Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Latest Advancement in Cloud Technologies Read chapter Read first chapter

2018 | OriginalPaper | Chapter

5. Cloud-Enabled Distributed Process Planning

Authors : Lihui Wang, Xi Vincent Wang

Published in: Cloud-Based Cyber-Physical Systems in Manufacturing

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Today, the dynamic market requires manufacturing firms to possess a high degree of adaptability to deal with shop-floor uncertainties. Specifically targeting SMEs active in the metal cutting sector who normally deal with intensive process planning problems, researchers have tried to address the subject. Among reported solutions, Cloud-DPP elaborates a two-layer distributed adaptive process planning based on function block technology and cloud concept. One of the challenges of companies is to machine as many part features as possible in a single setup on a single machine. Nowadays, multi-tasking machines are widely used due to their various advantages, such as reduced setup times and increased machining accuracy. However, they also possess programming challenges because of their complex configuration and multiple machining functions. This chapter reports the latest state of the design and implementation of Cloud-DPP methodology to support parts with a combination of milling and turning features, and process planning for multi-tasking machining centres with special functionalities to minimise the total number of setups. This chapter covers representation of machining states and part transfer functionality, support of multi-tasking machines in adaptive setup merging, development of special function blocks to handle sub-setups and transitions, and finally generation of function block networks for the merged setups. A case study is also included to validate the reported methodology.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Machine Availability Monitoring and Process Planning
next chapter Adaptive Machining Using Function Blocks
Literature
1.
M. Jeremy B., D.C. McFarlane, Assessing the responsiveness of existing production operations. Int. J. Oper. Prod. Manage. 19(8), 765–784 (1999)
2.
L. Wang, M. Givehchi, Web-DPP: an adaptive approach to planning and monitoring of job-shop machining operations, in Proceedings of the 7th CIRP International Conference on Digital Enterprise Technology (2011)
3.
L. Wang, H.Y. Feng, N. Cai, Architecture design for distributed process planning. J. Manuf. Syst. 22(2), 99–115 (2003)CrossRef
4.
X. Xu, L. Wang, S.T. Newman, Computer-aided process planning—a critical review of recent developments and future trends. Int. J. Comput. Integr. Manuf. 24(1), 1–31 (2011)CrossRef
5.
W. Shen, L. Wang, Q. Hao, Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 36(4), 563–577 (2006)CrossRef
6.
L. Wang, An overview of function block enabled adaptive process planning for machining. J. Manuf. Syst. 35, 10–25 (2015)CrossRef
7.
L. Wang, M. Holm, G. Adamson, Embedding a process plan in function blocks for adaptive machining. CIRP Ann. Manuf. Technol. 59(1), 433–436 (2010)
8.
L. Wang, H.Y. Feng, C. Song, W. Jin, Function block design for adaptive execution control of job shop machining operations. Int. J. Prod. Res. 47(12), 3413–3434 (2009)CrossRefMATH
9.
L. Wang, Wise-shopfloor: an integrated approach for web-based collaborative manufacturing. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 38(4), 562–573 (2008)CrossRef
10.
S. Shingo, A Revolution in Manufacturing: The SMED System (Productivity Press, 1985)
11.
N.C. Chiu, S.C. Fang, Y.S. Lee, Sequencing parallel machining operations by genetic algorithm. Comput. Ind. Eng. 36(2), 259–280 (1999)CrossRef
12.
D.E.R.E.K. Yip-Hoi, D. Dutta, A genetic algorithm application for sequencing operations in process planning for parallel machining. IIE Trans. 28(1), 55–68 (1996)
13.
E. Budak, A. Comak, E. Ozturk, Stability and high performance machining conditions in simultaneous milling. CIRP Ann. Manuf. Technol. 62(1), 403–406 (2013)CrossRef
14.
P. Selvaraj, E. Thirumal, P. Radhakrishnan, Multi-tasking machines: a new approach to increase the productivity of aircraft components manufacture. Int. J. Comput. Appl. Technol. 27(1), 24–30 (2006)CrossRef
15.
M. Djassemi, Emergence of multitasking machining systems: applications and best selection practices. J. Manuf Technol. Manage. 20(1), 130–142 (2008)CrossRef
16.
T. Moriwaki, Multi-functional machine tool. CIRP Ann. Manuf. Technol. 57(2), 736–749 (2008)CrossRef
17.
P. Selvaraj, P. Radhakrishnan, M. Adithan, Study of economics of multitasking with reference to a class of mechanical system components. Int. J. Manuf. Technol. Manage. 22(4), 301–323 (2011)
18.
K.H. Park, The growing importance of multitasking. Manuf. Eng. 148(5), 152–152 (2012)
19.
M. Mori, M. Fujishima, O. Yohei, 5 axis mill turn and hybrid machining for advanced application. Procedia CIRP 1, 22–27 (2012)CrossRef
20.
21.
Y. Altintas, C. Brecher, M. Weck, S. Witt, Virtual machine tool. CIRP Ann. Manuf. Technol. 542, 115–138 (2005)CrossRef
22.
R.S.U. Rosso, S.T. Newman, S. Rahimifard, The adoption of STEP-NC for the manufacture of asymmetric rotational components. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 218(11), 1639–1644 (2004)CrossRef
23.
S. Li, J.J. Shah, Recognition of user-defined turning features for mill/turn parts. J. Comput. Inf. Sci. Eng. 7(3), 225–235 (2007)CrossRef
24.
Y.J. Tseng, C.C. Liu, Concurrent analysis of machining sequences and fixturing set-ups for minimizing set-up changes for machining mill-turn parts. Int. J. Prod. Res. 39(18), 4197–4214 (2001)CrossRefMATH
25.
K. Waiyagan, E.L. Bohez, Intelligent feature based process planning for five-axis mill-turn parts. Comput. Ind. 60(5), 296–316 (2009)CrossRef
26.
K.H. Miska, Driven tools turn on turning centers. Manuf. Eng. 104(5), 63–66 (1990)
27.
D. Yip-Hoi, D. Dutta, Finding the maximum turnable state for mill/turn parts. Comput. Aided Des. 29(12), 879–894 (1997)CrossRef
28.
Y.S. Lee, C.J. Chiou, Unfolded projection approach to machining non-coaxial parts on mill-turn machines. Comput. Ind. 39(2), 147–173 (1999)CrossRef
29.
N. Date, P. Krishnaswami, V.S.K. Motipalli, Automated process planning method to machine A B-spline free-form feature on a mill–turn center. Comput. Ind. Eng. 56(1), 198–207 (2009)CrossRef
30.
Y.J. Tseng, S.B. Joshi, Recognition of interacting rotational and prismatic machining features from 3-D mill-turn parts. Int. J. Prod. Res. 36(11), 3147–3165 (1998)CrossRefMATH
31.
B. Hedrick, R.J. Urbanic, H.A. ElMaraghy, Multi-tasking machine tools and their impact on process planning, in CIRP 2004 International Design Conference, Cairo, Egypt, 2004
32.
Y.S. Kim, Y. Kim, F. Pariente, E. Wang, Geometric reasoning for mill-turn machining process planning. Comput. Ind. Eng. 33(3), 501–504 (1997)CrossRef
33.
K. Kubota, T. Kotani, K. Nakamoto, T. Ishida, Y. Takeuchi, Development of CAM system for multi-tasking machine tools. J. Adv. Mech. Des. Syst. Manuf. 4(5), 816–826 (2010)CrossRef
34.
K. Dwijayanti, H. Aoyama, Basic study on process planning for turning-milling center based on machining feature recognition. J. Adv. Mech. Des. Syst. Manuf. 8(4) (2014)
35.
K. Dwijayanti, H. Aoyama, Development of automatic process planning system for turning-milling center with 2 turrets system. Precis. Eng. J. 81(5), 471–480 (2015)CrossRef
36.
J. Zhu, M. Kato, T. Tanaka, H. Yoshioka, Y. Saito, Graph based automatic process planning system for multi-tasking machine. J. Adv. Mech. Des. Syst. Manuf. 9(3) (2015)
37.
Y. Li, X. Liu, J.X. Gao, P.G. Maropo, A dynamic feature information model for integrated manufacturing planning and optimization. CIRP Ann. Manuf. Technol. 61(1), 167–170 (2012)CrossRef
38.
Y. Li, W. Wang, X. Liu, Y. Ma, Definition and recognition of rib features in aircraft structural part. Int. J. Comput. Integr. Manuf. 27(1), 1–19 (2014)CrossRef
39.
L. Wang, N. Cai, H.Y. Feng, J. Ma, ASP: an adaptive setup planning approach for dynamic machine assignments. Autom. Sci. Eng. IEEE Trans. 7(1), 2–14 (2010)CrossRef
40.
M. Givehchi, A. Haghighi, L. Wang, Generic machining process sequencing through a revised enriched machining feature concept. J. Manuf. Syst. 37(2), 564–575 (2015)CrossRef
41.
Z. Liu, L. Wang, Sequencing of interacting prismatic machining features for process planning. Comput. Ind. 58(4), 295–303 (2007)CrossRef
Metadata
Title
Cloud-Enabled Distributed Process Planning
Authors
Lihui Wang
Xi Vincent Wang
Copyright Year
2018
Book
Cloud-Based Cyber-Physical Systems in Manufacturing

Print ISBN: 978-3-319-67692-0

Electronic ISBN: 978-3-319-67693-7

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-67693-7_5

Premium Partners

    Image Credits