·        3D Printing: Fast Radius, a Chicago-based manufacturer, uses a platform to collect data and findings from every part design that is stored and manufactured in the Fast Radius virtual warehouse. The data helps teams to identify applications suitable for 3D printing and evaluate engineering and economic challenges of producing a component by using 3D printing. The company also created a virtual parts warehouse consisting of 3,000 items for a heavy equipment manufacturer.  This eliminated the high costs of storing rarely ordered heavy parts.  

·        Decision Support System (DSS) for Luxury Products: Bottega Veneta, an Italian luxury goods house, improved the supply chain by using a uniform data model, used by all the actors involved in the production process to collect and represent the large amount of data involved in the production process. A DSS (Decision Support System) allows the production planner to focus on different scenarios to take better decisions.

·        Volkswagen Cloud: Volkswagen is creating a “Volkswagen Automotive Cloud” that offers features such as smart home connectivity, a personal digital assistant, predictive maintenance service, and media streaming. Volkswagen aims to add over 5 million Volkswagen brand offerings per year with  the help of this cloud service. This cloud is an effective approach for managing and transmitting large amounts of data to their vehicles.  The cloud   storage space enables automotive companies like Volkswagen to use extensive data analytics algorithms to convert data to knowledge and business intelligence.   

·        Automated Mobile Robots (AMRs): A DHL distribution center in the Netherlands is using Automated Mobile Robots (AMRs) to perform pick and place operations. These AMRs autonomously move across the facility alongside the workers, automatically learning and sharing the most efficient travel routes. Using these self-driving robots can help reduce order cycle time by up to 50% and provide up to twice the picking productivity gain, according to DHL.

·        Augmented Reality (AR): AR glasses are just beginning to find commercial applications. General Electric is piloting the use of AR glasses. Before using these smart glasses, jet engine makers often had to stop what they were doing in order to check their manuals and ensure tasks were being performed correctly. This is an error prone process. However, with AR glasses, they can now receive digitized instructions in their field of view. The mechanics can also access training videos or use voice commands to contact experts for immediate assistance. During the pilot, GE reported 11% improvement in previously. Similar applications of AR glasses in surgery and other delicate procedures are under investigation.  

·        Sensors: Sensors help manufacturers to optimize their operations quickly and efficiently by knowing what needs attention. There are many examples. Here is one. By using the data from sensors in its equipment, an African gold mine identified a problem with the oxygen levels that they did not know about. Once fixed, they were able to increase their yield by 3.7%, which saved them $20 million annually.

 

Suggested References:

·        “Industry 4.0: 7 Real-World Examples of Digital Manufacturing in Action”, March 28, 2019. URL:    https://amfg.ai/2019/03/28/industry-4-0-7-real-world-examples-of-digital-manufacturing-in-action/

·        Griecoa, A,., “An Industry 4.0 Case Study in Fashion Manufacturing”, https://doi.org/10.1016/j.promfg.2017.07.190

·        Marr, B., “What is Industry 4.0?”, Sep 2, 2018. URL: https://www.forbes.com/sites/bernardmarr/2018/09/02/what-is-industry-4-0-heres-a-super-easy-explanation-for-anyone/?sh=760593539788

·        Zangiacomi, A. “Moving towards digitalization: a multiple case study in manufacturing”, 04 Dec 2019, URL: https://www.tandfonline.com/doi/abs/10.1080/09537287.2019.1631468