The Thirteen Smart Technologies Shaping Industry 4.0

Three industrial revolutions have shaped our industrial processes. In the first industrial revolution, labor-centric production processes were mechanized through the use of water and steam power. The second was driven by moving assembly lines and mass production powered by electricity. The third was driven by electronics and the application of information technology as well as increased automated production. The fourth revolution or Industry 4.0 sees technology embed itself further in society with digital technological advances connecting all major stakeholders in core manufacturing activities.

Based on a study of 500+ engagements across 12 service providers (Accenture, Altran, Atos, Cognizant, Genpact, HCL, IBM, Infosys, LTTS, TCS, Tech Mahindra, and Wipro), we have identified 13 smart technologies shaping Industry 4.0 (See Exhibit 1). This PoV discusses the relative adoption of each technology and typical use cases.

Exhibit 1: Thirteen Smart Technologies shaping Industry 4.0

XX% = proportion of industry 4.0 engagements we studied leveraging the technology. It indicates the relative adoption of technologies

Source: HfS Research, sample set = 500+ Industry 4.0 engagements

1. Smart Analytics: Clients are already leveraging smart analytics to improve decision-making, and adoption continues to increase. Nearly 100 engagements that we studied (from a total sample set of 500) leverage smart analytics. In the manufacturing context, it refers to the systematic analysis of production and shop floor data to optimize manufacturing operations. Typical use cases for smart analytics include:

• Tracking of production data to optimize manufacturing processes
• Predictive maintenance modeling by analyzing real-time machine data
• Quality management from asset data monitoring

2. Robots: Robots are visible in main production lines and are working effectively in tandem with operators to increase efficiency, but their overall adoption is slow. Nearly 25 engagements that we studied (from a total sample set of 500) leverage robots. In the manufacturing context, robots are machines that can automatically carry out groups of complicated actions and can collaborate with humans. Typical use cases for robots include:

• Testing and validation of products through robotic inspections
• Precision manufacturing, such as drilling and riveting, and other critical requirements handled by robots
• In-house autonomous logistics using a robotic fleet that can interact with humans and other elements

3. Manufacturing Automation: Manufacturing plants are being automated to increase productivity and automation continue to increase. Nearly 100 engagements that we studied (from a total sample set of 500) leverage manufacturing automation. In the manufacturing context, it refers to the implementation of control systems to enable shop floor processes to work with minimal or no human intervention. This includes integration of disparate enterprise systems used in manufacturing for seamless data and information flow. Typical use cases for manufacturing automation include:

• Regulatory compliance management through automated data collection
• Automated workflow for manual data entry and machine control
• A central repository of data and improved reporting, driving the standardization of operation performance, and easy benchmarking

4. Digital Twin/Clone or Simulation: Clients are increasingly leveraging virtualization or simulation for ergonomics study, plant outlet design, and other purposes. Nearly 65 engagements that we studied (from a total sample set of 500) leverage digital twin or simulation. In the manufacturing context, digital twin or simulation is the implementation of a virtual manufacturing environment, in which operations are configured, tested, and optimized by creating a digital clone or twin of the actual production line. Typical use cases for simulation include:

• Improved product design and process improvement through virtual modeling
• Simulation software for less physical tests and validation of manufactured products
• Performance analysis by simulating real-life scenarios through digital simulations

5. 3D Printing: 3D printing or additive manufacturing is a hot topic for material and component research, prototypes, and spares, but we found a few case studies of 3D printing in production lines. Nearly 30 engagements that we studied (from a total sample set of 500) leverage 3D printing. Additive manufacturing is used for prototypes, spares, actual parts, and ultimately entire products. Typical use cases for 3D printing include:

• Reduction in the number of assemblies and weight reduction of components
• Design innovation through 3D printing
• Usage of 3D printers in manufacturing following the lean manufacturing principle 

6. Internet of Things (IoT): The IoT is a network in which physical devices communicate and pass on data. The manufacturing IoT exploits sensor data collected from machines on the manufacturing shop floor. There is strong interest in the IoT among service providers, but there are not many shop floor IoT case studies. Nearly 55 engagements that we studied (from a total sample set of 500) leverage IoT. Typical use cases for IoT include:

• Remote monitoring of manufacturing assets on a broad number of parameters ranging from small footprint embedded devices to large distributed control systems
• Improved machine design based on extensive data collected for critical machine parameters
• Shift in the asset maintenance system, i.e. from calendar-based maintenance to condition-based maintenance

7. Plant Cybersecurity: Clients are concerned about cybersecurity of their manufacturing plants, but the outsourcing has not picked up yet. Nearly 15 engagements that we studied (from a total sample set of 500) leverage cybersecurity. In the manufacturing context, cybersecurity implies security management of information technology (IT) and operation technology (OT) in manufacturing and plant facilities. Typical use cases for plant cybersecurity include:

• Cybersecurity solutions to protect plants and infrastructure that includes sensors, communication, and data platforms, as well as software applications
• Security solutions to comply with industry standards and governance

8. Cloud: Service providers are offering cloud capabilities in manufacturing, but it has yet to gain popularity among enterprises. Nearly 30 engagements that we studied (from a total sample set of 500) leverage cloud. In the manufacturing context, cloud engagements include the implementation of manufacturing and production systems on SaaS- and IaaS-based cloud platforms. Typical use cases for cloud include:

• Centralized serialization and genealogy solutions for different manufacturing parts of assembly lines for future reference
• Digital collaboration among different plants through a cloud-based hosting solution
• Tracking and accessing sensor data across the manufacturing value chain

9. Augmented Reality (AR): In the manufacturing context, AR is the augmentation of a real-world view of manufacturing operations, assets, and people with additional computer-generated pictures. In manufacturing and plant operations, augmented reality can be used to help the development process by visualizing a product in situ before conception or in a factory setting by showing an engineer additional information, such as thermal characteristics or schematics, while the engineer views the real object. Although the potential is great, the AR adoption is slow. Nearly 30 engagements that we studied (on a total sample set of 500) leverage AR. Typical use cases for AR include:

• AR-assisted in-service product performance monitoring and maintenance system that can be connected to a remote system for interactive assistance
• AR-enabled geo-fencing applications to identify material locations where the right material is available for the machine or operation

10. Virtual Reality (VR): In the manufacturing context, VR is the use of software to create images and sounds for imaginary or lifelike manufacturing plants or factories. Virtual reality in manufacturing and plant operations is used for many applications, including plant construction, plant maintenance, and operator training. While the potential is great, VR adoption is slow. Nearly 30 engagements that we studied (from a total sample set of 500) leverage VR. Typical use cases for VR include:

• Virtual reality–enabled engineering platform to develop new products or virtual factory layouts with an improved and interactive visual aid
• Training of factory operators and other professionals in a real-time view of actual surroundings combined with an overlay of intelligent virtual objects

11. Artificial Intelligence (AI): In this context, when a computer is used to mimic human cognitive functions, such as complex problem solving and learning, it is known as artificial intelligence. The use of artificial intelligence, machine learning in manufacturing, and plant operations includes setting parameters for plant operations and recognizing images and visuals using machine learning. At present, AI adoption is limited. Nearly 25 engagements that we studied (from a total sample set of 500) leverage AI. As enterprises will require more automated, intelligent decision-making capabilities, AI in manufacturing will evolve and could be a major differentiating factor for service providers. Typical use cases for AI include:

• Cognitive analysis of machine data and identification of process parameters responsible for plant productivity and product quality
• Deriving insights from unstructured data and feeding data to the product development stage
• Process optimization, including automation through operational data analysis

12. Visual Analytics: In the manufacturing context, visual analytics is the science and technology of analyzing visual information from pictures and videos to aid reasoning and decision making. The use of image analytics within the manufacturing sphere includes machine vision and video analytics in manufacturing and plant operations. While the potential is great, the adoption of visual analytics is slow. Nearly 30 engagements that we studied (from a total sample set of 500) leverage visual analytics. Typical use cases for visual analytics include:

• Visual analytics-based solutions for inspecting components and detecting defects on the shop floor
• Visual-enabled interactive console applications for images and export results analysis to provide real-time monitoring and alert functionalities

13. Small Batch Manufacturing: This entails implementing solutions that enable manufacturers to cost-effectively manufacture in small quantities. Though clients are implementing small batch manufacturing, the planning or implementation is not outsourced to service providers in any meaningful way. Only 10 engagements that we studied (from a total sample set of 500) leverage small batch manufacturing. Typical use cases for small batch manufacturing include:

• Planning and development of processes that enable small-batch manufacturing
• Implementation of small-batch manufacturing technologies

Bottom-line. Large manufacturing organizations are using some of the Industry 4.0 technologies in isolation, but the true potential of smart manufacturing will be achieved when all the technologies are leveraged in tandem as outlined in our Digital OneManufacturing framework. Manufacturers can achieve a significant increase in cost efficiency, time productivity, and flexibility by aligning and integrating their manufacturing processes and technology landscape across enterprises, which can enable mass customization.

HfS subscribers with a premium account can click here to access the HfS Blueprint Report, “HfS Blueprint Guide: Industry 4.0 Services 2017”