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RESEARCH PAPER
Framework of machine criticality assessment with criteria interactions
 
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1
Poznan University of Technology, Faculty of Management Engineering, ul. Prof. Rychlewskiego 2, 60-965 Poznan, Poland
 
2
Rzeszow University of Technology, Faculty of Mechanical Engineering and Aeronautics, ul. Powstańców Warszawy 8, 35-959 Rzeszów, Poland
 
3
Adam Mickiewicz University, Faculty of Mathematics and Computer Science, ul. Uniwersytetu Poznańskiego 4, 61-614, Poznan, Poland
 
4
Lublin University of Technology, Mechanical Engineering Faculty, ul. Nadbystrzycka 36, 20-618 Lublin, Poland
 
5
School of Reliability and Systems Engineering, Beihang University (BUAA), No.37 XueYuan RD. Haidian, Beijing 100191, China
 
 
Publication date: 2021-06-30
 
 
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(2):207-220
 
HIGHLIGHTS
  • A review of machines criticality assessment criteria was presented.
  • A novel model of a machine criticality assessment is proposed.
  • The model combines the importance of the machine criticality assessment criteria with interactions between them.
  • The machine criticality assessment model for the aviation industry is presented.
KEYWORDS
ABSTRACT
Criticality is considered as a fundamental category of production planning, maintenance process planning and management. The criticality assessment of machines and devices can be a structured set of activities allowing to identify failures which have the greatest potential impact on the company’s business goals. It can be also used to define maintenance strategies, investment strategies and development plans, assisting the company in prioritizing their allocations of financial resources to those machines and devices that are critical in accordance with the predefined business criteria. In a criticality assessment process many different and interacting criteria have to be taken into consideration, despite the fact that there is a high level of uncertainty related to various parameters. In addition, not all assessment criteria are equally important. Therefore, it is necessary to determine the weight of each criterion taking into account different requirements of machine criticality process stakeholders. That is why a novel model of a machine criticality assessment is proposed in this paper. The model extends the existing methods of assessing machines criticality, taking into account not only the importance of machine criticality assessment criteria, but also possible interactions between them
 
REFERENCES (92)
1.
Antosz K, Ratnayake RMC. Machinery Classification and Prioritization: Empirical Models and AHP Based Approach for Effective Preventive Maintenance. IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) 2016; 1380-1386, https://doi.org/10.1109/IEEM.2....
 
2.
Azadeh A, Ghaderi SF, Ebrahimipour V. An integrated PCA DEA framework for assessment and ranking of manufacturing systems based on equipment performance. Engineering Computations 2007; 24(4): 347-372, https://doi.org/10.1108/026444....
 
3.
Beliakov G, James S, Wu JZ. Value and Interaction Indices. Discrete Fuzzy Measures. Studies in Fuzziness and Soft Computing 2020; 382, https://doi.org/10.1007/978-3-....
 
4.
Bengtsson M. Classification of machine equipment. International Conference on Maintenance Performance Measurement & Management, Luleå 2011.
 
5.
Bevilacqua M, Braglia M. The analytic hierarchy process applied to maintenance strategy selection. Reliability Engineering & System Safety 2000; 70(1): 71-83, https://doi.org/10.1016/S0951-....
 
6.
Bokrantz J, Skoogh A, Berlin C, Wuest T, Stahre J. Smart Maintenance: An Empirically Grounded Conceptualization. International Journal of Production Economics 2020; 223:107534, https:/doi.org/10.1016/j.ijpe.2019.107534.
 
7.
Buck A, Anderson D, Keller J, Wilkin T, Islam M. A Weighted Matrix Visualization for Fuzzy Measures and Integrals. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Piscataway, NJ. 2020, https://doi.org/10.1109/FUZZ48....
 
8.
Chen RQ, Ma SH. Production and Operations Management; Higher Education Press: Beijing, China, 1999; 302-304.
 
9.
Chiou HK, Tzeng GH. Fuzzy multicriteria decision-making approach to analysis and evaluation of green engineering for industry. Environmental Management 2002; 30(6): 816-830, https://doi.org/10.1007/s00267....
 
10.
Choquet G. Theory of capacities. In Annales de l'institut Fourier 1954; 5: 131 - 295, https://doi.org/10.5802/aif.53.
 
11.
Colapinto C, Jayaraman R, Abdelaziz FB, La Torre D. Environmental sustainability and multifaceted development: multi-criteria decision models with applications. Annals of Operations Research 2020; 293: 405-432, https://doi.org/10.1007/s10479....
 
12.
Costantino F, Di Gravio G, Tronci M. Integrating environmental assessment of failure modes in maintenance planning of production systems. Applied Mechanics and Materials 2013; 295: 651-660, https://doi.org/10.4028/www.sc....
 
13.
Daniewski K, Kosicka E, Mazurkiewicz D. Analysis of the correctness of determination of the effectiveness of maintenance service actions. Management and Production Engineering Review 2018; 9 (2): 20-25, https://doi.org/10.24425/11952....
 
14.
Faisall M, Sharawi A. Prioritize Medical Equipment Replacement Using Analytical Hierarchy Process. IOSR Journal of Electrical and Electronics Engineering 2015; 10(3): 55-63.
 
15.
Farinha Torres JM. Asset Maintenance Engineering Methodologies. CRC Press 2018, https://doi.org/10.1201/978131....
 
16.
Fernandez O, Labib AW, Walmsley R, Petty DJ. A decision support maintenance management system: Development and implementation. International Journal of Quality & Reliability Management 2003; 20(8): 965-979, https://doi.org/10.1108/026567....
 
17.
Gass SI, Rapcsák T. Singular value decomposition in AHP. European Journal of Operational Research 2004; 154(3): 573-584, https://doi.org/10.1016/S0377-....
 
18.
Gluhak M. Equipment Reliability Process in Krško NPP. Journal of Energy 2016; 65(2): 32-40.
 
19.
Gopalakrishnan M, Skoogh A. Machine criticality assessment for productivity improvement. Smart maintenance decision support. International Journal of Productivity and Performance Management 2019, 68(5): 858-878, https://doi.org/10.1108/IJPPM-....
 
20.
Gopalakrishnan M, Skoogh A. Machine criticality based maintenance prioritization: identifying productivity improvement potential, International Journal of Productivity and Performance Management 2018A; 67(4): 654-672, https://doi.org/10.1108/IJPPM-....
 
21.
Gopalakrishnan M, Subramaniyan M, Skoogh A. Data-driven machine criticality assessment - maintenance decision support for increased productivity, Production Planning & Control 2020, https://doi.org/10.1080/095372....
 
22.
Grabisch M, Labreuche CA. Decade of Application of the Choquet and Sugeno Integrals in Multicriteria Decision Making. Annals of Operations Research 2010; 175: 247-286, https://doi.org/10.1007/s10479....
 
23.
Grabisch M. The Application of Fuzzy Integrals in Multicriteria Decision Making. European Journal of Operational Research 1996; 89: 445-456, https://doi.org/10.1016/0377-2....
 
24.
Gray DE. Doing Research in the Real World. Sage Publications, London 2004.
 
25.
Guest G, Bunce A, Johnson L. How many interviews are enough? An experiment with data saturation and variability. Field Methods 2006; 18(1): 59-82, https://doi.org/10.1177/152582....
 
26.
Guo L, Gao J, Yang J, Kang J. Criticality evaluation of petrochemical equipment based on fuzzy comprehensive evaluation and a BP neural network. Journal of Loss Prevention in the Process Industries 2009; 22(4): 469-476, https://doi.org/10.1016/j.jlp.....
 
27.
Guo W, Jin J, Hu SJ. Allocation of Maintenance Resources in Mixed Model Assembly Systems. Journal of Manufacturing Systems 2013; 32 (3): 473-479, https://doi.org/10.1016/j.jmsy....
 
28.
Guo YZ, Dong J. The application of fuzzy clustering analysis in process equipment importance classification. International Journal of Pressure Vessels and Piping 1997; 71: 175-179, https://doi.org/10.1016/S0308-....
 
29.
Guofa Li, Yi Li, Zhang X, Hou C, He J, Xu B, Chen J. Development of a Preventive Maintenance Strategy for an Automatic Production Line Based on Group Maintenance Method. Applied Science 2018; 8: 1781, https://doi.org/10.3390/app810....
 
30.
Gürbüz T, Alptekin SE, Alptekin GI. A hybrid MCDM methodology for ERP selection problem with interacting criteria. Decision Support Systems 2012; 54: 206-214, https://doi.org/10.1016/j.dss.....
 
31.
Hijes F, Cartagena J. Maintenance strategy based on a multicriterion classification of equipments. Reliability Engineering & System Safety 2006; 91(4): 444-451, https://doi.org/10.1016/j.ress....
 
32.
Hu YC, Chen H. Choquet Integral-based hierarchical networks for evaluating customer service perceptions on fast food stores. Expert Systems with Applications 2010; 37: 7880-7887, https://doi.org/10.1016/j.eswa....
 
33.
Jaderi F, Saidi E, Anvaripour B, Nabhani N. Criticality analysis for assets priority setting of Abadan Oil Refinery using AHP and Delphi Techniques. International Journal of Engineering and Innovative Technology 2012; 2(6): 48-53.
 
34.
Jagtap HP, Bewoor AK. Use of Analytic Hierarchy Process methodology for criticality Analysis of thermal Power plant equipment. in Materials Today: proceedings 2017; 4: 1927-1936, https://doi.org/10.1016/j.matp....
 
35.
Jasiulewicz-Kaczmarek M, Żywica P. The concept of maintenance sustainability performance assessment by integrating balanced scorecard with non-additive fuzzy integral. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2018; 20(4): 650-661, https://doi.org/10.17531/ein.2....
 
36.
Khanlari A, Mohammadi K, Sohrabi B. Prioritizing equipments for preventive maintenance (PM) activities using fuzzy rules. Computers and Industrial Engineering 2008; 54: 169-184, https://doi.org/10.1016/j.cie.....
 
37.
Kłosowski G, Rymarczyk T, Kania K, Świć A, Cieplak T. Maintenance of industrial reactors supported by deep learning driven ultrasound tomography. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (1): 138-147, https://doi.org/10.17531/ein.2....
 
38.
Konowrocki R, Chojnacki A. Analysis of rail vehicles' operational reliability in the aspect of safety against derailment based on various methods of determining the assessment criterion. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (1): 73-85, http://dx.doi.org/10.17531/ein....
 
39.
Kozłowski E, Borucka A, Świderski A. Application of the logistic regression for determining transition probability matrix of operating states in the transport systems. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22(2): 192-200, https://doi.org/10.17531/ein.2....
 
40.
Kozłowski E, Mazurkiewcz D, Kowalska B, Kowalski D. Application of multidimensional scaling method to identify the factors influencing on reliability of deep wells. In: Burduk A, Chlebus E, Nowakowski T, Tubis A. (eds) Intelligent Systems in Production Engineering and Maintenance. ISPEM 2018. Advances in Intelligent Systems and Computing 2019; 835: 56-65, https://doi.org/10.1007/978-3-....
 
41.
Labib AW. A decision analysis model for maintenance policy selection using a CMMS. Journal of Quality in Maintenance Engineering 2004; 10(3): 191-202, https://doi.org/10.1108/135525....
 
42.
Lewandowski J. Decision making processes in reliability and operation of continuous running technical objects. Technical University of Lodz Press, Lodz 2008.
 
43.
Li G, Li Y, Zhang X, Hou C, He J, Xu B, Chen J. Development of a Preventive Maintenance Strategy for an Automatic Production Line Based on Group Maintenance Method. Applied Sciences 2018,8: 1751, https://doi.org/10.3390/app810....
 
44.
Li L, Ni J. Short - Term Decision Support System for Maintenance Task Prioritization." International Journal of Production Economics 2009; 121 (1): 195-202, https://doi.org/10.1016/j.ijpe....
 
45.
Liu P, Liu J. Some q‐rung orthopai fuzzy Bonferroni mean operators and their application to multi‐attribute group decision making. International Journal of Intelligent Systems 2018; 33(2), 315-347, https://doi.org/10.1002/int.21....
 
46.
Lopes IS, Figueiredo MC, Sá V. Criticality evaluation to support maintenance management of manufacturing systems. International Journal of Industrial Engineering and Management 2020; 11(1): 3 -18, https://doi.org/10.24867/IJIEM....
 
47.
Loska A. Methodology of variant assessment of exploitation policy using numerical taxonomy tools. Management Systems in Production Engineering 2015; 2(18): 98-104, http://dx.doi.org/10.12914/MSP....
 
48.
Lotovskyi E, Teixeira AP, Guedes Soares C. Availability analysis of an offshore oil and gas production system subjected to age-based preventive maintenance by Petri Nets. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (4): 627-637, http://dx.doi.org/10.17531/ein....
 
49.
Ma J, Fan ZP, Huang LH. A subjective and objective integrated approach to determine attribute weights. European Journal of Operational Research 1999; 112(2): 397-404, https://doi.org/10.1016/S0377-....
 
50.
Mahmood K, Shevtshenko E. Analysis of machine production processes by risk assessment approach. Journal of Machine Engineering 2015; 15(1): 112-125.
 
51.
Mane AM, Dongale TD, Bapat MS. Application of Fuzzy Measure and Fuzzy Integral in Students Failure Decision Making. OSR Journal of Mathematics 2014; 10(6): 47-53, https://doi.org/10.9790/5728-1....
 
52.
Marichal JL, Roubens M. Dependence between criteria and multiple criteria decision aid. 2nd International Workshop on Preferences and Decisions, Trento, Italy,TRENTO'98. 1998 (https://core.ac.uk/download/pd...).
 
53.
Márquez AC, Herguedas AS. Learning about failure root causes through maintenance records analysis. Journal of Quality in Maintenance Engineering 2004; 10(4): 254 - 262, https://doi.org/10.1108/135525....
 
54.
Márquez AC, León PM, Fernández JFG, Márquez CP, Campos ML. The maintenance management framework: A practical view to maintenance management. Journal of Quality in Maintenance Engineering 2009; 15(2):167-178, https://doi.org/10.1108/135525....
 
55.
Mohamed MA, Xiao W. Q-measures: an efficient extension of the Sugeno lambda-measure. IEEE Transactions on Fuzzy Systems 2003; 11(3): 419-426, https://doi.org/10.1109/TFUZZ.....
 
56.
Mohebbi A, Achiche S, Baron L. A fuzzy-based framework to support multicriteria design of mechatronic systems. Journal of Computational Design and Engineering 2020; 7(6): 816-829, https://doi.org/10.1093/jcde/q....
 
57.
Moncadatorres A, Leuenberger K, Gonzenbach R, Luft A, Gassert R. Activity classification based on inertial and barometric pressure sensors at different anatomical locations. Physiological Measurement 2014; 35: 1245-1263, https://doi.org/ 10.1088/0967-3334/35/7/1245.
 
58.
Murofushi T, Soneda S. Techniques for reading fuzzy measures (III): interaction index. in: 9th Fuzzy System Symposium 1993: 693-696.
 
59.
Murofushi T. Techniques for reading fuzzy measures (I): The Shapley value with respect to a fuzzy measure. in: 2nd Fuzzy Workshop, Nagaoka, Japan 1992: 39-48.
 
60.
Ni J, Jin X. Decision Support Systems for Effective Maintenance Operations. CIRP Annals - Annals 2012; 61 (1): 411-414, https://doi.org/10.1016/j.cirp....
 
61.
Paszkowski W, Kotus J, Poremski T, Kostek B. Evaluation of sound quality features on environmental noise effects - a case study applied to road traffic noise. Metrology and Measurement Systems 2018; 25 (3): 517-531.
 
62.
Pękala B, Dyczkowski K, Grzegorzewski P, Bentkowska U. Inclusion and similarity measures for interval-valued fuzzy sets based on aggregation and uncertainty assessment. Information Sciences 2020; 547:1182-1200, https://doi.org/10.1016/j.ins.....
 
63.
Pertiwi S, Hermawan W, Prahmawati E. Maintenance Cost Reduction of Paddy Seed Production Machinery by Implementing Preventive Maintenance System.; IOP Conf. Series: Materials Science and Engineering 2019; 557: 012075, https://doi.org/ 10.1088/1757-899X/557/1/012075.
 
64.
Pschierer-Barnfather P, Hughes D, Holmes S. Determination of asset criticality: a practical method for use in Risk-Based investment planning. 21st International Conference on Electricity Distribution Frankfurt, 6-9 June 2011 paper no 1013.
 
65.
Qi HS, Alzaabi RN, Wood AS, Jani M. A fuzzy criticality assessment system of process equipment for optimised maintenance management. International Journal of Computer Integrated Manufacturing 2013; 28(1): 112-125, https://doi.org/10.1080/095119....
 
66.
Ratnayake RMC, Antosz K. Development of a Risk Matrix and Extending the Risk-based Maintenance Analysis with Fuzzy Logic Procedia Engineering 2017b; 182: 2- 610, https://doi.org/10.1016/j.proe....
 
67.
Ratnayake RMC, Antosz K. Risk-Based Maintenance assessment in the manufacturing industry: minimisation of suboptimal prioritisation. Management and Production Engineering Review 2017a; 8(1): 38-45, https://doi.org/10.1515/mper-2....
 
68.
Ratnayake RMC, Stadnicka D, Antosz K. Deriving an empirical model for machinery prioritization: mechanical systems maintenance. IEEE International Conference on Industrial Engineering and Engineering Management 2014; 1442-1447, https://doi.org/10.1109/IEEM.2....
 
69.
Roda I, Macchi M, Fumagalli L, Viveros P. A review of multi-criteria classification of spare parts: From literature analysis to industrial evidences. Journal of Manufacturing Technology Management 2014; 25(4): 528-549, https://doi.org/10.1108/JMTM-0....
 
70.
Roy W. Priority management: new theory for operations management. International Journal of Operations and Production Management 1994; 14(6): 4-24, https://doi.org/10.1108/014435....
 
71.
Sadiq R, Tesfamariam S. Developing environmental indices using fuzzy numbers ordered weighted averaging (FN-OWA) operators. Stochastic Environmental Research & Risk Assessment 2008; 22(1): 494-505, https://doi.org/10.1007/s00477....
 
72.
Saleh N, Sharawi A, Elwahed M, Petti A, Puppato D, Balestra G. Preventive maintenance prioritization index of medical equipment using quality function deployment. IEEE Journal of Biomedical and Health Informatics 2015; 19(3): 1029-1035, https://doi.org/10.1109/JBHI.2....
 
73.
Shahin A, Attarpour MR. Developing Decision Making Grid for Maintenance Policy Making Based on Estimated Range of Overall Equipment Effectiveness. Mathematical Models and Methods in Applied Sciences 2011; 5: 86, https://doi.org/10.5539/mas.v5....
 
74.
Singh RK, Kulkarni M. Criticality analysis of power-plant equipments using the Analytic Hierarchy Process. International Journal of Industrial Engineering & Technology 2013; 3(4): 1-14.
 
75.
Stadnicka D, Antosz K, Ratnayake RMC. Development of an empirical formula for machine classification: Prioritization of maintenance tasks. Safety Science 2014; 63: 34 - 41, https://doi.org/10.1016/j.ssci....
 
76.
Subramanian N, Ramanathan R. A review of applications of Analytic Hierarchy Process in operations management. International Journal of Production Economics 2012; 138(2): 215-241, https://doi.org/10.1016/j.ijpe....
 
77.
Sugeno M, Terano T. A model of learning based on fuzzy information. Kybernetes 1997; 6(2): 157-166, https://doi.org/10.1108/eb0054....
 
78.
Sun L, Dong H, Hussain OK, Hussain FK, Liu AX. A framework of cloud service selection with criteria interactions. Future Generation Computer Systems 2019; 94: 749-764, https://doi.org/10.1016/j.futu....
 
79.
Świderski A, Borucka A, Grzelak M, Gil L. Evaluation of the machinery readiness using semi-Markov processes. Applied Sciences 2020; 10(4), 1541: 1-15. https://doi.org/10.3390/app100....
 
80.
Taghipour S, Banjevic D, Jardine A. Prioritization of medical equipment for maintenance decisions. Journal of the Operational Research Society 2010: 1-22.
 
81.
Terano T, Asai K, Sugeno M. Fuzzy Systems Theory and Its Applications. Academic Press lnc. 1992: 137-145.
 
82.
Teunter RH, Babai MZ, Syntetos AA. ABC classification: Service levels and inventory costs. Production and Operations Management 2010; 19: 343-352, https://doi.org/10.1111/j.1937....
 
83.
Tongco MDC. Purposive sampling as a tool for informant selection. Ethnobotany Research and Applications 2007; 5: 147-158, https://doi.org/10.17348/era.5....
 
84.
Triantaphyllou E, Mann SH. Using the Analytic Hierarchy Process for Decision Making in Engineering Applications: Some Challenges. International Journal of Industrial Engineering: Theory, Applications and Practice 1995; 2(1): 35-44.
 
85.
Velasquez M, Hester PT. An Analysis of Multi-Criteria Decision Making Methods. International Journal of Operational Research 2013; 10(2): 56-66.
 
86.
Wang T, Mousseau V, Pedroni N, Zio E. An empirical classification-based framework for the safety criticality assessment of energy production systems, in presence of in-consistent data. Reliability Engineering and System Safety 2017; 157:139-151, https://doi.org/10.1016/j.ress....
 
87.
Wójtowicz A, Żywica P, Stachowiak A, Dyczkowski K. Solving the problem of incomplete data in medical diagnosis via interval modelling. Applied Soft Computing 2016; 47: 424-437, https://doi.org/10.1016/j.asoc....
 
88.
Yager RR. On ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Transactions on Systems, Man, and Cybernetics 1988; 18(1): 183-190, https://doi.org/10.1109/21.870....
 
89.
Yan S, Ma B, Wang X, Chen J, Zheng C. Maintenance policy for oil-lubricated systems with oil analysis data. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (3): 455-464, http://dx.doi.org/10.17531/ein....
 
90.
Yinghua HYL. Targeted Preventive Maintenance of Pharmaceutical Equipment. Journal of Drug Design and Medicinal Chemistry 2018; 4(2): 10-15, https://doi.org/10.11648/j.jdd....
 
91.
Zadeh LA. Fuzzy sets. Information and Control 1965; 8(3): 338-353, https://doi.org/10.1016/S0019-....
 
92.
Zuber N, Bajrić R. Gearbox faults feature selection and severity classification using machine learning. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (4): 748-756, http://doi.org/10.17531/ein.20....
 
 
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