Manufacturing Trends: Microfactories

Conventional manufacturing strategies have typically focused on economies of scale with linear production lines and extensive product distribution networks integral to business viability. These facilities tend to necessitate enormous capital investment, require large surface areas and considerable construction times as well as long amortization periods. Such constraints make it difficult for newcomers to enter the traditional manufacturing setup and, thereby, limits innovation. The carbon footprint of this product-push approach is also significant. Wastage due to overproduction and overcapacities is another issue.

Global developments are also impacting crucial strategic manufacturing decisions. Wages in previously low-cost labour regions have been on the rise in the past decade. For instance, the average manufacturing wage in China doubled between 2012–2020, and is now at a comparable level to Portugal. In addition, climate concerns have resulted in decarbonization becoming a centerpiece of policy, which has compelled manufacturers to look at their product value chain with a more holistic view of the lifecycle rather than merely focusing on production and usage. Long lasting supply chain issues have exposed the frailties of a globalized just-in-time production strategy. End-users are also becoming more conscious of how their purchases reach them.

The flexible and modular setup of microfactories allows manufacturers to swiftly scale up operations or repurpose failing product lines quickly and even relocate activities in case of regional conflicts. Changes to product design can also be accommodated easier.

The understanding of what exactly constitutes a microfactory ranges from mini milling machines in Do-It-Yourself workshops to the more complex robotics-centric manufacturing of vehicles and heavy machinery. Microfactories invariably forgo traditional assembly line ‘Takt production’ in favour of highly automated production cells where multiple operations are carried out. Legacy manufacturers have thus far viewed microfactories primarily as avenues for prototyping parts or training employees, while small businesses and individual consumers have utilized them for small batches of goods that would otherwise be too expensive to produce in a traditional factory.

Although industrial deployment of microfactories as a source for high-value end-products or components has hitherto been rare, this concept is steadily gathering steam in the automotive, fashion and consumer goods sectors. Microfactories display plug-n-play opportunities for new market entrants, thereby encouraging innovation, whilst also opening up alternative equipment and facility ownership models such as Factory-as-a-Service and shared-usage.

Large-scale manufacturers may explore setting up microfactories closer to home for critical products and components that might have long lead times, seasonal scarcities or can only be sourced from select regions. This approach of increased vertical integration involves knowledge creation of intricate high-complexity products and processes from scratch, thereby increasing risk accumulation. The benefit is a more flexible, resilient supply chain.

Central to the success of more complex microfactories are artificial intelligence, machine learning and big data analysis. Microfactories generate vast amounts of data during the various processing steps, which can be analyzed in real-time requiring minimal operational human intervention. Hence, faults and defects can be predicted before they occur, improving overall productivity and product quality.

In addition, lower batch sizes, greater product traceability and a higher level of performance data integration within the supplier network will have a positive impact on product liability and recall risks. On the flip side, new cyber risks will emerge that could endanger critical data as well as proper functioning of equipment and entire facilities unless sufficiently planned for.

This article is an excerpt from the Manufacturing Industry Trends – Casualty Risk Landscape report.