Smart Manufacturing

whitePaper | March 6, 2020

The manufacturing industry is undergoing tremendous change. The industrial revolution brought us assembly lines and mass production. The result was a dramatic increase in worker productivity. The digital revolution brings a host of new opportunities, enabled by data and the power and intelligence of cloud computing. However, it’s the talent, skill, and creativity of your people that determine success.

whitePaper | July 5, 2022

The manufacturing industry is constantly evolving. New technologies such as artificial intelligence and machine learning, data and analytics, advanced robotics, wearables and connected devices, and other innovations are reshaping how manufacturers produce goods, engage with customers, and support employees

whitePaper | July 29, 2023

Your design engineers are masters at coming up with elegant solutions to challenges. But they probably aren’t familiar with the cuttingedge manufacturing technologies, processes, and materials that can transform those solutions into feasible medical components and products that are cost-effective to produce and valued by end-users. That often results in a disconnect between design and manufacturing that can cost you both time and money.

whitePaper | May 26, 2023

Today’s advanced tooling manufacturers want to design and iterate faster, speed up production times, assure yield quality, and improve the durability and performance of their inserts. Achieving all this, and more, is mission critical to the needs of customers in the aerospace, energy, automotive, and other industries for whom the rapid and repeatable production of high-quality cast parts is essential. Until now the limitations of conventional 3D metal printers made it difficult for tooling manufacturers to harness the full potential of additive manufacturing (AM) and advanced tooling manufacturing processes. But no more.

whitePaper | January 3, 2023

In order to achieve digital manufacturing through Industry 4.0, it is critical to aggregate and manage the huge amount of data generated in the factory by Industrial Internet of Things (IIoT) sensors and devices. Having connected machines, workers and systems is just the start of the digital transformation journey. To extract real value from this connectivity, a digital twin of machines and processes have to be modeled in a standardized manner which will help aggregate heterogeneous data and provide valuable insights to drive productivity and efficiency. The interoperability and flexibility of different assets is an important challenge due to the volume and variety of data that needs to be modeled. This paper will go over Industry 4.0 compliant data modeling principles using the MongoDB Smart Factory testbed as an example. We will model the data using MongoDB Atlas in a way that fulfills requirements and needs of Industry 4.0: interoperability, flexibility and scalability.

whitePaper | December 22, 2022

Minimizing downtime and increasing production efficiency is one of the main goals of an effective maintenance strategy. Knowing the working hours, operating parameters, and consumption of one’s assets is the starting point for identifying operating conditions, studying their behavior, finding anomalies, and understanding the reasons for individual downtime. In this way, using different algorithms, it is possible to achieve the ideal strategy