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Identifying part commonalities in a manufacturing company database

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Manufacturing companies that produce and assemble multiple products rely on databases containing thousands or even millions of parts. These databases are expensive to support, maintain and the inherent complexity does not allow end users to utilize fully such databases. Designers and engineers are often not able to find previously created parts, which they could potentially reuse, and they add one more part to the database. Engineered improvements without removal of the previous version of the component also cause the avoidable increase of elements in the database. Reuse of parts or planned development of common parts across products brings many benefits for manufacturers. Search algorithm utilized across part databases and varying projects allows identifying similar parts. The goal is to compare part names and attributes resulting in the assignment of a similarity score. Determining common and differentiating part attributes and characteristics between pairs of components allows nominating parts that can become shared in different products. The case study utilizes an industrial example to evaluate and assess the feasibility of the proposed method for identifying commonality opportunities. It turned out that it is possible to find many parts that can be potentially shared between different products.
Rocznik
Strony
336--346
Opis fizyczny
Bibliogr. 17 poz., rys., wykr.
Twórcy
autor
  • MITPortugal, Instituto Superior Tecnico, Universidade de Lisboa, Lisbon, Portugal
autor
  • LAETA, IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
Bibliografia
  • [1] Boas R, Cameron B, Crawley EF. Divergence and Lifecycle Offsets in Product Families with Commonality. Systems Engineering. 2013.
  • [2] Christen P. Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection. Springer Science & Business Media; 2012.
  • [3] Corl MJ. Methodology for Optimizing Commonality Decisions in Multiple Classes of Ships. 2007 [cited 2015 Jun 28];Available from: http://deepblue.lib.umich.edu/handle/2027.42/55684
  • [4] Corl MJ, Parsons MG, Kokkolaras M. Optimal Commonality Decisions in Multiple Ship Classes [Internet]. In: Simpson TW, Jiao J (Roger), Siddique Z, Hölttä-Otto K, editors. Advances in Product Family and Product Platform Design. Springer New York; 2014 [cited 2015 Jan 7]. p. 625–645.Available from: http://link.springer.com/chapter/10.1007/978-1-4614-7937-6_25
  • [5] Fisher M, Ramdas K, Ulrich K. Component Sharing in the Management of Product Variety: A Study of Automotive Braking Systems. Manage. Sci. 1999 Mar;45(3):297–315.
  • [6] Hanafy M, ElMaraghy H. A modular product multi-platform configuration model. International Journal of Computer Integrated Manufacturing. 2015 Sep 2;28(9):999– 1014.
  • [7] Hoppmann J, Rebentisch E, Dombrowski U, Thimo Zahn. A Framework for Organizing Lean Product Development. Engineering Management Journal. 2011 Mar; 23(1): 3–15.
  • [8] Kelkar BA, Manwade PKB, Patil PGA. Near Duplicate Detection In Relational Database [Internet]. ESRSA Publications; 2013 [cited 2015 Jul 14]. Available from: http://www.ijert.org/view-pdf/2879/near-duplicate-detection-in-relational-database
  • [9] Lin Y-S, Liao T-Y, Lee S-J. Detecting near-duplicate documents using sentence-level features and supervised learning. Expert Systems with Applications. 2013 Apr; 40 (5): 1467–1476.
  • [10] Liu N, Choi T-M, Yuen CM, Ng F. Optimal Pricing, Modularity, and Return Policy Under Mass Customization. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans. 2012 May;42(3):604–614.
  • [11] McCoy AB, Wright A, Kahn MG, Shapiro JS, Bernstam EV, Sittig DF. Matching identifiers in electronic health records: implications for duplicate records and patient safety. BMJ Qual Saf. 2013 Mar 1; 22 (3): 219–224.
  • [12] Meyer MH, Lehnerd AP. The power of product platforms: building value and cost leadership. Free Press; 1997.
  • [13] Nobelius D, Sundgren N. Managerial issues in parts sharing among product development projects: a case study. Journal of Engineering and Technology Management. 2002; 19 (1): 59–73. 346
  • [14] Shi J (Junmin), Zhao Y. Component commonality under no-holdback allocation rules. Operations Research Letters. 2014 Sep; 42 (6–7): 409–413.
  • [15] Wang G, Chen S, Lin M, Liu X. SBBS: A sliding blocking algorithm with backtracking sub-blocks for duplicate data detection. Expert Systems with Applications. 2014 Apr; 41 (5): 2415–2423.
  • [16] Yan S, Lee D, Kan M-Y, Giles LC. Adaptive Sorted Neighborhood Methods for Efficient Record Linkage [Internet]. In: Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries. New York, NY, USA: ACM; 2007 [cited 2015 Oct 28]. p. 185–194.Available from: http://doi.acm.org/10.1145/1255175.1255213
  • [17] A330 Family: A330-200, A330-300 - A330 photos, pictures, A330 videos, A330 3D view | Airbus | Airbus, a leading aircraft manufacturer [Internet]. airbus. [cited 2015 Oct 27];Available from: http://www.airbus.com/aircraftfamilies/passengeraircraft/a330family/
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-bb121094-5c71-4bb6-86e8-bb459f43ab6d
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