To Fully Embrace the Future of Manufacturing, We Need to Take a Step Back

As we all know, technology is a science built upon a series of cascading events — and inventions. Without the wheel, there would be no automobile. Without electricity, there would be no telegraph, no telephone, no radio, no television, no computers, and ultimately, no internet. As far back as five years ago, futurist Mike Ivicak wrote, in his Jan. 1, 2018, article “The Startup,” advances in technology are an "area where past events can provide a good indicator of how future events can transpire. . . . When it rolled out the original Kindle in 2007 and Alexa in 2014, Amazon was anticipating customer demand by being at the forefront of technological advances.”

Accelerated learning curve

While it may sometimes appear steep, the learning curve in manufacturing has accelerated with each century since the first industrial revolution. And the advances just keep coming. But where are they going?

We have gained momentum, going from traditional coal-fired and steam-driven machines to smaller, faster, leaner, cleaner-powered machines to mechanized assembly to computer-driven assembly to robotics and machine learning. Where has this landed us?

We now are on the cusp of the most hands-off, efficient manufacturing processes ever imagined. So, what did we learn from the past that got us here? We learned that there are basic principles that govern both efficiency and effectiveness, such as Six Sigma, lean manufacturing, and other process improvement methodologies. The principles of lean manufacturing can significantly reduce waste, optimize resources, and enhance productivity in future manufacturing processes. In his book, Essential Tools for Process Improvement, Dr. Fred Rispoli demonstrates the importance of drilling down to uncover the real root causes of failure and inefficiency in manufacturing. This derives directly from William Edwards Deming’s statistical process control, which earned its place among the new standards for quality control in 20th century manufacturing. 

The first industrial robot

Consider that the first industrial robot by Unimation in 1961 revolutionized assembly lines, enhancing speed and precision. Further advances in robotics and automation will lead to even more efficient and flexible manufacturing processes, reducing labor costs and increasing output. The ultimate long-term benefits are incalculable. Consider the impact robotics has already made on surgery, for example.

We learned the importance of creating technologies that enable and foster human collaboration, such as enterprise resource planning (ERP) systems. We learned above all that every technology will ultimately be eclipsed by another in time. Henry Ford’s auto assembly line worked for a century . . . until Asian auto manufacturers came up with a better system by pre-assembling components for each step. Data storage media have evolved from tape to disks to flash drives. Will crystals be next? Probably, since they have  potentially much greater data storage capacity. 

What will get us to the next level in manufacturing? Understanding that what got us here may not get us there is the first step. As we search for ever better solutions, however, we still need to look back to analyze not only what has worked, but why it worked to get us here. For example, without lasers, we would never have achieved the ultimate precision needed for certain critical applications, such as drilling and surface marking, as well as imprinting identifying numbers. But what drove the need to apply the technology? Was it simply faster, smarter, less expensive production — or a more pressing underlying need? As we identify the missing elements in the past, we can begin to reshape the future of manufacturing.

Impact of advanced materials

Aviation is perhaps one of the best examples of looking at the past to create a better future. Learning the principles of aerodynamics gave rise to newer, improved designs. Every part of the process took on its ever-evolving shape — from physical appearance to materials used to propulsion systems. Discoveries in metallurgy, polymers, and composites have enabled the development of lighter, stronger, and more versatile materials for manufacturing. Future manufacturing can benefit from advanced materials to create innovative products with improved durability, efficiency, and sustainability.

Even smaller companies can now access the best of today’s cutting edge manufacturing technologies as costs come down. At my company, Exothermic Molding, we were able to bring in large-format 3D printing, receive training on the equipment, and offer our customers less expensive, faster, high-quality prototyping of plastic parts without the need to create molds. We now validate our parts and molds with laser scanning without ever touching them.

Advent of AI

Artificial Intelligence (AI) is another important technology for manufacturing. Are we ready to turn over our whole enterprise to AI? At Exothermic, we use AI (as a participant) in daily production meetings to summarize topics, conversations held (while recognizing voices), and summarizing assigned responsibilities. It works amazingly well and brings value. We’re at the outset of AI and the technological changes it brings. The next step is to explore what it can do for our operation. 

According to a survey by Deloitte, small and medium-sized enterprises (SMEs) across various sectors are increasingly investing in AI technologies to improve operational efficiency and competitiveness. A report by Accenture notes that small businesses globally are recognizing the potential of AI and are expected to double their adoption rates over the next few years. This reflects a broader trend of AI becoming more accessible to smaller enterprises.

AI a game changer for SMEs

For example, companies like Smith Robotics, a boutique robotics manufacturer, have harnessed AI to enhance the precision and flexibility of their robotic systems. This small-scale operation's ability to leverage AI showcases the democratization of advanced technologies, enabling even niche manufacturers to compete at the cutting edge.

In a similar vein, precision machining company Quantum CNC has employed AI algorithms to optimize toolpaths, reducing production time and minimizing material waste. This exemplifies how AI is not limited to large-scale enterprises but is becoming a game-changer for smaller players seeking efficiency gains.

Additionally, Innovate Tech Solutions, a small electronics assembly company, has embraced AI-driven quality control systems. By employing computer vision and machine learning algorithms, it has significantly reduced defects and enhanced product reliability. These success stories demonstrate that the integration of AI is not confined to a specific sector but is versatile and adaptable to diverse manufacturing environments.

In the current environment, we view manufacturing as a much more holistic endeavor. It’s not just about making a product. It’s about understanding the marketplace’s needs, learning how to best satisfy those needs, and anticipating future needs — as in the Amazon example above — all while considering and respecting each and every stakeholder’s needs, from the customer to the supplier to the employee, and ultimately to the planet. Understanding how we failed to do this in the past will help us to adjust our mindset as we create our future.