Industrial Digitalization and the Manufacturing Industry
Industrial digitalization has many benefits for manufacturing companies. It helps companies gain a holistic view of their operations as well as fine-grained information. With specialized software, management can see at a glance how production, resource flows, and target metrics are performing. The software also lets managers do a deep dive into the function of specific equipment. By providing this kind of information at a glance, industrial digitalization helps reduce the friction between ideas and execution.
Although there is no single standard for industry 4.0, the Fieldbus networks of the 1990s are a good starting point. More than 20 standards have already emerged, including Ethernet with distinct industrial protocols like EtherNet/IP and Profinet. The goal is to standardize industrial networks to make them interoperable, but it’s taking much longer than expected to achieve this goal. The OPC Foundation, an open-source initiative, and the Object Management Group have teamed up to develop an industry-wide strategy to achieve technical interoperability.
Initially, manufacturers pushed for automation, but the cost was prohibitive for them with the technologies available then. Another problem was the integration of components from different suppliers that used different communication protocols. Moreover, there were multiple competing data interchange standards between the U.S. and Europe. Despite these challenges, the German initiative, known as Industry 4.0, is now influencing thinking throughout the world and influencing other initiatives.
This new technology has made it possible for manufacturers to increase productivity and quality. With the advent of connected platforms and mobile devices, consumer expectations have shifted from mass production to personalized manufacturing. As a result, industrial manufacturing companies are embracing new, advanced technologies that help them move from mass production to personalized production. In addition, the internet of things has made it possible for consumers to interact with products on their devices, including smart TVs and other connected devices.
Industrial digitalization has many implications for the manufacturing industry. Cyber-physical systems are emerging as the foundation for the fourth industrial revolution, or Industry 4.0. They enable new capabilities, including remote control, services, and predictive and proactive maintenance. They can also be used to monitor the health of mechanical and structural systems. With their increased flexibility, they also offer new business models. Here are four examples of how cyber-physical systems are transforming the manufacturing industry.
Smart Industry is a term that describes the technological evolution of manufacturing, where the physical and virtual worlds interact. It is the fourth industrial revolution, and it includes the Internet of Things, Data, and Services. In this revolution, decentralized intelligence provides new ways to monitor and manage processes and objects. This creates independent process management and intelligent object networking. This interaction between the real and virtual worlds is one of the biggest new elements of manufacturing.
CPPS is a term first introduced by E. A. Lee in 2006 and has been studied in many practical and scientific disciplines. It involves continuous information exchange. Sensors and actuators record environmental conditions and evaluate them in the cybersphere. The information is then exchanged with other entities. Once the information is exchanged, it can be used to change the environment. It may be used to monitor processes or prevent accidents.
To ensure sustainability, profitability, and safety, industrial digital transformation is essential. Fortunately, AI is a key enabler of this change. AI helps industrial companies predict future problems and improve production. Read on to learn more about the benefits of AI and industrial digitalization. For manufacturers, the most prominent use of AI in manufacturing today is predicting machine failure. But AI can do so much more than improve productivity. Here are some other ways that industrial digitalization can improve production.
Embedding AI into operational technologies is a critical part of AI-based industrial digitalization. Aspen Technology’s AIoT Hub offers production-grade data management and cloud infrastructure to help companies derive business value from industrial data assets. Information Technology, for example, provides the applications and infrastructure that power industrial operations while Operational Technology executes the physical value-add via real systems. In a recent press release, the company touted the potential benefits of AI and industrial digitalization.
Industry 4.0 companies are looking for new ways to increase efficiency, improve their profitability, and ensure the safety of their operations. Digitalization provides a direct path to achieving these goals. With digital twins, managers can gain valuable insights from plant data, which leads to operational excellence. It can also reduce the need for personnel to walk into dangerous areas or travel long distances. A digital twin of an industrial facility, coupled with AI, can help companies solve operational challenges such as increased plant uptime and reduced maintenance costs.
In recent years, companies have leveraged the power of machine learning and artificial intelligence to create new consumption models. Amazon and Netflix have popularized this approach by creating data-based content channels. A global pandemic has also prompted a need for new consumption models. By leveraging machine learning and artificial intelligence, these companies have made it possible to forecast future demand and invest in the most relevant products. This type of technological advancement has become essential for companies that rely on data to improve their processes and increase profitability.
For example, a denial-of-service attack on a network could bring production to a standstill. This would be particularly detrimental to floor operators since they would no longer be able to access the information they need. Machine learning and artificial intelligence are also transforming production processes by allowing them to become more transparent and flexible. As more manufacturers become more familiar with this technology, it is expected to influence the manufacturing industry.
While machine learning is one of the most promising technologies available for manufacturing companies, several other AI-related technologies will play a critical role in factories of the future. For example, machine learning and artificial intelligence (AI) software use process-based data and rely on inference and pattern recognition to make predictions without requiring any code. The benefits of this technology to businesses are far-reaching and are becoming more prevalent each year.
IoT (Internet of Things)
The growth of the Industrial Internet of Things (IIoT) has spurred adoption in many industries. Through IIoT, manufacturers can optimize operations, reduce downtime, and improve process performance. Earlier, manufacturing was the industry that led the way in implementing IIoT, but other industries are following. In this article, we will explore the latest developments in IIoT and how they affect manufacturing.
As the number of connected devices grows, so does the volume of data generated by these devices. More devices generate more data, but they do so in different programming languages. Many machines and applications still rely on outdated programming languages. This makes it necessary to translate data to make it understandable for applications. This makes IIoT projects highly beneficial to manufacturing companies of all sizes. But, what about SMEs?
The IoT can help improve worker safety. Employees working in hazardous environments need to be alerted of potentially hazardous events. IoT sensor-based applications can help companies monitor employee safety and environmental conditions. The IoT can also help physicians monitor patient health. This makes it possible to monitor the condition of their patients without having to physically visit them. In the future, connected industrial buildings could be as safe as their physical counterparts.
Analytic software helps companies in many ways, including improving the quality of targeted advertising campaigns, reducing costs, and understanding visitor behavior. It also helps measure the effectiveness of marketing campaigns, brand awareness, and customer satisfaction. Analytics has historically been used in advertising, sales, and marketing communications, but has expanded to many industries, including manufacturing, logistics, and supply chain management. This article will discuss how analytics software can benefit your business and how to find a good fit for your needs.
BI solutions can help organizations realize the digitally enabled future faster by streamlining data preparation, visualization, search, and modeling processes. They can also help organizations scale analytics across sites and regions to meet key business objectives, such as productivity, safety, and environmental initiatives. BI solutions help organizations build a holistic digital transformation strategy by ensuring they’re able to identify the best practices and apply them across their enterprise. To get started, start by evaluating your current analytics software and identifying the best fit.
Once you have collected data from your assets, you can use that information to create predictive analytics. This can help you identify problems before they become major problems and improve production processes. For example, if a machine fails to produce an expected quantity, you can use predictive analytics to identify the reasons why it failed to deliver and make changes to optimize the process. This type of analytics can be applied to a variety of industries, and it will help you reduce costs and maximize yield.
Network security solutions
As manufacturing plants move closer to industrial digitalization, more data is being generated and stored. As more products, machines, processes, and data are integrated, cybersecurity and data integrity become more important. Industrial cybersecurity initiatives also need to consider plant availability and real-time functionality. An attacker’s ability to circumvent traditional security technologies is becoming more sophisticated. Moreover, current industrial security practices rely heavily on endpoint protection of ICS components, and this is not sufficient for cybersecurity.
In addition to endpoint protection, manufacturers should consider the benefits of advanced industrial cybersecurity tools, which can deliver visibility and insight into IACS, as well as dynamic and automated policy management. Industrial cybersecurity tools can also help secure cloud-based assets and communication flows. These solutions help manufacturers reduce operational risk and ensure the security of their production networks. To protect industrial cybersecurity, manufacturers should deploy an industrial demilitarized zone that monitors all IACS devices and communications. To achieve this, manufacturers can leverage cybersecurity applications such as Cisco Cyber Vision to gain ubiquitous visibility of their manufacturing networks and protect them from attacks.
With modern network capabilities, manufacturing operations can benefit from improved efficiency, productivity, and competitive advantage. Connectivity can enable remote access to experts and critical equipment, while new services can be accessed by factory workers. But while these benefits are attractive, they also pose an additional security risk. For this reason, security solutions must remain a central component of digitalization. There is no room for complacency in security. You need to be prepared for any eventuality.