Today’s supply chains and manufacturing operations are global, highly efficient, and carefully tuned. At the same time, the COVID-19 black-swan event has demonstrated painfully that they are also fragile and lacking transparency at times when faced with unexpected disturbances. The various interruptions led to a shortage of essential goods, ranging from PPE and smartphones to critical industrial parts impacting the final assembly of cars and ventilators.

The consensus is, that we urgently need to improve resiliency, agility, and visibility of global supply chains moving forward to avoid similar issues in the future.

Future supply chains need to reinvent themselves, embracing disruptive technologies and reimagined processes—thus creating digital supply networks that are capable of rapidly adapting to all kinds of scenarios. One crucial capability is to leverage a diverse set of organizations by creating efficient, ad-hoc value chains, including local manufacturing resources.

This vision aligns with the strong desire of reshoring manufacturing operations shared by many leading economies around the globe, including the United States, Japan, South Korea, and several countries in the EU. All have announced programs and/or policies to reevaluate essential manufacturing operations in light of recent events and some even plan to elevate selected manufacturing operations to strategic resources and strongly incentivize reshoring.

However, at this point we do not see a significant number of relocations of many high-value and essential manufacturing operations from China, in particular. The reasons are manifold, yet a key factor preventing rapid reshoring are the significant advanced manufacturing capabilities, resources, and enabling infrastructure that are available and, most importantly, visible and accessible. In contrast, the U.S. has significant advanced manufacturing capabilities, yet they are often hard to locate and access. Addressing these crucial barriers is key to motivating and enabling the reshoring of value-adding manufacturing operations and other critical components of today’s supply networks.

To get a better grasp of ‘how’ these barriers can be overcome, we need to take a look at companies that have stood out when it comes to navigating the crises. More specifically, technology companies with a digital DNA such as Amazon and Tesla. Tesla managed to rapidly retool its operations to produce ventilators with car parts, while Amazon moved quickly to employ wearables and AI-powered vision systems to increase worker safety. Both companies have a digital core that provides better visibility of their manufacturing resources and capabilities, allowing them to be more agile and resilient in the face of disruption.

Abstracting from these successful examples, it becomes apparent that there is a critical component missing to truly enable agile ad-hoc formation of digital supply networks making large scale reshoring economically and technically feasible: an easy-to-use, effective, efficient, and cybersecure way of identifying manufacturing resources and capabilities. Manufacturing resources and capabilities include part designs and features, machine tools and equipment, capabilities, skilled labor, etc.

In essence, we need a “Google for manufacturing” that enables us to search for, for example, complex part designs or CNC machining capacity. This does not imply Google per se, but rather what Google stands for today. A straightforward and highly effective way to find and consume digital information and knowledge—in essence the access, power, and user-friendliness Google brought to web search. A platform that significantly reduces the barriers and effort to search for manufacturing resources ad capabilities.

A core technical obstacle is how to describe diverse manufacturing resources and capabilities in a way that aligns with the requirements of today’s search engines and semantics. To illustrate the challenges, let’s discuss two different examples: available manufacturing capacity and complex part designs. For available manufacturing capacity, we can either focus on the machine tool and its specifications, which is comparably easy, or focus on its capabilities to manufacture parts with certain requirements, which is more inclusive. For the former, one might search for a 5-axis CNC milling center with horsepower and x/y/z travel metrics. However, in the case of the latter, one might expand the search to add metal additive manufacturing as an option that would have been excluded previously.

For some applications such as small-batch sizes and time critical parts, this is a distinct advantage. Besides increasing the agility and resilience of supply networks, it will also reduce significant waste that we see today in product design and manufacturing. Many identical (or really similar) parts are designed from scratch every day across the globe, as there is no efficient way of finding the designs effectively and efficiently across organizations or even within an organization. There are different approaches on how to do that, from better semantics, to ontologies, to new and innovative ways to describe design features uniquely using persistent heat signature.

Manufacturing is a broad and complex domain; therefore, these two examples are only a tiny sample of the diverse set of items that need to be annotated in a searchable way to enable such a comprehensive manufacturing search engine. A positive side effect of such a “Google for manufacturing” platform is the democratizing of manufacturing and design by making it more accessible to anybody with a minimum technological literacy.

Creating such a “Google for manufacturing” platform is not a trivial undertaking; it requires coordinated action in several dimensions. The technical challenges and possible pathways to overcome them have been illustrated above. However, this is not a purely technical problem but an interdisciplinary task encompassing issues related to trust, business model innovation, risk-sharing, liability, and many more. Questions regarding how to ensure that such a manufacturing capabilities marketplace will not be dominated by few large organizations are valid and have to be answered to truly make this vision a reality.

So how can that play out? On the technical side, we need to start by mapping manufacturing capabilities, and if that is worked out, we can expand the platform to include more complex manufacturing resources, including complex design features and skills.

It is crucial that such a platform has broad support from industry and policy, and is overseen by a trusted, neutral entity that provides a long-term, sustainable perspective. This could be either an industry association with federal (policy) backing or an established entity such as the Manufacturing USA institutes in the US or the EIT Manufacturing initiative in the EU, providing the required access, trust, resources, and leverage directly from the start. Joint support from industry, academia, and policy makers is crucial to make such a transformative vision a reality – and let’s keep in mind, Google after all, started as an NSF-funded research project!

Thorsten Wuest, Ph.D., is an assistant professor and J. Wayne and Kathy Richards Faculty Fellow in Engineering at West Virginia University, globally recognized as one of SME’s 20 most influential professors in smart manufacturing, and co-author of Digital Supply Networks: Transform Your Supply Chain and Gain Competitive Advantage with Disruptive Technology and Reimagined Processes.