SCIRP Mobile Website
Paper Submission

Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.


Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
Paper Publishing WeChat
Book Publishing WeChat

Article citations


Emami-Mehrgani, B., Nadeau, S. and Kenné, J.-P. (2014) Optimal Lockout/Tagout, Preventive Maintenance, Human Error and Production Policies of Manufacturing Systems with Passive Redundancy. Journal of Quality in Maintenance Engineering, 20, 453-470.

has been cited by the following article:

  • TITLE: A Mathematical Model: A Flexible Manufacturing System, Prone to Error, Making Two Products Each with Stochastic Demand Schedules

    AUTHORS: Issa Diop, Sylvie Nadeau, Behnam Emami-Mehrgani

    KEYWORDS: Optimal Production Control, Corrective Maintenance, Lockout/Tagout, Human Error

    JOURNAL NAME: American Journal of Industrial and Business Management, Vol.9 No.1, January 16, 2019

    ABSTRACT: Lockout/tagout (LOTO) is practiced in manufacturing facilities to ensure safety during machinery maintenance procedures. In flexible manufacturing systems, human error (HE) is a major source of accidents and process deviations. Special measures are needed to minimize occupational risk and increase operational efficiency. In this article, we study a production planning problem involving a failure-prone production system meeting two types of demand and we discuss the associated decision-making process. The aim is to develop an optimal, robust and flexible control strategy that facilitates the integration of LOTO into corrective maintenance (CM) and ultimately into production. The influence of HE on flexible manufacturing systems (FMS) is viewed in terms of production and maintenance planning. The frequency of machine repair depends largely on HE. The intrinsic costs of shortage, inventory and CM are optimized over an unbounded planning horizon. Analytical formalism is combined with discrete event simulation, as well as design of experiments (DOE) and a genetic algorithm (GAs) to identify the optimal planning of production and CM with mandatory LOTO. An illustration and sensitivity analysis are proposed to express, in quantitative terms, the usefulness and efficiency of the proposed approach.