HDPS-BPSO Based Predictive Maintenance Scheduling for Backlash Error Compensation in a Machining Center

  • Zhe LiEmail author
  • Yi Wang
  • Kesheng Wang
  • Jingyue Li
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 484)


This paper presents a novel HDPS-BPSO maintenance scheduling strategy for backlash error compensation in a machining center through binary particle swarm optimization (BPSO) and data-driven regression methods. During the experiment, a hierarchical diagnosis and prognosis system (HDPS) was leveraged to predict the potential backlash error first. Then BPSO is applied to provide optimized maintenance strategies through capturing the trade-off between several factors such as maintenance cost, machining accuracy, and defective percentage. The target of proposed predictive maintenance strategy is to minimize the cost of potential failures and relevant maintenance performances. The numerical result in this case demonstrates the benefit of implementing predictive maintenance compared with preventive one.


Maintenance scheduling Binary particle swarm optimization Machining center Backlash error compensation 



This work is supported by the CIRCIT (Circular Economy Integration in the Nordic Industry for Enhanced Sustainability and Competitiveness) project, which is financed by Nordic Green Growth Research and Innovation Programme.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceNorwegian University of Science and TechnologyTrondheimNorway
  2. 2.School of BusinessUniversity of PlymouthPlymouth, EnglandUK
  3. 3.Department of Mechanical and Industrial EngineeringNorwegian University of Science and TechnologyTrondheimNorway

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