Strategic maintenance technique selection using combined quality function deployment, the analytic hierarchy process and the benefit of doubt approach

The business performance of manufacturing organizations depends on the reliability and productivity of equipment, machineries and entire manufacturing system. Therefore, the main role of maintenance and production managers is to keep manufacturing system always up by adopting most appropriate maintenance methods. There are alternative maintenance techniques for each machine, the selection of which depend on multiple factors. The contemporary approaches to maintenance technique selection emphasize on operational needs and economic factors only. As the reliability of production systems is the strategic intent of manufacturing organizations, maintenance technique selection must consider strategic factors of the concerned organization along with operational and economic criteria. The main aim of this research is to develop a method for selecting the most appropriate maintenance technique for manufacturing industry with the consideration of strategic, planning and operational criteria through involvement of relevant stakeholders. The proposed method combines quality function deployment (QFD), the analytic hierarchy process (AHP) and the benefit of doubt (BoD) approach. QFD links strategic intents of the organizations with the planning and operational needs, the AHP helps in prioritizing the criteria for selection and ranking the alternative maintenance techniques, and the BoD approach facilitates analysing robustness of the method through sensitivity analysis through setting the realistic limits for decision making. The proposed method has been applied to maintenance technique selection problems of three productive systems of a gear manufacturing organization in India to demonstrate its effectiveness.

[1]  Thomas L. Saaty,et al.  DECISION MAKING WITH THE ANALYTIC HIERARCHY PROCESS , 2008 .

[2]  Mahdi Bashiri,et al.  Selecting optimum maintenance strategy by fuzzy interactive linear assignment method , 2011 .

[3]  Prasanta Kumar Dey,et al.  Decision support system for inspection and maintenance: a case study of oil pipelines , 2004, IEEE Transactions on Engineering Management.

[4]  Francesco Vidoli,et al.  Robust weighted composite indicators by means of frontier methods: an application to European infrastructure endowment , 2012 .

[5]  S. K. Mukherjee,et al.  Integrating AHP with QFD for robot selection under requirement perspective , 2005 .

[6]  Jun Wu,et al.  Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process , 2007 .

[7]  Miguel Ángel Sanz Bobi,et al.  SIMAP: Intelligent System for Predictive Maintenance: Application to the health condition monitoring of a windturbine gearbox , 2006 .

[8]  Matthieu van der Heijden,et al.  On the availability of a k-out-of-N system given limited spares and repair capacity under a condition based maintenance strategy , 2004, Reliab. Eng. Syst. Saf..

[9]  N. S. Arunraj,et al.  Risk-based maintenance policy selection using AHP and goal programming. , 2010 .

[10]  Ludo Gelders,et al.  Development of maintenance function performance measurement framework and indicators , 2011 .

[11]  Albert H. C. Tsang.  Strategic dimensions of maintenance management , 2002 .

[12]  María Carmen Carnero.  Selection of diagnostic techniques and instrumentation in a predictive maintenance program. A case study , 2005 .

[13]  Gunner Chr. Larsen,et al.  Fundamentals for remote structural health monitoring of wind turbine blades - a preproject , 2002 .

[14]  S.D.J. McArthur,et al.  A Multi-Agent Fault Detection System for Wind Turbine Defect Recognition and Diagnosis , 2007, 2007 IEEE Lausanne Power Tech.

[15]  B. C. Nakra,et al.  Defect detection in rolling element bearings by acoustic emission method , 1990 .

[16]  Aditya Parida,et al.  Development of a multi‐criteria hierarchical framework for maintenance performance measurement (MPM) , 2007 .

[17]  James R. Evans,et al.  The management and control of quality , 1989 .

[18]  Kanet Katchasuwanmanee,et al.  CURVE is the Institutional Repository for Coventry University Development of the Energy-smart Production Management system ( e-ProMan ) : A Big Data driven approach , analysis and optimization , 2016 .

[19]  Peter W. Tse,et al.  Wavelet Analysis and Envelope Detection For Rolling Element Bearing Fault Diagnosis—Their Effectiveness and Flexibilities , 2001 .

[20]  Qiao Sun,et al.  SINGULARITY ANALYSIS USING CONTINUOUS WAVELET TRANSFORM FOR BEARING FAULT DIAGNOSIS , 2002 .

[21]  Prasanta Kumar Dey,et al.  Strategic supplier performance evaluation: a case-based action research of a UK manufacturing organisation , 2015 .

[22]  Sadhan Kumar Ghosh,et al.  Model for a Predictive Maintenance System Effectiveness Using the Analytical Hierarchy Process as Analytical Tool , 2015 .

[23]  Cc Tan.  Application of Acoustic Emission to the Detection of Bearing Failures , 1990 .

[24]  Susan Carlson Skalak.  House of Quality , 2002 .

[25]  Adolfo Crespo Márquez,et al.  Contemporary maintenance management: process, framework and supporting pillars , 2006 .

[26]  J. Hauser,et al.  The House of Quality , 1988 .

[27]  B. C. Nakra,et al.  Comparison of vibration and acoustic measurement techniques for the condition monitoring of rolling element bearings , 1992 .

[28]  Zahir Irani,et al.  A framework for managing maintenance using performance measurement systems , 2001 .

[29]  P.-T. Chuang,et al.  Combining the Analytic Hierarchy Process and Quality Function Deployment for a Location Decision from a Requirement Perspective , 2001 .

[30]  Peter Kipruto Chemweno,et al.  Development of a risk assessment selection methodology for asset maintenance decision making: An analytic network process (ANP) approach , 2015 .

[31]  N. P. Mukherjee,et al.  Rapid hard tooling process selection using QFD‐AHP methodology , 2006 .

[32]  Selim Zaim,et al.  Maintenance strategy selection using AHP and ANP algorithms: a case study , 2012 .

[33]  Albert H. C. Tsang,et al.  A strategic approach to managing maintenance performance , 1998 .

[34]  Andrej Atrens,et al.  Strategic maintenance management , 2002 .

[35]  S. Leske,et al.  Managing Gearbox Failure , 2006 .

[36]  Ali Emrouznejad,et al.  Strategic logistics outsourcing: An integrated QFD and fuzzy AHP approach , 2012, Expert Syst. Appl..

[37]  Maurizio Bevilacqua,et al.  A combined goal programming - AHP approach to maintenance selection problem , 2006, Reliab. Eng. Syst. Saf..

[38]  S. Luce,et al.  Choice criteria in conditional preventive maintenance , 1999 .

[39]  Jianfeng Li,et al.  An evaluation of maintenance strategy using risk based inspection , 2011 .

[40]  Emmanuel Thanassoulis,et al.  The use of data envelopment analysis in the regulation of UK water utilities: Water distribution , 2000, Eur. J. Oper. Res..

[41]  Sung-Hoon Ahn,et al.  Condition monitoring and fault detection of wind turbines and related algorithms: A review , 2009 .

[42]  D. E. Butler,et al.  The Shock-pulse method for the detection of damaged rolling bearings , 1973 .

[43]  Ming-Lu Wu,et al.  Quality function deployment: A literature review , 2002, Eur. J. Oper. Res..

[44]  H. Müller,et al.  Grid Compatibility of Variable Speed Wind Turbines with Directly Coupled Synchronous Generator and Hydro-Dynamically Controlled Gearbox , 2006 .

[45]  Qian Wang,et al.  Priority setting in maintenance management: a modified multi-attribute approach using analytic hierarchy process , 1998 .

[46]  Liliane Pintelon,et al.  Development of a maintenance performance measurement framework—using the analytic network process (ANP) for maintenance performance indicator selection , 2014 .