In 1913 Henry Ford invented the assembly line and forever changed the way the world made physical products. For more than 100 years, the industrial society launched new technologies, new industries, and educational programs focused on perfecting manufacturing and scaling automation via incremental improvements over time.
Process improvement techniques that utilize statistics and mathematical concepts, such as Lean and Six Sigma, created cottage industries helping manufacturers and service companies reduce errors, improve efficiency, and reduce the costs of goods and services. Tools like computer-aided designs (CAD) and robotic manufacturing, which leverage mathematical concepts, created new economic markets to help companies improve throughput. Universities, community colleges, and trade schools have advanced curricula to create new degree programs that produce a mathematically proficient workforce. That workforce will perfect the development of physical products via advanced manufacturing, industrial automation, industrial design, and applied mathematics and statistics. The results of these innovations have yielded companies that compete to reduce product cost, improve high-speed manufacturing capabilities, rapidly design and develop products, and dramatically improve reliability while lowering maintenance costs. Mathematics, through applied disciplines, has enabled the industrial revolution to reach its current heights in our developed societies and launched the notion of industry 5.0.
The world now faces new challenges given rise via the advent of the Information Age. In this new age, software—an intangible product—has taken over as a dominant driver of economic growth. Software is now an integral part of most products, including automobiles, airplanes, manufacturing equipment, and even entertainment. Yet, the software industry still lacks the tools, workforce, and methods to control development costs, error rates, and efficiency. In many ways, software development is still an artisan industry like our village blacksmiths from the early 1800s.
This craft vs. science concept made Henry Ford’s invention of the assembly line revolutionary. It was very difficult for Ford to scale the production of cars by teaching every employee to build an entire car. However, by breaking down the steps and defining them in mathematical terms, Ford hired and used less-skilled workers to perform one step necessary to build a car. By organizing each step and placing rigorous and algorithmic standards, he made a car for the masses.
Where we are today
In today’s world, software “assembly” still possesses that artisan, craft build concept. This approach limits the ability to automate software engineering. A quest is underway to find tools, protocols, and processes to introduce mathematics and algorithmic structures that enable the automation of systems engineering and software development. Technologies like compositional design and reasoning, program analysis, correct-by-construction code generation, and software-focused digital engineering will serve as critical capabilities to improve efficiency, the quality of software development, and the integration of software to physics-based system designs.
The question that remains is, “who will lead the race to transform the industrial base during the information age?” Many would argue that companies such as Microsoft, Google, Apple, Amazon, and Facebook are driving this transformation. They undoubtedly play a critical role.
However, many industry players will deploy math to software that have yet to emerge the same way companies were built via the market development of CAD application to physics-based engineering.
Recent work has begun to develop concepts that support creating scalable automation for systems – the next assembly line. The DARPA HACMS program demonstrated the promise of component-oriented engineering. The recently kicked-off VSPELLs program brings automation to systems engineers. New companies like Galois spinout, Tangram Flex, offer products to support the realization of component-oriented engineering with confidence.
Building on these technologies and investing in R&D fields like digital engineering, program analysis, code generation, artificial intelligence, run-time assurance, and others will pave the way for rapid advancements. The key to these emergent technologies is mathematical precision and the vision to see how they can update and improve upon the current techniques in the software industry. With the right tools and talent, industry 5.0 can be a reality that increases technical efficiency and creates a brighter future for our world.