Apr 27 2018
Intelligent manufacturing encompasses a broad array of processes, products and technology, each of which is transforming industry composition both in manufacturing and throughout associated industries. From supply chains to the labor force, intelligent manufacturing is having material impacts on all facets of the manufacturing sector.
At the industry level, operators are expanding the breadth of their operations to encompass technology and services from other industries. While new products garner most of the attention, the process with which these innovative products are made and monitored represents the core of intelligent manufacturing. These new trends are enabling manufacturers to leverage big data to improve operations, but not without drastically shifting how they run their businesses.
Efficiencies from data leveraging
Data leveraging provides insights that connect the point of manufacturing (where a product is made) with the point of sale (where it is sold) and the point of use (where it is used). As companies seek to take advantage of this large-scale data, they have to fundamentally adjust their operations. Many manufacturers have evolved toward standardized platforms, pushing unique components and customization further down the assembly line. This process enables companies to benefit more from economies of scale.
Production costs decrease as product variability and specialization become more efficient. For instance, Ford Motor Company is simplifying its vehicle platforms to allow for standard chassis and power train components, which can then be further customized. Beyond in-factory specialization, the increased connection between factory technology and technology within the products themselves enables continuous monitoring, updates and specialization. Though this is most evident in smartphones, with manufacturers periodically prompting users to update software remotely, this functionality is now embedded in everything from cars to refrigerators.
“Designed in USA, Made in China”
Manufacturing companies combine engineering, IT, assembly, logistics, marketing, sales, services and corporate functions. These functions have typically been separated into distinct departments, but the growth of embedded IT in products, manufacturing machinery and logistics has driven the importance of data flow and necessitated investment in more high-skilled labor. This is resulting in more-efficient production but also more-diversified and -specialized operations within establishments.
This increased specialization, in particular, has become a driving force of global value chains. As manufacturing activity and the focus on new products evolve, there is increased potential for manufacturing activity to move back toward high-wage areas. This may flip the story of the previous several decades, during which knowledge centers grew in high-wage areas and component production occurred elsewhere. This has important ramifications for the economies of China and the United States; the former has traditionally focused on the component-production side of this structure, while the latter has become a center for high-wage design and innovation.
As technology progresses, however, it is likely that this dynamic will have to change as well, a fact that has impacted the recent trade talks between the United States and China. As tariffs have been proposed and trade arguments have risen in prominence, questions of intellectual property (IP) and positions in the supply chain have become essential to trade discussions. China has agreed to gradually eliminate its restriction on foreign ownership, reversing a long period of limitations intended on elevating domestic Chinese IP. This deregulation appears to follow in line with intelligent manufacturing trends. As manufacturing activities require less and less physical labor, it becomes increasingly important for states to entice leading companies to establish domestic locations.
The shift to high-wage labor
Average wages in the manufacturing sector have been steadily increasing. The average salary for workers in manufacturing has risen from $53,617 in 2003 to $59,292 in 2018. Additionally, the sector’s real output per hour has nearly doubled over the past 20 years. According to data from the Bureau of Labor Statistics, when indexed to 2009, output per hour in the manufacturing sector increased from 65.0 in 1997 to 108.3 in 2017. As technology has progressed, data aggregation and sharing at each stage of the manufacturing process has resulted both in greater efficiency but also in a blurring of industry distinctions. As a result, IT departments are expanding, and companies are using acquisitions to generate new value propositions with technology. Networked machines, for example, are beginning to fully automate and optimize production. A production machine can now detect a potentially dangerous malfunction, shut down other equipment that could be damaged and direct maintenance staff to the problem.
This newest stage of technological change has caused a divergence from recent long-term trends. The IT revolution of the early 2000s resulted in a rapid uptick in revenue per employee and a reduction in wages’ share of revenue. As production became more efficient through robotics and process tracking, US manufacturing labor became rapidly more productive. Additionally, this has not simply been restricted to high-technology industries. For example, out of all 193 manufacturing industries covered by IBISWorld, revenue per employee grew fastest in the Paperboard Mills industry, where it increased an annualized 4.2% from 2005 to 2018. Wages’ share of revenue fell an annualized 3.4% during the same period.
More recently, sector-wide manufacturing trends have shifted slightly with the current technological revolution. Although productivity has not declined, its rate of expansion has slowed. As the integration of software and technology has generated greater need for highly skilled labor, labor costs have shifted. Whereas low-skill labor could work in tandem with the previous iteration of manufacturing technology, labor requirements are rapidly moving from physical processes to software-driven roles. Investment in new capital machinery is being overshadowed by investment in labor as a means of providing more-efficient production.
Edited by Kieran Newton. Designed by Anam Baig.