A multi-stage remanufacturing approach for life extension of safety critical systems

Life extension of safety critical systems is gaining popularity in many industries due to the increasing demand in world's energy consumption and the strong desire to reduce carbon emissions by different countries. Identification and implementation of a suitable life extension strategy enables safety critical systems to perform their intended functions under stated condition for an extended period of time beyond original design life. In the past, the viability analysis of life extension strategies has been undertaken based on the accumulated knowledge and experience of Original Equipment Manufacturer (OEM), maintenance engineers and inspectors. These approaches involving expert judgement are qualitative in nature and based on conservative assumptions, which may lead to inaccurate conclusion or misleading recommendations to asset managers. Therefore, it is crucial to develop an approach consisting of methods to determine the technical condition of components, estimate the cost of life extension interventions and to analyze carbon footprints. “Remanufacturing” is considered as a suitable end-of-life strategy that can help reduce the overall environmental burden from the product by processing waste materials while at the same time keeping reliability high. Due to the advantages of remanufacturing, it is widely applied for life extension purposes in safety critical industries such as offshore oil and gas, nuclear power, petrochemical, renewable energy, rail transport, aviation, shipping, and electricity distribution and transmission. In this paper, a multi-stage approach is presented to analyze the impact of remanufacturing of safety critical systems on the performance of industrial operations in terms of total cost and carbon footprint. In this approach, the equipment health status is determined by modelling the degradation of the system and then the maintenance costs and carbon footprint are calculated. For the purpose of clarity, the proposed model is applied to an air compressor system and the results are discussed.

[1]  Mahmood Shafiee,et al.  Maintenance strategy selection problem: an MCDM overview , 2015 .

[2]  Mahmood Shafiee,et al.  Warranty and sustainable improvement of used products through remanufacturing , 2009 .

[3]  Mohammed Dahane,et al.  Impact of spare parts remanufacturing on the operation and maintenance performance of offshore wind turbines: a multi-agent approach , 2017, J. Intell. Manuf..

[4]  Vahit Kaplanoglu,et al.  Multi-agent based approach for single machine scheduling with sequence-dependent setup times and machine maintenance , 2014, Appl. Soft Comput..

[5]  S. Tsang Mang Kin,et al.  Remanufacturing Process Planning , 2014 .

[6]  Manoj Kumar Tiwari,et al.  Production planning optimization for manufacturing and remanufacturing system in stochastic environment , 2013, J. Intell. Manuf..

[7]  G. Keoleian,et al.  The Value of Remanufactured Engines: Life‐Cycle Environmental and Economic Perspectives , 2004 .

[8]  Surendra M. Gupta,et al.  Remanufacturing Modeling and Analysis , 2012 .

[9]  Sabrina Bouzidi-Hassini,et al.  Multi-agent based joint production and maintenance scheduling considering human resources , 2013, 2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO).

[10]  Wahidul K. Biswas,et al.  A life cycle greenhouse gas assessment of remanufactured refrigeration and air conditioning compressors , 2011 .

[11]  H. Brandt,et al.  Life Extension of Offshore Assets - Balancing Safety & Project Economics , 2013 .

[12]  Salvatore Venticinque,et al.  A Multi-agent and Dynamic Programming Algorithm for Aeronautical Maintenance Planning , 2013, 2013 Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing.

[13]  M. Pipattanasomporn,et al.  Multi-agent systems in a distributed smart grid: Design and implementation , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[14]  Maxim Finkelstein,et al.  Optimal burn-in and preventive maintenance warranty strategies with time-dependent maintenance costs , 2013 .

[15]  Mahmood Shafiee,et al.  Development of a techno-economic framework for life extension decision making of safety critical installations , 2016 .

[16]  I. Karimi,et al.  Agent-based supply chain management—1: framework , 2002 .

[17]  Khalid Kouiss,et al.  Using multi-agent architecture in FMS for dynamic scheduling , 1997, J. Intell. Manuf..

[18]  Xue Zhong Wang,et al.  A multi-agent system for chemical supply chain simulation and management support , 2002, OR Spectr..

[19]  Liang Gao,et al.  An effective hybrid particle swarm optimization algorithm for multi-objective flexible job-shop scheduling problem , 2009, Comput. Ind. Eng..

[20]  Amaresh Chakrabarti,et al.  Sustainability through remanufacturing in India: a case study on mobile handsets , 2011 .

[21]  Xiao Wang,et al.  Multi-agent reinforcement learning based maintenance policy for a resource constrained flow line system , 2016, J. Intell. Manuf..

[22]  Andrew Y. C. Nee,et al.  Design for Disassembly for Remanufacturing: Methodology and Technology , 2014 .

[23]  C. A. McMahon,et al.  Development of design for remanufacturing guidelines to support sustainable manufacturing , 2006 .

[24]  Jiucheng Xu,et al.  Towards a distributed multi-agent framework for shared resources scheduling , 2014, J. Intell. Manuf..