Have we reached the end of manufacturing management?
The history of the systems and technologies that enable manufacturing management has been one of continuous expansion in both depth and breadth. Starting with the first material requirements planning systems in the middle of the twentieth century, computer use in manufacturing management quickly grew into a more comprehensive manufacturing resource planning (MRPII) that morphed into enterprise resource planning (ERP), the predominant information system supporting manufacturing management today.
Arguably, MRPII and ERP as it exists in the community today are somewhat crude and limited in their current state, especially when viewed in the context of artificial intelligence, machine learning, and the wonders of IIoT, cloud computing and ubiquitous global communications through the Internet. ERP is absorbing some of these technologies, of course, and in doing so is fast approaching its ultimate potential… the end of the journey: full and comprehensive management of the extended manufacturing enterprise including clients, partners, multiple production sites and the logistical links across the supply chain. I’m sure the marketing folks will come up with a clever name and acronym to describe this ultimate manufacturing management system, but until they do, and for the sake of discussion, let’s just call it System X.
The path from current ERP to System X is clear; simply continue to incorporate the existing and evolving technologies as enablers to tie the disparate parts of the enterprise together with the ultimate goal of better coordinating activities thereby reducing waste, lowering cycle times, and increasing flexibility to better serve customers.
Here’s how it all comes together:
The digital twin / digital thread establishes and maintains the foundational information that defines the products and processes. IIoT sensors and devices continually feed data from the plants, warehouses, service providers, and suppliers providing an unprecedented level of visibility throughout the entire life of the product from design through manufacturing and on to distribution and ultimate use or consumption.
Armed with this information, much if not all of it resident on the cloud, analytical programs keep a close watch on all activities, measurements, and requirements. Through the poser of simulation, the likely impact of any deviation from the expected can be modeled. Appropriate (human) managers are warned if the deviation threatens the timely completion of planned activities or poses other problems like quality issues or higher costs.
Since the model contains a rich history of operations, including previous deviations and how they were dealt with, machine learning allows the system to try literally thousands of various remedial actions, playing each of them out through to completion, to find the best action to take and accurately predicting the outcome.
These technologies are available today, gradually making their way into commercial software suites being deployed in real enterprises around the globe and building toward that ultimate System X. The remaining piece of the equation is to expand the reach of the system to the extended enterprise. It’s not enough to just manage and coordinate activities within the plant, or even within the entity (site, division or corporation). The visibility, modeling, and problem resolution functions should include supply chain partners (customers, suppliers, offsite manufacturing facilities) as well as service providers i.e., warehousing and transportation providers, distributors, etc. to form a fully coordinated ecosystem working together and fully focused on the efficient production and delivery of quality products per customer needs.
And because of the comprehensive and general nature of this integrated systems approach, it need not be limited to manufacturing. In fact, the inclusion of partners and service providers in the manufacturing supply chain inherently extends the benefits to non-product entities like customs brokers, infrastructure maintenance resources and many other types of businesses. Service-oriented operations can be modeled, monitored and managed just as effectively as manufacturing.
Is there truly an end to manufacturing management? Certainly not. As we work to achieve the vision outlined here, technology is sure to present us with additional capabilities that will provide us with even more opportunity to better manage processes and networks for even greater agility, efficiencies, and quality.