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In 1947, manufacturing accounted for 25% of US GDP. By 2019, this proportion has fallen to 11%, and has fallen further throughout the COVID-19 pandemic. Industrial manufacturing-products such as flow control pumps, heating and air-conditioning systems, and food processing equipment-have been hit particularly hard. This decline has wide-ranging effects because this sector alone has caused more than half of the overall manufacturing contraction in the United States over the past 30 years. The industrial sector also employs the highest percentage of the manufacturing labor force in the country.
This article was co-authored by members of McKinsey's Advanced Industrial Practice: Ryan Fletcher, Mohit Jaju, Abhijit Mahindroo, Daniel Mongrain, Benjamin Plum, and Mark Sawaya.
In the industrial sector, the challenges faced by companies with revenues of less than US$2 billion are even more severe. In the past ten years, measured by total shareholder return, the value created by these small companies lags behind that of large companies by 41% (Exhibit 1). But as the U.S. economy continues to transition to the next normal, the shift to end-to-end market demand, coupled with the innovation of manufacturing processes, provides a way for these smaller industrial companies to improve.
The transformation is already underway. The traditional method of focusing on finding areas with the lowest labor costs is beginning to be replaced by technology-led, flexible and efficient manufacturing at locations close to the point of use. As the pace of cross-industry innovation accelerates, the ability to flexibly add product features and functions becomes critical. High mix and high configurability are increasingly replacing the "few options best suited" approach. Localized supply chains and shorter lead times may bring new opportunities to maintain minimal inventory.
New manufacturing capabilities will increase the demand for integrated networks of small, highly skilled labor and small, professional and flexible factories.
In order to fully realize these changes, continuous innovation is required-industrial manufacturing processes must become more flexible, efficient and precise. Fortunately, as measured by the number of new patents registered in the United States in the past 20 years, the rate of innovation in manufacturing technology has soared by more than 150% (Figure 2). Rapid innovation makes new processes possible—such as laser metal deposition and cutting, ultrasonic welding, and thermal diffusion galvanizing—must be developed, adopted, and expanded. These new manufacturing capabilities have improved accuracy, geometric complexity, and compatibility with advanced materials, and will increase the demand for small, highly skilled labor and integrated networks of small, professional and flexible factories. Of course, not all innovations are created equally or can add the same value. However, participants who adopt the right combination will gain a huge market share.
To help us understand the opportunities available, we developed the Manufacturing Process Innovation Index or MPI2. In order to analyze the industrial manufacturing space, we created a comprehensive classification consisting of seven core technologies such as forming, forming and joining; 39 technologies such as casting, milling, and welding; and 194 discrete processes, such as extrusion molding and laser cutting And fused deposition (Figure 3).
We determine the pedigree of each process by evaluating three core capabilities—accuracy level, geometric complexity, and throughput speed—and three economic driving factors—compatibility with advanced materials, scalability, and development speed (Figure 4). This pedigree is then reflected in the MPI2 score, allowing the process to rank against other processes.
The first capability factor-precision-considers the evolution from the traditional multi-step iterative process to single-step, high-precision manufacturing. For example, medical stents are usually produced using three techniques: etching, electroforming, and die casting. The ability to achieve high accuracy in the first process is limited, requiring the application of secondary and tertiary manufacturing processes, such as surface milling and etching, to achieve the required level of accuracy. The shift to high-precision manufacturing has greatly improved accuracy and consistency, eliminating the need for subsequent processing operations.
The second capability factor-geometric complexity-consider the ability to create complex, multi-dimensional shapes that are increasingly required for highly engineered products, such as aerospace steel alloy components or polymer-based dental restoration products tailored to the specific requirements of each patient . Many existing manufacturing processes, including plasma cutting, laser welding, and high-speed milling, can produce complex shapes, but additive technology is the most important of them. For example, in the automotive field that is beginning to adopt additive manufacturing, this technology can easily prototype and test metal engine parts with complex customized shapes. In production, it can finally achieve better performance in a smaller package.
The third capability factor is throughput speed. Many manufacturing process advancements are achieving faster throughput, while automation and process optimization are reducing preparation and cycle time. For example, traditional molding techniques, such as matrix molding, can only produce one piece per hour. Blow molding technology has increased this to 1,500 pieces per hour, while extrusion molding can now produce more than 500 pieces per hour, depending on the materials involved.
In addition to inherent capabilities such as accuracy, speed, and geometric complexity, other factors can also add value. Many industries are using advanced materials to improve performance, such as carbon fiber, high-strength steel, and ceramics. These new high-strength, lightweight materials are superior to traditional aluminum and steel alloys in terms of strength-to-weight ratio performance, robustness, and durability: for example, the new aircraft design includes 50% carbon fiber-reinforced polymer for use in cabins and aircraft. Wing and the fuselage have helped reduce fuel consumption by 20% in the past 20 years.
The shift to carbon fiber in wind turbine blade manufacturing has also improved performance. This lighter and stronger material allows thinner and larger blades to be made, increasing output from 1.3 MW/hour to over 8 MW/hour. In addition, lighter carbon fiber blades also reduce the pressure on the turbine and tower, further improving performance and service life. Although the value of these materials is obvious, processing them is more challenging because it requires specialized manufacturing techniques and capabilities.
The economic scalability of a given manufacturing process can also add value. The ability of the process to increase output and optimize large-capacity is directly related to the maximization of return on investment in related equipment. For example, improvements in laser cutting technology are meeting the industry's demand for better cutting performance. Due to innovations (including nesting software, fiber technology, and automatic material feeding) that have significantly improved the scalability of laser cutting, the output has continued to increase, while the cost per piece is falling.
Finally, the development speed of a particular industrial manufacturing process will also have an impact on value. The US patent application is an example. The evaluation of 194 independent process applications clearly shows that the pace of innovation in most processes has accelerated. Consider bending of the elastic body. The first patent for this process was issued in 1984, so it is a relatively new innovation. Compared with the previous ten years, the number of new patents for this technology has increased by 4,700% from 2010 to 2020. The number of patents for more traditional, long-standing processes is also increasing. The first patent for trephine was issued in 1847. Compared with the period from 2000 to 2010, the number of patents from 2010 to 2020 has increased by 450%.
The first stage of determining the MPI2 score involves evaluating the profile and products of the industrial company. This assessment is then used to map the company’s capabilities and key technologies and technologies that are manufactured (for equipment suppliers) or utilized (for manufacturing service providers).
From this map, we can use the MPI2 model according to three core capability factors (accuracy level, geometric complexity and throughput speed) and three economic driving factors (compatibility with advanced materials, scalability and development speed) Score each company. Each is weighted according to the relevant market segment (equipment supplier or manufacturing service provider), and the total score is calculated by adding the individual scores for each technology.
We apply the six parameters that make up the manufacturing process innovation index to two parts of the industrial value chain: equipment suppliers, whose tools are used in industrial manufacturing and assembly processes, and manufacturing service providers, which manufacture customized components, for example, as per OEM specifications Manufacture of precision castings and machined parts. We found that these six parameters are closely related to financial performance, and MPI2 is a particularly important indicator of a company's ROIC (Exhibit 5). (For more information on our assessment methodology, please see the sidebar "Determining MPI2 Score".)
In order to better understand how the MPI2 score is determined, let us delve into the division, which is one of the seven industrial manufacturing technologies. Within the range of available cutting technologies, laser cutting has the highest MPI2 score (25). During the study period, it also provided year-on-year growth of up to 10%, surpassing other processes. Laser cutting has benefited from the steady pace of innovation over the past 60 years, from the earliest commercial cutting CO2 lasers (in the 1960s) to the recently introduced optical feedback system with improved accuracy, making it possible to process advanced materials and three-dimensional geometries.
Among the six factors that define the MPI2 score, laser cutting provides higher accuracy-up to 0.025 mm and reduced thermal stress, as well as throughput speeds of 1,000 to 5,000 inches per minute, eclipsing waterjet and plasma technology. The enhanced capabilities of laser cutting make it the highest MPI2 score of all technologies, offsetting the high cost and higher cost of fiber lasers-up to $2 million-equipped with similar CO2 lasers.
In recent years, welding technology has also been greatly developed. The first arc welding method using carbon electrodes was developed as early as 1880. The commercialization of metal shielded arc welding in 1950 made it possible to manufacture large steel structures. In 2008, laser-arc-hybrid welding was developed. By 2017, more than 2 million industrial welding robots have been put into use worldwide.
We can also look at the range of processes available in welding technology and check their MPI2 scores individually. Although flux cored arc welding has the lowest growth rate of the four technologies, its market size is 7.5 billion US dollars, far exceeding the recent runner-up: shielded metal arc welding (1.4 billion US dollars) and tungsten inert gas arc welding (700 million US dollars) Dollar). In addition, flux-cored arc welding exceeds or matches the highest MPI2 score in half of the category drivers, and outperforms all other technologies in terms of accuracy, throughput speed, and development speed.
The pattern of suppliers supplying industrial manufacturing equipment is fragmented and highly competitive. The top 20 to 30 companies with an average revenue of approximately US$9 billion account for 25% of the market. The remaining 75% of the market share is scattered among more than 5,000 organizations, most of which are privately held, with revenues ranging from US$20 million to US$2 billion. Traditional technology still accounts for most of the revenue, especially in primary forming and forming, such as rolling, bending and forming. However, the wave of innovation in the industrial manufacturing process in the past 20 years has spawned many smaller, focused equipment suppliers.
In addition, the performance level is sticky. Of the 40 public equipment suppliers we analyzed, only 3 (previously in the second and third quartiles) were among the leaders in the top quartile in six years. Companies starting from the lowest quartile still exist (Exhibit 6). As mentioned earlier, the MPI2 score is closely related to performance. Consider the average return on investment of 40 companies from 2017 to 2019. Those companies that are classified as leading or rising have a much higher percentage of adopting high MPI2 technology (Exhibit 7).
MPI2 helps demystify the factors that drive value creation in a complex manufacturing process environment, but research results are only valuable when stakeholders act on insights. We have identified important steps that company leaders, board members, and investors can take after reviewing their manufacturing processes through MPI2.
High MPI2 leaders continue to innovate by pursuing new processes, improving existing products, and actively shaping investment portfolios through mergers and acquisitions. In organic innovation, this means developing new manufacturing processes with the greatest potential that can create value through the following activities:
Organic growth of industrial companies may be difficult because of their fragmented structure and limited ability to support large-scale new technology investments, especially for companies with annual revenues of less than US$2 billion. However, there are many opportunities for integration and inorganic growth, and an active M&A strategy can obtain new manufacturing processes faster.
Organizations that effectively deploy mergers and acquisitions can increase the range of products they offer in manufacturing processes that may generate high value. They can also provide end users with a complete ecosystem—expanding scale and market influence—and create free revenue streams through smart products that improve customer operations.
Effective execution also includes measures to improve some of the dimensions measured by MPI2: throughput speed, accuracy, geometric complexity, and compatibility with advanced materials. Ideally, this improvement will happen quickly—possibly within four to six months after the start of the project—to help the company stay ahead of the competition. Finally, leaders should not hesitate to cannibalize their current portfolio by eliminating legacy projects and seeking high-growth opportunities to increase their competitive advantage.
Strong execution requires a new script (Figure 8). For example, improving the level of innovation requires a clear vision and strategy, an end-to-end willingness to innovate, and a highly mobilized organization that can quickly and effectively promote change on a large scale. Company leaders must not only become product champions, they must also create new ecosystems through mergers and acquisitions, evaluate the value of synergies and ensure strong governance processes. The company must also establish strict rules for expansion.
To help derive value from MPI2 insights, board members should first evaluate their company’s position, strategy, and governance to determine whether these factors support growth. For example, board members should identify the parts of the manufacturing process that can provide the most value and the end markets that can benefit most from them. They should also determine whether the company's innovation, product development, and product improvement methods are consistent with the chosen strategy.
Finally, board members should not only ensure that their company has a governance model that can measure progress, but they should also choose the best internal and external indicators to track (for example, with product performance, regulatory issues, customers, and competition).
Investors should determine the manufacturing processes and basic technologies that generate value or may generate value in the future. They should also judge how a particular company’s portfolio will compete on the innovation dimension most closely related to value. Finally, investors should determine whether the company’s manufacturing process and technology’s target end market momentum is increasing.
The timing of investment is also important. Ideally, investors should examine the innovation cycles of different emerging technologies before deciding when to allocate funds. Important considerations include market traction; the rate of disruption of related manufacturing processes, technologies, and processes; and the impact of regulatory changes or geopolitical headwinds on product supply.
Finally, investors must consider how they want to obtain value. For example, they may wish to increase revenue by combining multiple high MPI2 products into one product portfolio. They can also try to achieve cost synergies by creating high MPI2 products with as many commonalities and platforms as possible to optimize development expenditures. They may enhance this with more profitable software products, unlocking it through the creation and expansion of a digital ecosystem.
The frequency and severity of shocks disrupting industrial manufacturers have increased in the past year and are expected to increase over time, whether from supply chain, labor, or product demand challenges. As companies throughout the industrial manufacturing value chain try to reduce these risks by evaluating new options such as nearshore outsourcing and production flexibility, the importance of high-value manufacturing technologies is rising.
For a complex landscape with countless technologies, materials and processes, determining the source of value creation is challenging. MPI2 can help demystify this field and help operators, board members, and investors drive the next frontier of industrial manufacturing performance in the United States and other regions.
Ryan Fletcher is an associate partner in the McKinsey Southern California office, and Abhijit Mahindroo is a partner in the office. Mohit Jaju is an assistant partner in the Houston office; Daniel Mongrain is a consultant in the Montreal office; Benjamin Plum is an expert assistant partner in the New York office; Mark Sawaya is a consultant in the Cleveland office.
The author would like to thank Mackenzie Donnelly, Ankitha Kartha, and Armand Latreille for their contributions to this article.
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