7 Quick wins for an agile manufacturing future

whitePaper | March 23, 2023

The fourth industrial revolution is transforming the manufacturing industry as we speak. Industry 4.0 is digitally driven, and like all other revolutions, the transformation did not happen overnight. Since the first personal computer on a factory floor in 1970s, computer-aided design has developed and matured exponentially. Strategically eective evolutionary steps has resulted in productivity and eciency gains in manufacturing. We live in the Industry 4.0 era, characterized by the digitization of manufacturing processes. Inevitably, today, information plays a significant role for an enterprise transformation. Data on how the product’s design and manufacturing information is authored, exchanged, and processed is critical to competitiveness. Information ‘silos’ for various life cycle processes are gradually connected to form a digital thread of information, envisioned to integrate and drive modern product design, manufacturing, and product support service processes.

whitePaper | March 8, 2023

Agile Manufacturing is a manufacturing philosophy that emphasizes flexibility, adaptability, and responsiveness in production processes. It is an approach that allows manufacturers to quickly respond to changing market demands and customer needs. The term Agile refers to a set of principles and practices aimed at delivering high-quality products that meet the needs of customers in a fast-changing environment. The term Agile Manufacturing was first coined in the early 1990s, during a time of increasing global competition and rapidly changing market conditions. As a result, manufacturers began to explore new ways to improve their competitiveness and responsiveness to changing customer needs, leading to the development of the Agile Manufacturing strategy. In January 1991, the term appeared in an important report entitled “21st Century Manufacturing Enterprise Strategy” by the Iacocca Institute at Lehigh University in the United States.

whitePaper | March 17, 2022

Manufacturing industry professionals must corral and understand massive amounts of data from many systems to drive operational efficiencies, higher levels of service, supply chain resiliency, and ultimately a complete view of the business. Having the ability to explore the impact of and interplay among changes in production efficiency, product quality, customer demand, and service excellence isn’t possible without visibility into data and meaningful data analytics. This “big data” approach to manufacturing operations and supply chain optimization can deliver big results and is at the heart of the digital transformation initiatives of many industrial companies.

whitePaper | June 12, 2022

Automation has been a driving force behind greater productivity and efficiency in manufacturing companies since the 1980s. In the 2020s, a new generation of applications will enable even more production companies to benefit from the potential of automated processes. Advances in sensor technology and networking enable increasingly complex tasks to be performed reliably and safely by robots. Thanks to high-performance sensor technology, they can automatically react to many changing circumstances. Connected to the Internet of Things (IoT), the robots automatically provide information about progress and incidents. Via a remote connection, the IoT technology can be provided with new instructions, monitored, and remotely operated if necessary.

whitePaper | April 12, 2023

Industrial companies, such as those in manufacturing, energy, mining, agriculture, and transportation, are increasingly looking to fuel digital transformation—from optimizing operations to accelerating design to reinventing supply chains. For these organizations, data has become the connective tissue that holds their complex industrial systems together.

whitePaper | July 25, 2022

Manufacturers are demanding ever-greater precision, accuracy, and reliability from industrial automation. Fortunately, sensors, robot arms, grippers, and the software to connect and guide them have become increasingly capable. In response to the labor and supply chain challenges of the past few years, as well as the demands for personalization and rapid fulfillment, many factories and other facilities are looking to adopt robots or add them to their operations. In this Special Focus Issue, we look at how AI and machine learning are enabling more precise picking, among other applications.