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The unique benefits of 5G could unlock $740bn of value in manufacturing in 2030. This is based on models generated from 100+ interviews and surveys with senior manufacturing industry executives. What steps should operators, manufacturers and others take to achieve these benefits?
Introduction: Setting the scene
Challenges and future opportunities in the manufacturing industry
The manufacturing industry is going through an era of digital transformation, often termed “Industry 4.0”. This is partly driven by new technology providing the underlying toolkit and a mechanism to improve the business model: cloud, artificial intelligence (AI) and machine learning, new connectivity technologies (5G, Wi-Fi 6, etc.), internet of things (IoT) and sensor technology, digital twins and robotics are all contributing to the digitisation of manufacturing.
Every manufacturer strives to improve efficiencies and grow its productivity levels. Most enterprises look for a 3% improvement in productivity year-on-year, which typically involves more than 100 different activities being reviewed and refined. One important metric used to track performance is Operational Equipment Effectiveness (OEE). OEE measures the effectiveness of a production line and evaluates three factors to give an overall score – availability, performance and quality.
- Availability: operating time as a proportion of planned production time. Availability is reduced by unplanned downtime, i.e. time where production is stopped owing to unforeseen issues.
- Performance: the extent to which machines are producing output at their optimal rate, i.e. the theoretical maximum speed of production. This is reduced by machines not being in perfect condition.
- Quality: the percentage of output that is defective, or that requires rework.
- There are three challenges facing manufacturers in all markets that are driving the need to accelerate OEE improvements:
- Global competition. Manufacturers must find ways to continuously be more efficient to compete at lower prices or adopt new business models as revenues from the traditional model of selling products are squeezed.
- Changing consumer demand. Consumers increasingly expect products to be available “on- demand” and that they be fully customisable, putting pressure on manufacturers to reduce cycle times and create unique products whilst maintaining efficiencies.
- Labour skills shortages. The introduction of new technologies creates demand for new skills and the manufacturing industry is struggling to attract new talent, with an estimated 2.4 million positions (or 15% of the total workforce) to be unfilled by 2028 in the US alone.
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The role of technology in addressing challenges
The key to addressing the above challenges is through improving efficiency – technology will drive this efficiency by enabling rapid digital transformation. Effective use of data is key to making better decisions, however its real benefits will come from creating new business and operating models.
Effective use of data is key
The catalyst to unlocking efficiencies is the generation of richer information and insight, and the ability of users to have simple and real-time access to that information so that better decisions can be made faster. Four key technology pillars underpin these two change drivers.
The four pillars of technology that will help in driving efficiency
Source: STL Partners
Information and insight
- Data. Big data and its potential value in bringing new insights to organisations has been hyped in recent years in many industries. This holds true in manufacturing and industry 4.0 where technological advances allow richer and more granular data to be collected on machines and processes in the plant. One key factor is the ability to collect data using the appropriate sensor. In manufacturing, there has been a proliferation of connected sensors monitoring various conditions: temperature, status (e.g. valve open or closed), pressure, location, humidity, etc.
- Analytics. Although monitoring data points (remotely) can itself bring some benefits to the operating plant, analysis of time series data and cross-referencing with other data sources, combined with machine learning or artificial intelligence will significantly improve the way in which data can be used to enhance processes, asset use, supply chain, product design, etc.
Access and integration
As useful as having more information is, if those who need it cannot access the information when they need it, its value cannot be derived. The industry will therefore need:
- Connectivity. Underpinning the digital transformation of the manufacturing industry is connectivity – allowing information to be transferred reliably, securely, and in real-time, between processes and equipment within the plant and between different parties – the manufacturer, supply chain partners, maintenance providers, etc. Communication solutions such as 4G, Wi-Fi, and now 5G, help ensure the connectivity required can be delivered easily with the performance needed.
- Management. In order to be of value, the many sources of information on machines/processes/systems need to be integrated into existing systems and accessible by the right people at the right time. This would ideally be through a unified platform/portal to remove the need for siloed efforts.
Technology drives new business and operating models
By accessing and using data more effectively, manufacturers can make better decisions. For example, having an accurate view of processes in real-time and enriching this insight with AI can mitigate risks of error in production. Fundamentally, technology will help to change the way in which manufacturers operate:
- Flexible operations: consumers’ needs are changing more quickly now than ever before; the output a manufacturer produces will rapidly need to adapt to meet new demand. Connected systems that leverage the cloud or cloud-like infrastructure on premises are easier to change, as they are not tied to capital. This means they are flexible enough to create different products at short notice. These characteristics have been tied to IT systems and processes for years, but industry 4.0 moves this into the OT (operational technology) domain, i.e. to manage the machines and physical processes too.
- Sharing models: cloud and data technologies combined will enable shared, “as-a-service” models, so that manufacturers can share plant space and physical infrastructure to reduce their capital costs. By decoupling the systems and processes from the physical objects they control, the same assets and infrastructure can be used by multiple users.
- Service models: continuous insight on products allows manufacturers to provide services on top of the products they provide, for example using data from in-life products to offer maintenance services after sale or even moving to the Rolls-Royce model of selling “hours of operation” rather than “engines.”
Table of Contents
- Preface
- Executive Summary
- Introduction: setting the scene
- Challenges and future opportunities in the manufacturing industry
- The role of technology in addressing challenges
- Relevance of 5G in manufacturing
- What is 5G?
- Benefits of 5G for the manufacturing industry
- New and improved use cases and applications enabled by 5G
- Advanced predictive maintenance
- Precision monitoring and control
- Augmented reality and remote expert
- 5G impact: $739Bn increase in global manufacturing GDP by 2030
- It’s not just about money: 5G’s socio-economic benefits
- Next steps for the manufacturing industry
- Challenges with accessing 5G
- The manufacturing industry’s role in accelerating 5G adoption
- Conclusion
Table of Figures
- Figure 1: The four pillars of technology that will help in driving efficiency
- Figure 2: 5G’s technological capabilities and their implications for users
- Figure 3: Key benefits of 5G according to the manufacturing industry
- Figure 4: Use cases in the manufacturing industry enabled by 5G
- Figure 5: Advanced predictive maintenance mapped to 5G benefits
- Figure 6: Impact of advanced predictive maintenance on unplanned downtime relative to planned production time
- Figure 7: Benefits of advanced predictive maintenance in the manufacturing plant
- Figure 8: Using sensors to create digital twins in manufacturing
- Figure 9: Precision monitoring and control mapped to 5G benefits
- Figure 10: thyssenkrupp technicians using AR for technicians servicing elevators
- Figure 11: Augmented reality and remote expert mapped to 5G benefits
- Figure 12: Impact of 5G use cases on OEE
- Figure 13: Estimated impact of 5G on global manufacturing GDP (USD Billions) by use case
- Figure 14: Proportion of global manufacturing 5G benefit by country income level
- Figure 15: Proportion of global manufacturing 5G benefit – top 10 countries
- Figure 16: 5G impact on manufacturing GDP by region
- Figure 17: Fatal and non-fatal work injuries by industry (EU, 2016)
- Figure 18: How 5G in manufacturing benefits UN SDGs
- Figure 19: Scope of 3GPP standards releases
- Figure 20: Comparison of UK 5G roll-out target cities and the locations of automotive production facilities
- Figure 21: Telcos playing beyond connectivity
- Figure 22: Telco 5G business models
