IEEE Access (Jan 2024)

An Altruistic-Based Framework to Support Collaborative Healing of Manufacturing Resources in a Self-Organized Shop-Floor

  • Luis A. Estrada-Jimenez,
  • Sepideh Kalateh,
  • Sanaz Nikghadam-Hojjati,
  • Jose Barata

DOI
https://doi.org/10.1109/ACCESS.2024.3349508
Journal volume & issue
Vol. 12
pp. 4282 – 4300

Abstract

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In manufacturing, biologicalisation defines the analysis of biological patterns as a source of inspiration to model intelligent manufacturing systems. This analysis is highly desirable as an answer to the increasing complexity of modeling current engineering solutions which are required to be self-organized, cooperative, and autonomous. Building on this line of research, our paper introduces a framework inspired by the notion of “reciprocal altruism” observed in species like vampire bats. The goal of this framework is twofold; first, to showcase the bio-inspired methodological guidelines of altruism in a manufacturing context. Second, to foster cooperative behaviors among its constitutive resources. The core idea revolves around the assignment of two roles: altruistic/donors and recipients. In this context, altruistic/donors are individuals willing to share their resources or capabilities with those in need, even at the potential cost of their own fitness. We believe that this concept has versatile applications in various manufacturing scenarios, ranging from peer-to-peer energy sharing among mobile robots to load sharing and even tool sharing. In our work, we instantiate the control logic, functionalities, and proof of concept of this altruistic approach, focusing on tool-sharing as an illustrative application. Our preliminary results demonstrate an improvement when comparing the altruistic approach with a manual one. This improvement is particularly evident when considering potential production downtime and production rate fluctuations caused by tool defects. These findings underscore the tangible benefits that bio-inspired solutions can offer in addressing the ongoing challenges of smart manufacturing, especially in terms of engineering design.

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