Abstract
With the increase of personalized customization and collaborative production requirements, more and more manufacturing enterprises virtualize and publish their resources and capabilities as cloud services for sharing. However, due to the lack of a general modelling method in the sharing process, data cannot be interpenetrated among different life cycle stages. Also, models built in a lifecycle stage cannot be transformed and propagated to other stages. To alleviate these drawbacks, in this paper, a novel service model transformation method based on product lifecycle is designed and developed to model and transform manufacturing services among different life cycle stages efficiently and accurately. Specifically, based on the discussion of the business model of life cycle service in cloud manufacturing environment, a novel service model transformation method which includes general and view service transformation is proposed and elaborated. Then, the life cycle service model is established mathematically, and eight transformation operators are summarized and their mathematical definitions are given in detail. Meanwhile, the transformation logic process and change propagation are studied. The proposed method is superior to previous methods in that: 1) the model established in this paper is a generic model which can run through different life cycle stages, including both general and personalized data; 2) the eight operator definitions cover most of the operation types in the model transformation process, which greatly improves the operability of the model automatic transformation; 3) the establishment of change propagation mechanism ensures the accuracy of model synchronization when data changes. The successful application in an instrument enterprise demonstrates the rationality and effectiveness of the proposed methodology.
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References
Zhang L, Luo YL, Tao F, Li BH, Ren L, Zhang XS, Hua G, Cheng Y, Hu AR, Liu YK (2014) Cloud manufacturing: a new manufacturing paradigm. Enter Inf Syst-UK 8(2):167–186
Borangiu T, Trentesaux D, Thomas A, Leitão P, Barata J (2019) Digital transformation of manufacturing through cloud services and resource virtualization. Comput Ind 108:150–162
Li JR, Tao F, Cheng Y, Zhao LJ (2015) Big Data in product lifecycle management. Int J Adv Manuf Technol 81:667–684
Vezzetti E, Violante MG, Marcolin F (2014) A benchmarking framework for product lifecycle management (PLM) maturity models. Int J Adv Manuf Technol 71:899–918
Hedberg T, Feeney AB, Helu M, Camelio JA (2017) Toward a lifecycle information framework and technology in manufacturing. J Comput Inf Sci Eng 17:021010
Shin JH, Kiritsis D, Xirouchakis P (2015) Design modification supporting method based on product usage data in closed-loop PLM. Int J Comput Integ M 28(6):551–568
Moghaddam M, Nof SY (2018) Collaborative service-component integration in cloud manufacturing. Int J Prod Res 56(1–2):677–691
Luo Y, Zhang L, Tao F et al (2013) A modelling and description method of multidimensional information for manufacturing capability in cloud manufacturing system. Int J Adv Manuf Technol 69(5–8):961–975
Liu N, Li X (2012) A resource virtualization mechanism for cloud manufacturing systems. International IFIP Working Conference on Enterprise Interoperability, Springer, Berlin Heidelberg 122:46–59
Liu N, Li XP, Shen WM (2014) Multi-granularity resource virtualization and sharing strategies in cloud manufacturing. J Netw Comput Appl 46:72–82
Xu W, Yu J, Zhou Z et al (2015) Dynamic modelling of manufacturing equipment capability using condition information in cloud manufacturing. J Manuf Sci E-T ASME 137(4):040907
Li ZH, Nie FP, Chang XJ et al (2018) Rank-Constrained spectral clustering with flexible embedding. IEEE Transactions on neural networks and learning systems 29(12):6073–6082
Li ZH, Nie FP, Chang XJ et al (2018) Dynamic affinity graph construction for spectral clustering using multiple features. IEEE Transactions on neural networks and learning systems 29(12):6323–6332
Talhi A, Fortineau V, Huet JC et al (2019) Ontology for cloud manufacturing based product lifecycle management. J Intell Manuf 30:2171–2192
Zhao YY, Liu Q, Xu WJ, Wu XX et al (2017) Dynamic and unified modelling of sustainable manufacturing capability for industrial robots in cloud manufacturing. Int J Adv Manuf Technol 93(5–8):2753–2771
Guo H, Shu M (2018) Research on the cloud service description model for cloud service composition in cloud manufacturing system. J Phys Conf Ser 052015:1–7
Yu CY, Mou SD, Ji YJ et al (2018) a delayed product differentiation model for cloud manufacturing. Comput Ind Eng 117:60–70
Duan YY, Han K (2017) Self-organization evolution model of cloud manufacturing service collaborative network. AMME 2017:210–213
Namchul D (2017) Integration of design and manufacturing data to support personal manufacturing based on 3D printing services. Int J Adv Manuf Technol 90:3761–3773
Camba JD, Contero M, Company P, Pérez D (2017) On the integration of model-based feature information in product lifecycle management systems. Int J Inform Manage 37(6):611–621
Liu XL, Wang WM, Guo HY, Barenji AV, Li Z, Huang GQ (2019) Industrial blockchain based framework for product lifecycle management in industry 4.0. Robot Comput Integr Manuf 63(1):1–16
Myrodia A, Randrup T, Hvam L (2019) Configuration lifecycle management maturity model. Comput Ind 106:30–47
Lam HY, Tsang YP, Wu CH, Tang Valerie (2020) Data analytics and the P2P cloud: an integrated model for strategy formulation based on customer behavior. Peer Peer Netw Appl (4)
Ali MM , Doumbouya MB , Louge T et al (2020) Ontology-based approach to extract product's design features from online customers' reviews. Comput Ind 116:103175
Souri ME, Gao J, Simmonds C (2019) Integrating manufacturing knowledge with design process to improve quality in the aerospace industry. Procedia CIRP 84:374–379
Ko T, Lee JH, Cho H, Cho S, Lee W, Lee M (2017) Machine learning-based anomaly detection via integration of manufacturing, inspection and after-sales service data. Ind Manag Data Syst 117(5):927–945
Li ZH, Yao LN, Chang XJ et al (2019) Zero-shot event detection via event-adaptive concept relevance mining. Pattern Recogn 88:595–603
Wisnesky R, Breiner S, Jones A, et al (2016) Using category theory to facilitate multiple manufacturing service database integration. J Comput Inf Sci Eng 16(2):021011
Helu M, Joseph A, Hedberg T (2018) A standards-based approach for linking as-planned to as-fabricated product data. CIRP Ann - Manuf Techn 67:487–490
Mekki K, Derigent W, Rondeau E et al (2017) Data lifecycle management in smart building using wireless sensors networks. IFAC-PapersOnLine 50–1:12944–12949
Li DC, Wen IH, Chen WC (2016) A novel data transformation model for small data-set learning. Int J Prod Res 54(24):7453–7463
Calvar TL, Chhel F, Jouault F et al (2021) Coupling solvers with model transformations to generate explorable model sets. Softw Syst Model 20:1633–1652
Xiang F, Huang YY, Zhang Z, Jiang GZ, Zuo Y (2019) Research on ECBOM modelling and energy consumption evaluation based on BOM multi-view transformation. J Amb Intel Hum Comp 10:953–967
Rutle A, Lovino L, König H et al (2020) A query-retyping approach to model transformation co-evolution. Softw Syst Model 19:1107–1138
Rondini A, Pezzotta G, Cavalieri S et al (2018) Standardizing delivery processes to support service transformation: A case of a multinational manufacturing firm. Comput Ind 100:115–128
Costa G, Sicilia A (2020) Alternatives for facilitating automatic transformation of BIM data using sematic query languages. Automat Constr 120:103384
Zhu LL (2019) Research on building semantic model transformation based on integration of BIM and GIS. Central China Normal University 5:35–39 (in Chinese)
Platenius-Mohr M, Malakuti S, Grüner S, Schmitt J, Goldschmidt T (2020) File- and API-based interoperability of digital twins by model transformation: An IIoT case study using asset administration shell. Future Gener Comp Sy 113:94–105
Burgueño L, Cabot J, Li S et al (2021) A generic LSTM neural network architecture to infer heterogeneous model transformations. Softw Syst Model: https://doi.org/10.1007/s10270-021-00893-y
Höppner S, Kehrer T, Tichy M (2021) Constrasting dedicated model transformation languages versus general purpose languages: a historical perspective on ATL versus Java based on complexity and size. Softw Syst Model: https://doi.org/10.1007/s10270-021-00937-3
Jesús B, Lucía DV, Pedro A, Ana N (2019) A safety analysis of roundabouts and turbo roundabouts based on Petri nets. Traffic Inj Prev 20(4):400–405
Panahandeh M, Hamdaqa M, Zamani B et al (2021) MUPPIT: a method for using proper patterns in model transformations. Softw Syst Model 20:1491–1523
Azizi B, Zamani B, Kolahdouz-Rahimi S (2020) SEET: Symbolic execution of ETL transformations. J Syst Softw 168:110675
Chu CY, Ren XS, Sun AC (2018) Platform independent model transformation based on sysml. Comput Appl Softw 35(12):7–11 (in Chinese)
Qi LQ, Wang CC, Wang CD (2020) Key Factors of the transformation of port’s equipment manufacturing and producer services based on virtual alliance. J Coastal Res103:654–657
Rodriguez-Echeverria R, Macias F, Rutle A et al (2021) Suggesting model transformation repairs for rule-based languages using a contract-based testing approach. Softw Syst Model: https://doi.org/10.1007/s10270-021-00891-0
Xu B, Qi J, Hu XX, Leung KS et al (2018) Self-adaptive bat algorithm for large scale cloud manufacturing service composition. Peer Peer Netw Appl 11:1115–1128
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This research was supported by the National Science and Technology Major Project of China under Grant No. 2018ZX04001006.
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Ding, T., Yan, G., Zhou, Z. et al. A novel manufacturing service model transformation method based on product lifecycle. Peer-to-Peer Netw. Appl. 15, 1638–1652 (2022). https://doi.org/10.1007/s12083-022-01311-w
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DOI: https://doi.org/10.1007/s12083-022-01311-w