The Industrial Use Case

How to make the digitalization useful


The Industrial Use Case is aimed to solve the three overarching problems of digitalization in industrials:

  • No compelling use cases that justify the digitalization hype
  • No experience in developing and applying digital technology
  • Proliferating information about digitalization make it difficult to find the signal in the noise

Unlike the multitude of articles, books and posts about digitalization, we focus on the core, applicable use cases for industrial players.

Use Case Categories:

  • IoT and Big Data: Leveraging sensors to create data that is communicated wireless and analyzed to create use cases. E.g. to increase efficiency of operations, enhance life-time of equipment (predictive and preventive maintenance),  create new business models. Three areas of use cases can be distinguished:
    • Create transparency about the customer (e.g. preferences, purchase patterns, product utilization)
    • New business models / services based on customer data (e.g. preventive maintenance, pay-for-utilization models)
    • Overall improvement of manufacuring efficiency and asset utilization (e.g. condition monitoring, remote control)
  • Digital Engineering & Wearables:
  • Omni-Channel / Apps / Social media: 
  • 3D-Printing:
  • Robotics & Drones: Machines used for task automation. E.g. robots that replace humans in manufacturing set-ups; drones that enable quicker delivery of goods. Two types of robots exist 1) Conventional robots that engage in specialized tasks such as welding, fine assembly, painting, pick-and-place; not safe to work around people. 2) Collaborative robots that do simpler tasks but learn by watching (other people or video footage) and by “doing” (manual guidance of the robot); they can also work alongside humans. Three use case areas can be distinguished:
    • Improved product quality: Both types are more precise and consistent than humans, leading to higher product quality
    • Enhanced operational efficiency: Both types enable automation, leading to faster throughput and less reliance on human labor
    • Increased production flexibility: Collaborative robots can be easily moved and reprogrammed to address bottlenecks, allowing firms to adjust their production facilities smoothly according to customer demands
  • Cyber security:
  • Smart Factory:
  • Artificial Intelligence: Artifical Intelligence (AI) technology seeks to automate human thoughts (e.g. facial recognition, natuaral language processing, visural processing, etc.) through advanced uses of Big data analytics