Jigsaw puzzles date back to 1760, when European mapmakers pasted their maps onto wood and cut them into small pieces. Digital manufacturing today would test the limits of the best puzzle solvers of any age, with its need to quickly generate and modify designs, create accurate forecasts, set operational plans, and coordinate logistics and workforce resources. A series of interlocking, targeted applications, each aiming at one piece of the puzzle and running on a single collaborative platform, is the foundation for solving today’s digital manufacturing needs.
Simulation has emerged as the key app for solving the puzzle of digital manufacturing. Simulation makes the abstract concrete—how can I see and try everything beforehand to make sure it works? And there are few things more difficult to get your arms around than a digital manufacturing enterprise and its extended ecosystem of supply-chain partners.
Simulation, in creating a digital representation of a digital manufacturing scenario, then gives birth to a Digital Twin: digital duplicates of the products, processes and workflows at the heart of the digital manufacturing puzzle. They coexist in a symbiotic state: digital manufacturing feeding back status and performance data to its digital representation, the digital double cataloging best practices and simulating improvements for the next real-world iteration.
The follow-on piece of the digital manufacturing jigsaw is figuring out how much you’re going to sell to inform build schedules, parts sourcing and delivery strategy. The puzzle-busting app here is Probabilistic Forecasting: recognizing there is no way you can come up with a precise number for demand, but that you can determine a range of answers and outcomes, along with the probability that each will best approximate your incoming orders.
Then you’ve got to continuously track and fine-tune your digital manufacturing process. Here, applications like Manufacturing Execution Systems, Manufacturing Operations Management and Manufacturing Intelligence function like a health-monitoring wearable on your wrist, only they “wrap around” your production facilities to track its vital signs.
Machine learning is the crown jewel of the bunch. It can follow every action, every step, every process, scooping up vast quantities of data and crunching it to uncover patterns, make suggestions, and in some cases automatically adjust your operations on the fly. It’s “cognitive” powers far exceed those of any one person or team to make sense in near real time of the fast-moving, puzzling universe that is the digital manufacturing enterprise.
There is of course a multitude of additional functionality that surrounds these five apps: Generative Design to shorten design cycles, linkage to the Internet of Things to stream real-world data from products and processes back to the Digital Twin, social media monitoring to assess consumer sentiment and potential demand, user-configurable dashboard intelligence, etc.
But these five applications stand out, all running on a single, unified, digital collaborative platform for ease of communication and the oft-cited “single source of truth”—in this case, the in-process or completed puzzle, instantly visible to all the hands putting the pieces together.
Editor’s Note: To learn more about solving manufacturing puzzles check out Dassault Systèmes DELMIA Quintiq solutions, used to plan and optimize complex production value networks, optimize intricate logistics operations, and plan and schedule large, geographically diverse workforces.
John Martin writes about technology, business, science, and general-interest topics. A former U.S. correspondent for The Economist (Science & Technology), he writes for the private sector, universities, and media, and can be reached at jm@jmagency.com.