Improving the Experience for Production Staff in Manufacturing Companies

whitePaper | January 20, 2022

The roadmap commitments now indicate the manufacturing industry’s readiness to work towards net zero. There are however conditions required for the manufacturing sector to reach the net zero goal and fully realise the opportunities presented by the net zero ambition. A deeply or fully decarbonised power supply, reliable, in sufficiency and at a reasonable cost is one of these conditions. This includes the development of a hydrogen network that reaches not only industrial clusters but also dispersed manufacturing sites.

whitePaper | July 1, 2020

The auto move manufacturer had incurred significant financial losses and struggled in denying methods in which they could optimize their excising operons and align with corporate Industry 4.0 incaves. They experienced bo@leneck operons that caused unplanned down me and had increasing scrap rates due to a lack of process visibility

whitePaper | October 19, 2022

The 1980s saw the Western World’s academics and manufacturers cast their eyes eastward to the miracle of Japanese manufacturing. Specifically, its low cost, high quality, and low stock. As a result, Japanese products were successfully flooding the Western World’s market and were seen as “World Class”.

whitePaper | August 31, 2022

The business case for collaboration and cross-functional transformation Faced with significant and ongoing disruption in the industry, manufacturing companies have known for years that digital transformation is essential to maintain a competitive edge. COVID-19 has only accelerated the need for digital transformation. The pandemic has disrupted supply chains, created an increasingly distributed and remote workforce, caused significant changes in demand, and increased the challenges of providing field service. To address these changes, manufacturing companies have accelerated their investments in digitization. According to McKinsey, advances in this area are now ahead of schedule by three to four years.1

whitePaper | November 12, 2022

Since the first Industrial Revolution, the manufacturing process has been revolutionised from water and steam-powered machines to electrical and automated ones. The term "Industry 4.0" or simply I4 was introduced by the German government in 2011, which encourages the use of modern technology in the manufacturing process. It defines that automation technology can be improved by offering different methods of self-configuration, self-optimisation and self-diagnosis. The fourth era of revolution (Industry 4.0) is all about connectivity trends, advanced material, processing technology, service orientation and collaboration in advanced manufacturing networks. It presents a unique level of control and coordination over the whole value chain of the products. Internet of things (IoT) and machine to machine communication (M2M) are merged to improve communication and automation. It creates a new set of design principles for effective and computerised control of the manufacturing process which includes

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.