Maintenance cost optimization in condition based maintenance: a case study for critical facilities

The increasing availability required to industrial plants and the limited budget often existing to assure it, require a careful formulation of maintenance optimization models. This need is primary for process plants, for which minimization of stops and maximization of their availability, are essential for ensuring targeted production and, therefore, profitability. In this context, the choice of the maintenance strategy is hence fundamental, depending on the system features and then on the effectiveness of the strategy. To evaluate the maintenance activities expected costs, it is necessary to implement appropriate technical and economic models, in order to represent the different types of maintenance types adopted. The aim of this study is to evaluate the technical and economic feasibility of condition based maintenance techniques for a service facility of a process plants. For this aim, the study was done for a HVAC system of a pharmaceutical laboratory. Three different kinds of maintenance strategies (corrective, time based and condition based) were considered, referring to three important equipment of the laboratory. For each system, the evaluation of the average cost of each maintenance strategy was done, so as to identify the most affordable one. Finally, we considered the cost-effectiveness of the implementation of a reliability continuous monitoring system, through the installation of an up-todate supervision structure. The paper offers an example of an economic model for the maintenance of a HVAC service system, presenting an original evaluation of continuous monitoring economics. Moreover, in this study, the newest monitoring technologies were considered, up to date and improved from the latest studies. This paper is directed to facility service and process plant managers. Keyword-CBM, HVAC system, maintenance optimization models.

[1]  William P. Pierskalla,et al.  A survey of maintenance models: The control and surveillance of deteriorating systems , 1976 .

[2]  Mario Tucci,et al.  Conception of a prototype to validate a maintenance expert system , 2013 .

[3]  Rommert Dekker,et al.  Applications of maintenance optimization models : a review and analysis , 1996 .

[5]  Felix T.S. Chan,et al.  Maintenance policy selection in manufacturing firms using the fuzzy MCDM approach , 2012 .

[6]  Jos van Iwaarden,et al.  The effects of increasing product variety and shortening product life cycles on the use of quality management systems , 2012 .

[7]  Daming Lin,et al.  A review on machinery diagnostics and prognostics implementing condition-based maintenance , 2006 .

[8]  Richard M. Feldman,et al.  A survey of preventive maintenance models for stochastically deteriorating single-unit systems , 1989 .

[9]  Antonella Petrillo,et al.  Multi-criteria risk analysis to improve safety in manufacturing systems , 2012 .

[10]  O Borgia,et al.  Risk-based inspections enhanced with Bayesian networks , 2011 .

[11]  Marvin Rausand,et al.  The basic concepts of failure analysis , 1996 .

[12]  S. T. Taylor,et al.  HVAC systems and equipment , 1990 .

[13]  F. D. Carlo,et al.  Service demand forecasting through the systemability model: a case study , 2013 .

[14]  F. D. Carlo,et al.  Imperfect maintenance modelling by dynamic object oriented Bayesian networks , 2013 .

[15]  Mario Tucci,et al.  Accelerated degradation tests for reliability estimation of a new product: A case study for washing machines , 2014 .

[16]  Byron A. Ellis,et al.  Condition Based Maintenance , 2008 .

[17]  Per Hokstad,et al.  An overall model for maintenance optimization , 1996 .

[18]  Mahmut Parlar,et al.  A survey of maintenance models for multi-unit systems , 1991 .

[19]  B. M. Worrall,et al.  Application of dynamic scheduling rules in maintenance planning and scheduling , 1980 .

[20]  Anthony M. Smith,et al.  Reliability-Centered Maintenance , 1992 .

[21]  A structured approach to the selection of condition based maintenance , 1997 .