated, and leveraged. Investments in these new technologies are typically made piecemeal, but by adhering to a common reference architecture, these incremental investments can provide more holistic benefits.

    Cybersecurity in Action

    Learn how improved cybersecurity helped a paper mill manufacturer extend control system lifespan.

    View Case Study

    Deploying Industry 4.0 Technologies

    Manufacturers can benefit from these technologies in multiple deployment scenarios. Broadly, they can be seen as affecting the supply chain, smart factory, and connected objects. Application of each technology can be found across this value chain, but these buckets will prove useful when thinking about common use cases as well as compliance requirements associated with manufacturing activity, which is too broad a sector to have an overarching regulatory framework.

    The manufacturing sector is one of the largest, most diverse, and rapidly changing segments of the global economy. And it is a top target for cyber adversaries. Robotics, automation, machinery, IoT/IIoT, smart devices — it’s time to secure manufacturing from threats, hackers, and risks.

    New sections in the Comprehensive Guide to Manufacturing Cyber Security will be published over the next several weeks. Don’t forget to subscribe to get notifications!