Production Optimization versus Asset Availability – a Review

Nowadays, companies want to give a quick answer in order to face their market competitors. Thesequick responses must be reflected in the quality of the products; to this be possible, it is necessary to manage anumber of factors that will bring benefits in its market positioning. As technology grows, there is the possibility, ata computational level, to create a combination of mathematical and technological tools that were not implementedin the past due to the lack of resources, since they have high robustness about their analytical resolution.This paper presents mathematical and computer tools that have potential great benefits when applied to industrialproblems solving, such as operation management.Along the paper it is made a temporal location of all tools with their main objectives about optimizing industrial processes, focusing on maintenance costs, contributing directly to the rationalization of global costs of theprocesses.Analytical and technological methods that have had great success regarding to the reduction costs of productionin industries are presented. The approaches of this paper bring a literary review of process optimization, namelyabout Neural Networks and multivariate analysis for prediction

[1]  H. Hotelling,et al.  Multivariate Quality Control , 1947 .

[2]  George Henry Dunteman,et al.  Introduction To Multivariate Analysis , 1984 .

[3]  John T. Renwick,et al.  Vibration Analysis---A Proven Technique as a Predictive Maintenance Tool , 1985, IEEE Transactions on Industry Applications.

[4]  Richard P. Lippmann,et al.  An introduction to computing with neural nets , 1987 .

[5]  H. Raghav Rao,et al.  Expert Systems in Production and Operations Management: Classification and Prospects , 1988 .

[6]  W. T. Tucker,et al.  Identification of out of control quality characteristics in a multivariate manufacturing environment , 1991 .

[7]  Charles W. Champ,et al.  A multivariate exponentially weighted moving average control chart , 1992 .

[8]  Douglas C. Montgomery,et al.  Investigation and characterization of a control scheme for multivariate quality control , 1992 .

[9]  Ludo Gelders,et al.  Maintenance management decision making , 1992 .

[10]  Douglas C. Montgomery,et al.  A review of multivariate control charts , 1995 .

[11]  M. S. Sachdev,et al.  Design, implementation and testing of an artificial neural network based fault direction discriminator for protecting transmission lines , 1995 .

[12]  Vallayil N. A. Naikan,et al.  Availability and maintenance cost optimization of a production plant , 1995 .

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

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

[15]  David J. Edwards,et al.  Predictive maintenance techniques and their relevance to construction plant , 1998 .

[16]  Jean-Marie Proth,et al.  Predictive maintenance: The one-unit replacement model , 1998 .

[17]  David J. Sherwin Age‐based opportunity maintenance , 1999 .

[18]  Kenneth K. Boyer,et al.  Strategic consensus in operations strategy , 1999 .

[19]  Soteris A. Kalogirou,et al.  Applications of artificial neural networks in energy systems , 1999 .

[20]  Luca Maria Gambardella,et al.  Ant Algorithms for Discrete Optimization , 1999, Artificial Life.

[21]  Hong-Guang Ni,et al.  Prediction of compressive strength of concrete by neural networks , 2000 .

[22]  Bikash Bhadury,et al.  Opportunistic maintenance of multi‐equipment system: a case study , 2000 .

[23]  Ahc Tsang,et al.  Reliability centred maintenance : a key to maintenance excellence , 2000 .

[24]  Soteris A. Kalogirou,et al.  Applications of artificial neural-networks for energy systems , 2000 .

[25]  R. Schroeder,et al.  Relationships between implementation of TQM, JIT, and TPM and manufacturing performance , 2001 .

[26]  Hongzhou Wang,et al.  A survey of maintenance policies of deteriorating systems , 2002, Eur. J. Oper. Res..

[27]  A. J. Morris,et al.  Statistical performance monitoring of dynamic multivariate processes using state space modelling , 2002 .

[28]  Gerald M. Knapp,et al.  A fuzzy neural network approach to machine condition monitoring , 2003, Comput. Ind. Eng..

[29]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[30]  Vincenzo Crupi,et al.  Neural-Network-Based System for Novel Fault Detection in Rotating Machinery , 2004 .

[31]  L. McLaughlin,et al.  Optimal design of a condition-based maintenance model , 2004, Annual Symposium Reliability and Maintainability, 2004 - RAMS.

[32]  R. Das,et al.  A novel approach for ground fault detection , 2004, 57th Annual Conference for Protective Relay Engineers, 2004.

[33]  A. D. Hope,et al.  Bearing fault diagnosis using multi-layer neural networks , 2004 .

[34]  Benoît Iung,et al.  Predictive maintenance in intelligent-control-maintenance-management system for hydroelectric generating unit , 2004 .

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

[36]  D.J. Evans,et al.  A Real-Time Predictive Maintenance System for Machine Systems - An Alternative to Expensive Motion Sensing Technology , 2005, 2005 Sensors for Industry Conference.

[37]  David J. Evans,et al.  A real-time predictive maintenance system for machine systems , 2004 .

[38]  Balbir S. Dhillon,et al.  Maintainability, Maintenance, and Reliability for Engineers , 2006 .

[39]  Amik Garg,et al.  Maintenance management: literature review and directions , 2006 .

[40]  Aitor Arnaiz,et al.  Intelligent automation systems for predictive maintenance: A case study , 2006 .

[41]  Stephan Biller,et al.  Maintenance opportunity planning system , 2007 .

[42]  W. Rivera,et al.  Wind speed forecasting in the South Coast of Oaxaca, México , 2007 .

[43]  Eric Levrat,et al.  ‘Odds Algorithm’-based Opportunistic Maintenance Task Execution for Preserving Product Conditions , 2007 .

[44]  J. Shahrabi,et al.  A combined multivariate technique and multi criteria decision making to maintenance strategy selection , 2007, 2007 IEEE International Conference on Industrial Engineering and Engineering Management.

[45]  Ling Wang,et al.  An optimum condition‐based replacement and spare provisioning policy based on Markov chains , 2008 .

[46]  Barry Lennox,et al.  Monitoring a complex refining process using multivariate statistics , 2008 .

[47]  Mahmud Güngör,et al.  Generalized Regression Neural Networks and Feed Forward Neural Networks for prediction of scour depth around bridge piers , 2009, Adv. Eng. Softw..

[48]  C. T. Barker,et al.  Optimal non-periodic inspection for a multivariate degradation model , 2009, Reliab. Eng. Syst. Saf..

[49]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[50]  Lina Bertling,et al.  An optimization framework for opportunistic maintenance of offshore wind power system , 2009, 2009 IEEE Bucharest PowerTech.

[51]  Sameh M. Saad,et al.  An integrated cost optimisation maintenance model for industrial equipment , 2009 .

[52]  Xiaojun Zhou,et al.  Opportunistic preventive maintenance scheduling for a multi-unit series system based on dynamic programming , 2009 .

[53]  Fuli Wang,et al.  Predictive maintenance policy based on process data , 2010 .

[54]  S. G. Deshmukh,et al.  A literature review and future perspectives on maintenance optimization , 2011 .

[55]  Wenbin Wang,et al.  A simulation-based multivariate Bayesian control chart for real time condition-based maintenance of complex systems , 2012, Eur. J. Oper. Res..

[56]  Jin-Ting Zhang,et al.  A note on the modified two-way MANOVA tests , 2012 .

[57]  Zhigang Tian,et al.  Opportunistic maintenance for wind farms considering multi-level imperfect maintenance thresholds , 2012 .

[58]  Hans Wortmann,et al.  Condition based maintenance in the context of opportunistic maintenance , 2012 .

[59]  Yat Hung Chiang,et al.  Predicting the maintenance cost of construction equipment: Comparison between general regression neural network and Box–Jenkins time series models , 2014 .

[60]  Ashutosh Tiwari,et al.  State of the art in simulation-based optimisation for maintenance systems , 2015, Comput. Ind. Eng..

[61]  Hong-Bae Jun,et al.  On condition based maintenance policy , 2015, J. Comput. Des. Eng..

[62]  Laura Margarida Santos Gouveia Impacto da Internet of Things no Lean Manufacturing , 2015 .

[63]  Christophe Letot,et al.  An adaptive opportunistic maintenance model based on railway track condition prediction , 2016 .

[64]  Jiangjiang Wang,et al.  Thermodynamic performance analysis and optimization of a solar-assisted combined cooling, heating and power system , 2016 .

[65]  Yisha Xiang,et al.  A review on condition-based maintenance optimization models for stochastically deteriorating system , 2017, Reliab. Eng. Syst. Saf..

[66]  Y. Zhou,et al.  Opportunistic maintenance considering non-homogenous opportunity arrivals and stochastic opportunity durations , 2017, Reliab. Eng. Syst. Saf..

[67]  Gregoris Mentzas,et al.  A Proactive Event-driven Decision Model for Joint Equipment Predictive Maintenance and Spare Parts Inventory Optimization , 2017 .

[68]  Adrian Gill,et al.  Optimisation of the technical object maintenance system taking account of risk analysis results , 2017 .

[69]  Tullio Tolio,et al.  Impact of opportunistic maintenance on manufacturing system performance , 2018 .

[70]  Mohammad Reza Dehghani,et al.  Development of prediction models for repair and maintenance-related accidents at oil refineries using artificial neural network, fuzzy system, genetic algorithm, and ant colony optimization algorithm , 2019, Process Safety and Environmental Protection.

[71]  Chanan S. Syan,et al.  Maintenance applications of multi-criteria optimization: A review , 2019, Reliab. Eng. Syst. Saf..

[72]  Abdul Haq,et al.  Memory‐type multivariate control charts with auxiliary information for process mean , 2018, Qual. Reliab. Eng. Int..

[73]  Jing Chen,et al.  Maintenance, Repair, and Operations Parts Inventory Management in the Era of Industry 4.0 , 2019, IFAC-PapersOnLine.

[74]  Chen Zhang,et al.  Opportunistic maintenance strategy for wind turbines considering weather conditions and spare parts inventory management , 2019, Renewable Energy.

[75]  Yuwang Liu,et al.  Proactive preventive maintenance policy for buffered serial production systems based on energy saving opportunistic windows , 2020 .

[76]  Salih O. Duffuaa,et al.  An integrated model of production scheduling, maintenance and quality for a single machine , 2020, Comput. Ind. Eng..

[77]  José María Ponce-Ortega,et al.  Simultaneous structural and operating optimization of process flowsheets combining process simulators and metaheuristic techniques: The case of solar-grade silicon process , 2020, Comput. Chem. Eng..

[78]  Mitra Fouladirad,et al.  Dynamic opportunistic maintenance planning for multi-component redundant systems with various types of opportunities , 2020, Reliab. Eng. Syst. Saf..