A Statistical Process Monitoring Control for an Integrated Production, Maintenance, and Quality Policy of a Forecasting Production Problem

EasyChair Preprint 10067

Abstract

This paper proposed a new, improved combination of corrective, imperfect, and perfect preventive maintenance strategies for forecasting production and maintenance problems under quality constraints. The relationship between demand, production, and maintenance varies from one period to another. To address this problem, we developed integrated maintenance based on optimal production decisions and a quality inspection policy for a production system that must satisfy a forecasting demand under a given service level and during a finite horizon. The integrated model involves a new switching system between perfect and imperfect maintenance planning based on the statistical process model with an alert (surveillance) signal indicating special assignable causes of variation. We use the sampling intervals (h, sizes n, i times and the control chart limit Kp, as decision levels. Then the correlation between the degradation and Production of the machine. The forecasts in production decisions aimed to improve reliability and reduce the non-conformal items, thereby, minimizing the expected total costs. A simulation-based sequential optimization approach is used to optimize the decision parameters of the control policy.

Keyphrases: Assignable causes, Maintenance, Quality, SPC, production

@booklet{EasyChair:10067,
  author    = {Aminu Sahabi Abubakar and Hajej Zied and Aime C Nyoungue and Ayoub Tighazoui},
  title     = {A Statistical Process Monitoring Control for an Integrated Production, Maintenance, and Quality Policy of a Forecasting Production Problem},
  howpublished = {EasyChair Preprint 10067},
  year      = {EasyChair, 2023}}