Digital technologies are transforming industrial production processes from design and engineering to manufacturing. IndianMark helps harness the full potential of Industry 4.0: greater flexibility in processes, increased productivity and revenue, and higher-quality production.
“Industry 4.0” refers to the fourth industrial revolution, which affects every manufacturing domain and comprises advanced manufacturing technologies that capture, optimize, and deploy data.
Put simply, Industry 4.0 makes factories “smart.” Such technologies as the industrial Internet of Things, artificial intelligence, and cyber-physical systems interact seamlessly, communicating and adjusting continuously. Businesses that fully understand and capture the value of these advantages will be best positioned to take on the challenges that lie ahead.
Industry 4.0 is revolutionizing the way companies manufacture, improve and distribute their products. Manufacturers are integrating enabling technologies, including Internet of Things (IoT), cloud computing and analytics, and AI and machine learning into their production facilities and throughout their operations. These smart factories are equipped with advanced sensors, embedded software and robotics that collect and analyze data and allow for better decision making. Even higher value is created when data from production operations is combined with operational data from ERP, supply chain, customer service and other enterprise systems to create whole new levels of visibility and insight from previously siloed information. This technology leads to increased automation, predictive maintenance, self-optimization of process improvements and, above all, a new level of efficiencies and responsiveness to customers not previously possible.
Developing smart factories provides an incredible opportunity for manufacturers entering the fourth industrial revolution. Analyzing the large amounts of data collected from sensors on the factory floor ensures real-time visibility of manufacturing assets and can provide tools for performing predictive maintenance in order to minimize equipment downtime.
Using IoT devices in smart factories leads to higher productivity and improved quality. Replacing manual inspection with AI-powered visual insights reduces manufacturing errors and saves money and time. With minimal investment, quality control personnel can set up a smartphone connected to the cloud to monitor manufacturing processes from virtually anywhere. By applying machine learning algorithms, manufacturers can detect errors immediately, rather than at later stages when repair work is more expensive.
Industry 4.0 concepts and technologies can be applied across all types of industrial companies, including discrete and process manufacturing, as well as oil and gas, mining and other industrial segments.
Starting in the late 18th century in Britain, the first industrial revolution helped enable mass production by using water and steam power instead of purely human and animal power. Finished goods were built with machines rather than painstakingly produced by hand.
A century later, the second industrial revolution introduced assembly lines and the use of oil, gas and electric power. These new power sources, along with more advanced communications via telephone and telegraph, brought mass production and some degree of automation to manufacturing processes.
The third industrial revolution, which began in the middle of the 20th century, added computers, advanced telecommunications and data analysis to manufacturing processes. The digitization of factories began by embedding programmable logic controllers (PLCs) into machinery to help automate some processes and collect and share data.
We are now in the fourth industrial revolution, also referred to as Industry 4.0, which is characterized by increasing automation and the employment of smart factories informed by data to produce goods more efficiently and productively. Flexibility is improved so that manufacturers can better meet customer demands using mass customization—ultimately seeking to achieve efficiency with, in many cases, a lot size of one. By collecting more data from the factory floor and combining that with other enterprise operational data, a smart factory enables better decisions to be made.
IndianMark’s Industry 4.0 consulting services take a holistic, sustainable, and scalable approach. We deliver by deploying proprietary tools and methodologies developed in our Innovation Center for Operations infrastructure. These offerings cover every manufacturing domain and comprise advanced manufacturing technologies that are empowered through data progression, storage, and optimization.
The classic example of additive manufacturing is 3D printing. Instead of prototyping individual components, companies can now produce small batches of customized products. The resulting advantages include the speedy manufacturing of complex, lightweight designs.
Augmented reality (AR) systems support a variety of services, such as selecting parts in a warehouse and sending repair instructions over mobile devices. With AR, companies can provide workers with real-time information that improves decision making and work procedures.
Autonomous robots can interact with one another and work safely side by side with humans. These robots will cost less and have an increasing range of capabilities over time.
In an Industry 4.0 context, the collection and comprehensive evaluation of data from many different sources—production equipment and systems as well as enterprise- and customer-management systems—will become table stakes.
The more production-related initiatives a company undertakes, the more it needs to share data across sites. Meanwhile, cloud technologies continue to get faster and more powerful. Companies will increasingly deploy machine data and analytics to the cloud, thus enabling more data-driven services for production systems.
It’s no surprise that Industry 4.0 boosts increased connectivity and the use of standard communications protocols. As a result, the need to protect critical industrial systems and manufacturing lines from cybersecurity threats rises dramatically. For this reason, secure, reliable communications, together with sophisticated access management for machines and identity verification of users, are essential.
Industry 4.0 allows companies, departments, functions, and capabilities to become much more cohesive. Cross-company, universal data-integration networks evolve and enable truly automated value chains.
Industry 4.0 means that more devices are enriched with embedded computing. This process allows devices to communicate and interact both with one another and with more centralized controllers. It also decentralizes analytics and decision making, thus enabling responses in real time.
Simulations are a cornerstone of the industrial revolution 4.0. They’re used extensively in plant operations to leverage real-time data and to mirror the physical world. Done right, these models allow operators to test and optimize settings in numerous variations, thereby driving down machine setup times and increasing quality.
Truly open automation, agnostic software and unique solutions that protect our planet are bringing tomorrow's industries to life today. This is the Industry of the Future.
Enterprise asset management (EAM) is essential for keeping operations running. Manufacturers implementing Industry 4.0 technologies can easily have many thousands of IoT-connected devices in their smart factories. To meet the demands of Industry 4.0, each must have maximum uptime to ensure efficiency. Enterprise asset management drives operational resiliency and agility by allowing remote monitoring of equipment, offering functionality to extend asset lifecycles and providing analytics for predictive maintenance.
Industry 4.0 is bringing about the convergence of information technology (IT) and operational technology (OT) systems, creating interconnectivity between autonomous manufacturing equipment and broader computer systems. OT data from sensors, PLCs and SCADA systems is being integrated with IT data from MES and ERP systems. Augmented by machine learning, this integration impacts the entire enterprise, from engineering to operations, sales and quality.
Augmenting manual inspections with AI-powered automated inspections cuts down on product defects, improving efficiency and minimizing false positives. Typically, the deep learning model can be quickly trained with existing images and videos. After it is connected to a smartphone camera, the automated inspection model is ready to be added to the production line.
The digital transformation to Industry 4.0 starts with collecting data, then adds artificial intelligence to make sense of that data. Smart factories employ IoT devices that connect machines and computers to get a clear picture of the manufacturing facility with real-time data. Then AI and machine learning are used to pull actionable insights from the large quantities of data.
Synonymous with smart manufacturing, Industry 4.0 is the realization of the digital transformation of the field, delivering real-time decision making, enhanced productivity, flexibility and agility.
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