APU Business Original

Industrial Automation: From Henry Ford to Elon Musk (Part I)

Pinterest LinkedIn Tumblr

By Dr. Justin Goldston
Faculty Member, Dr. Wallace E. Boston School of Business

Note: This article is part 1 of a two-part series on industrial automation.

Industrial automation can be defined as the use of technologies and automatic devices to control machines, systems, and processes. Although it can be argued that automation itself dates back to 3200 B.C.E. with the invention of the wheel, automation within the manufacturing industry was introduced in 1913 with the Ford Motor Company’s assembly line.

This method of automation can be referred to as “fixed automation” by which the Ford company produced a large number of vehicles each year. With this fixed, repetitive automation model, however, Ford was limited to initially producing one type of automobile, the Model T, before introducing the Model A in 1928.

Fixed Automation, Programmable Automation and Flexible Automation

As automated production systems emerged within the manufacturing industry, systems were classified into three distinct types: fixed automation, programmable automation and flexible automation. Many organizations continue to use the Ford production model because it aligns with their business strategy.

It was not until the 1930s that switches, relays, and timers were introduced into the auto industry, giving rise to industrial automation. The introduction of computational tools and technology made organizations more efficient, reduced downtime, and made environments safer through the use of technology.

With customer demands requiring business organizations to create models to address the need for mass customization, corporate leaders began to integrate machines capable of being reconfigurable through programmable automation. The goal of programmable automation was to produce a larger variety of products without the capital expense to purchase additional machines.

Flexible automation was introduced into manufacturing environments to minimize the time lost when reprogramming and reconfiguring machines and systems while changing tools and fixtures to produce new lines of products. As an extension to programmable automation, flexible automation allowed organizations to change configurations to produce new products with no downtime or wait time, eliminating the need to reprogram the machinery before beginning production of new products.

In 2011, the German Government Created ‘Industrie 4.0′ to Promote Technological Integration in Manufacturing

In identifying the manufacturing industry as a laggard in technology and innovation in 2010, many manufacturing organizations automated their factories and field operations with new products and hardware. In 2011, the German government created a project called “Industrie 4.0.” The goal was to promote the integration of technology within manufacturing and move out of the traditional automation age of Industry 3.0.

The German government’s vision was to create what some called a “smart factory” that would include cyber-physical systems, cloud computing, and the Industrial Internet of Things (IIoT). It was intended to result in interoperability, the decentralization of information, real-time data collection and increased flexibility.

As Industry Entered 2020, There Began a Shift from Hardware to Software

As industry entered 2020, software controlled the same processes. As leaders of organizations identified uses for technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Edge computing for industrial applications, there began a shift from hardware applications to software applications, hence the terms IIoT or “smart factories.”

Although the delivery method changed from hardware to software, each step of the Automation Pyramid still required functionality and logic. Organizations continue to make this transition at Level 4 of the Automation Pyramid, where companies are moving their Enterprise Resource Planning (ERP) systems from on-premise applications to the cloud.

In doing so, corporations have reduced the overhead and maintenance costs incurred by housing servers within their organization to a Software-as-a-Service (SaaS) model. They can pay a monthly or subscription fee for the vendor to host, maintain and upgrade their systems. Although organizations have implemented aspects of the German government’s vision, a large majority of manufacturers continue to use the devices and tools of Industry 3.0 effectively.

Are We Moving into Industry 4.5?

Nikola Tesla in 1926 dreamed of a “connected world.” Martin Eberhard, Marc Tarpenning, Ian Wright, JB Straubel and Elon Musk made it a reality in 2003 with their creation of Tesla Motors.

With the vision of producing an entirely electric car, Tesla Motors disrupted the automotive industry with its innovative thinking. After shifts in leadership, the departure of founders Eberhard and Tarpenning, and mounting financial troubles in 2009, the company went public in 2010 under Musk’s leadership.

 As the popularity of the Tesla automobile grew, the organization announced the building of a “superfactory” in 2014. In what Musk refers to as a gigafactory, the Sparks, Nevada, facility was built to produce batteries that store gigawatt-hours of capacity. The first gigafactory is on schedule to becoming the world’s largest building by footprint.

Musk Took Ford’s Vision and Turned it into the Gigafactory

In blending sustainable practices and automation, Musk took Ford’s same vision and turned it into the gigafactory where vehicles are built by automating many processes. Although automotive manufacturers have used industrial automation for years, the level to which Tesla Motors automated its gigafactory is unprecedented. As Tesla increased automation at its other facilities to address its growing mass consumer demand, the automaker experienced a minor setback in 2017, when its Freemont, California, location shut down twice in two months due to potential over-automation.

With the efficiencies Tesla realized through industrial automation, the company has reduced the price of its automobiles, further increasing the demand for its electric vehicles on a global scale. Tesla has opened another gigafactory in Shanghai, China, and announced the construction of additional gigafactories in Austin, Texas, and Grünheide, Germany. Tesla now has an opportunity to reflect on the lessons learned at Sparks and Freemont for developing an automation strategy at these locations.

Small steps have been made during the first decade of Industry 4.0 to align with the German government’s vision. The next decade may introduce the next phase of Industry 4.0: Industry 4.5. With the inclusion of AI, ML, blockchain and other technologies that are being adopted within various industries, what does the future hold?

In the second part of this series, we will look at a few of these emerging technologies. In the meantime, ask yourself:

  • Is it a bold statement to propose that we are moving into Industry 4.5 with objectives of Industry 4.0 still outstanding?
  • Are there risks (i.e., cybersecurity risks) that must be considered when adopting these technologies?
  • Will this automation replace jobs within industries? If so, which industries pose the highest risk?

About the Author

Dr. Justin Goldston is a faculty member with the Wallace E. Boston School of Business. He spent a number of years in the management consulting industry, where he worked on digital transformations and optimizing supply chain networks. Dr. Goldston holds a Ph.D. in leadership and organizational change from Walden University, an M.Phil. in leadership and organizational change from Walden University, an M.P.S. in supply chain management from Pennsylvania State University, and a B.S. in supply chain management from North Carolina A&T State University.

Dr. Goldston teaches undergraduate and graduate-level supply chain and logistics classes at American Public University, Penn State University, and Georgetown University. He is a five-time TEDx speaker on blockchain. He has published numerous peer-reviewed journal articles, and is the author of the forthcoming book “AI for Good: Achieving Sustainability Through Citizen Science and Organizational Citizenship.”

Comments are closed.