#SPAICER — The Vision

AI-based Resilience Management in Production Engineering

The Vision, Image: © WZL | Daniel Trauth & Semjon Becker

What is the purpose of this?

The Vision

Timeline and Background

#SPAICER: Scalable adaptive production systems through AI-based resilience optimization

Resilience in a nutshell

The #SPAICER concept idea

SPAICER’s promise of benefits for production companies

Vision of a Smart Resilience Management Ecosystem, Image: © DFKI | Wolfgang Maaß

Manage disturbances and changes

  • Disturbances in production companies concern the supply of material of insufficient quality, leakage of lubricant lines, damage to machines (extension of predictive maintenance), power failure or illness of employees [7. Furthermore, Disturbance scan can be predictable or not predictable [8].
  • Changes usually affect companies from outside, such as systematic market changes in the form of innovative technologies (e.g. shared production lines or 3D printing), changes in demand behavior or abrupt changes in the political or financial system [9,10]. In addition, changes can lie in products themselves, such as their quality, branding, and manufacturing (in-)efficiency. Moreover, there are changes in political regulation, the labor market and the environment itself [11].

Bridging Psychology and Production Engineering

  • predict disturbances and changes in extremely heterogeneous, distributed and permanently changing machines and technology environments close to real time,
  • identify optimized options for action and
  • propagate resilience-optimizing information in the production network.

What #SPAICER does

  • (1) large performance differences between edge devices and cloud servers,
  • (2) edge devices are mostly heterogeneous (e. g. from ARM CPUs to GPUs), which complicates application development,
  • (3) hardware and software update cycles of edge devices are slower in the context of production than in data centers,
  • (4) reduction of the growth of storage capacities with simultaneous growth of generated data, data storage is generally cost inefficient [13].

The #SPAICER Use Case

Finblanking press Feintool XFT 2500 speed. Image: © WZL | Winandy



Get in contact




Footer, Image: © WZL | Daniel Trauth & Semjon Becker



The vision of the #SPAICER research project is to develop a framework model for AI-based resilience management for production companies in production networks.

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Daniel Trauth

danieltrauth.com works in digital transformation (senseering), tokenization of CO2 emissions (BlackFourier), & stands up for human rights (BraveBrew).