Dynamic optimization of process quality control and maintenance planning

Amit Kumar Jain, Bhupesh Kumar Lad

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


In this paper, we propose a novel methodology for dynamic optimization of process quality control and maintenance planning while considering the real-Time health state of the system. First, by investigating the relationship between product quality and tool degradation, a new tool condition monitoring (TCM) system for instantaneous diagnostic and prognostic is proposed. Subsequently, the existing process quality control policy is enhanced to become dynamic and extended to deal with machine deterioration with time. This is done via the proposed residual-life based evaluation and multistate magnitude of process shift schemes. Furthermore, the maintenance planning model is modified to capture real-Time remaining life information. These models are integrated and built in conjunction with developed TCM system. As a result, the designed dynamic integrated model can evolve itself to re-evaluate the optimal values for the design parameters used in the entire lifecycle of the manufacturing process. Finally, an experimental case study is implemented to demonstrate the practical feasibility of the developedmethodology.An extensive performance investigation revealed substantial economic benefits over conventional independent approach. This is further complimented with systematic sensitivity analysis. Moreover, we attempt to present potential implications and guidelines for various industrial scenarios to expand the model's robustness and relevance in industrial environment.
Original languageEnglish
Pages (from-to)502-517
Number of pages16
JournalIEEE Transactions on Reliability
Issue number2
Early online date25 Apr 2017
Publication statusPublished - Jun 2017


  • diagnostic
  • maintenance planning
  • process quality control
  • prognostic
  • tool condition monitoring (TCM)


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