The State of Food Manufacturing

whitePaper | March 29, 2023

Smart factories have various areas of strengths and weaknesses, just as people do. Strengths bring the opportunity for positive differentiation, whilst weaknesses offer challenges to address in order to deliver consistently on expectation. Many people like to measure their IQ to see how they compare in terms of being “Smart”— so why should we not do the same for the data-driven Smart assembly factory? This helps reveal both strengths and weaknesses, builds the roadmap for improvement and development, increases visibility of unique values, and eliminates risk derived from bottlenecks and inefficiencies. It is time to put our Smart, data-driven manufacturing operation to the test, ensuring preparedness as the industry transforms toward the elusive Industry 4.0.

whitePaper | November 2, 2022

This white paper entitled "Artificial Intelligence in Manufacturing" reports the use of Artificial Intelligence (AI) in European manufacturing, and its potential to enhance competitiveness and technological leadership in the future. The paper is based on research conducted by the Artificial Intelligence in Manufacturing NETwork (AIM-NET), which represents the viewpoint of the manufacturing community on the achievements and challenges of AI solutions. The document covers topics such as AI in manufacturing processes, robots, machines, and operations support in manufacturing, and AI in manufacturing systems. It also includes discussions on cross-cutting aspects such as regulation, education, systems engineering, and data augmentation. The paper also presents the maturity achieved TRL levels of existing AI-based applications in manufacturing, typical KPIs used to assess performance, and barriers and limitations to wide adoption. It also provides a roadmap for future work on AI, with efforts needed in short-term and long-term time horizons. Overall, the paper provides a comprehensive overview of the current status and future vision of AI in manufacturing for policy makers, practitioners, and researchers.

whitePaper | February 24, 2020

This white paper is part of AMT’s resource library on transformative technologies. There is enormous opportunity for learning, collaboration, and investment between the manufacturing and technology communities to accelerate innovative solutions and product development in the coming decade. Industry leaders agree that every part of the manufacturing value chain will be transformed by technology-R&D, the supply chain, factory operations, sales, and service. Digital connectivity among designers, managers, workers, customers, and physical industrial assets will unlock enormous value and change the manufacturing landscape.

whitePaper | May 19, 2022

Manufacturers, suppliers, and logistics companies are finding themselves at an interesting intersection today. Digital transformation, forcefully propelled atop any executive agendas by COVID-19, is no longer a trend or a hype. With more pressure from stakeholders, customers, and competitors, companies need to act fast and decidedly to kickstart their smart factory roadmap.

whitePaper | December 1, 2022

Printed circuit assemblers need an IoT ecosystem, the cornerstone of Industry 4.0. One of the key advantages of an IoT ecosystem is that it can take siloed information, analyze it, and optimize processes across a company’s systems. Aligning IT and OT is key to the Industry 4.0 transformation and to improving manufacturing processes and leads to higher production performance and lower costs. However, it requires effective governance and tools to adapt IT project management models for use in operations.

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.