Digital Manufacturing for Aerospace Industry

Post on 10-Apr-2018

219 views 0 download

Transcript of Digital Manufacturing for Aerospace Industry

8/8/2019 Digital Manufacturing for Aerospace Industry

http://slidepdf.com/reader/full/digital-manufacturing-for-aerospace-industry 1/3

8/8/2019 Digital Manufacturing for Aerospace Industry

http://slidepdf.com/reader/full/digital-manufacturing-for-aerospace-industry 2/3

Virtual Concept 2006 Digital Manufacturing for Aerospace industry: Experimental Aircraft

aper Number -2- Copyright Virtual Concept

In addition, virtual manufacturing also reduces the cost of tooling, eliminates the need for multiple physical prototypes,and reduces material waste. It provides manufacturers with theconfidence of knowing that they can deliver quality products tomarket, on time and within budget. Small improvements inmanufacturing have dramatic and profound effects in terms of cost and quality, and it not only happens to the beginning of the life of the product but during its service life. [D1, C1, G4]

Return on investment calculations have shown that smallsavings in material usage deliver enormous returns in amanufacturing environment. A virtual lab for product creationuses a computer to simulate a product’s performance and theprocesses involved in its fabrication. This technology hasenabled companies to simulate fabrication and testing in amore realistic manner than ever before.

The case study explained next is a project concerning theassembly and redesign of an experimental, true-scale aircraftRV-10, with capacity for four passengers. This aircraft wassupplied by ICKTAR, a Mexican company, with the generalobjective of producing technological competences forproviding high tech. services to the aerospace industry. Suchdemanding project was entirely carried out by students of Tecnológico de Monterrey, enrolled in different teams, eachone undertaking a specific task (or sub-project) tow ards thecompletion of the full project. Instructors acted as moderatorsand promoters of inter-team communication, rather thantransmitters of knowledge. [E1, Y1, G3]

Some of the results obtained through this project are shown inthis paper. From the available manufacturing tools thatDassault Sytemes ® offers in PLM environment, just some of them have been used according to the project’s requirements:CATIA®, DELMIA® and QUEST®.

Product design analysis

One part of the study was the design of the positioning andanchorage mechanisms of the battery system to a structure of new design (Figure 1). The design of this new product wasperformed with CATIA® software.

Figure 1 : Battery model

Figure 2: Riveting machine

The requirement of creating tools that would help in thefabrication phase came up. This machine (Figure 2) wasplanned to help in the drilling and riveting stations,optimizing and simplifying the work to be done in theconstruction stations. This designed tool is a pneumaticriveter with a rivets container that facilitates their positioningduring the process.

Layout planning analysis

The preliminary work consisted in subdividing and groupingthe required steps for the assembly into five differentworkstations: riveting, drilling, de-burring, fixturing andassembly. After that, for each station were defined resources,processes and knowledge using the collaborative work of experts consulted, as well as the previous experiences of themembers.

The next step was to propose different layouts to arrange thedifferent workstations, considering the work sequence, thetimings, the material flows and the value-adding processes(Figure 3). For this task, the PLM digital tools (Factory Flowsimulation, for instance) were significantly useful since someof the modules are designed to perform these specificactivities, sharing automatically knowledge and information.

Figure 3 : Layout planning analysis

Ergonomic analysis Other stage of the project was to use virtual manufacturingtools in order to make ergonomics analysis due to thecomplexity of the traditional assembly procedure (Figure 4).This analysis included: time studies, process optimizationwith an special focus on critical steps of the assemblyprocess, for quality considerations.

8/8/2019 Digital Manufacturing for Aerospace Industry

http://slidepdf.com/reader/full/digital-manufacturing-for-aerospace-industry 3/3

Virtual Concept 2006 Digital Manufacturing for Aerospace industry: Experimental Aircraft

aper Number -3- Copyright Virtual Concept

Figure 4 : Ergonomic simulation analysis

Factory flow simulation

Finally, a study of all the airplane construction phaserequirements was analyzed in terms of the different flows. Adivision has been made into elements, such as materials,manpower, energy requirements, etc. Figure 5 shows thesimulation of the queue model for the factory flow .

Figure 5 : Queue model factory flow simulation

Conclusions

Digital manufacturing tools are a helpful set of tools into thePLM framework, which allow companies to reduce the wastein material, resources and time. This technology involves themain process stages of the Product Lifecycle, for instance,product design, process design, factory flow simulation,ergonomic analysis, etc. Digital manufacturing are offeringhigh benefits and revenues to all kind of manufacturingindustries as well as complex industries as the aerospace.

Digital manufacturing tools provided by Dassault Systemes®(CATIA®, DELMIA ® and QUEST ®) supported successfullythe RV-10 battery model development by means of the productdesign made in CATIA, process design and ergonomicsanalysis by DELMIA and factory flow simulation developed inQUEST. The results were an efficient battery supportmodeling, handling features design, new tool design, andoptimal layout for manufacturing and assembly processes. Allthese results allowed building expertise and knowledge toimprove the ICKTAR’s processes.

References

[C1] Chudoba, K., Wynn, E., Lu, M., Watwon-Manheim,M., (2005). How virtual are we? Measuring virtuality and understanding its impact in a global organization.Information Systems Journal. 15 (4):279-306.

[D1] Deviprasad, T., Kesavadas, T. (2003) . Virtual prototyping of assembly components using process modeling.Journal of Manufacturing Systems. 22 (1):16.

[E1] Elizalde, H.; Ramírez, R.; Orta, P.; Guerra, D.; Pérez,Y. (2006) An Educational Framework for Learning

Engineering Design through Reverse Engineering .Proceedings of Sixth intern ational workshop on ActiveLearning in Engineering Education, Tecnológico deMonterrey, Monterrey, México. pp 344-365.

[G1] Guerra- Zubiaga, D. A.; Gonzalez, E.; Rodriguez-Bueno, S.; Contero, M. (2006) Knowledge Structures: a key

factor in Product Lifecycle Management . Proceedings of 12International Annual Conference of SOMIM, Acapulco,México, (1) 44.

[G2] Guerra, D.; Rios, E.; Molina, A.; Parkin, R.; Jackson,M.; Niño, E. (2006) Mechatronics Design Methodology

Applied at Manufacturing Companies . The 10thMechatronics Forum Biennial International Conference MX2006, Penn State Great Valley, USA.

[G3] Guerra, D.; Rosas, R.; Camacho, R.; Molina, A. (2005) Information Models to Support Reconfigurable Manufacturing System Design , International Conference onProduct Lifecycle Management PLM'05, IUT Lumiere –Lumiere University of Lyon, France. Editors: AbdelazizBouras , Balan Gurumoorthy, Rachuri Sudarsan, pp . 55 – 63.Inderscience Enterprises Limited

[G4] Grieves, M. (2006). Product Lifecycle Management: Driving next generation of the lean thinking . McGraw Hill.

[Q1] Qin, S., Harrison, R., and Wright, D. (2004). Development of a novel 3D simulation modelling system for distributed manufacturing. Computers in Industry, 54 (1):69-81.

[S1] Saaksvuori, A. & Immonen, A. (2004). Product Lifecycle Management . Springer.

[S2] Stark, J.(2006). Product Lifecycle Management: 21st Century paradigm for product realisation. Springer.

[S3] Sudarsan, R.; Fenvers, S.; Siriram, R & Wang, F.(2005). A product information modeling framework for

product lifecycle management. Computer-Aided Design , 37(13): 1399-1411.

[Y1] Yingxue, Y., Hang, Z., Jianguang, L., Zhejun, Y.(2006). Modeling of virtual workpiece with machining errorsrepresentation in turning . Journal of Materials ProcessingTechnology, 172 (3, 10): 437-444.