The way machining operations have been running has changed over the years. Nowadays, machine utilization and availability monitoring are becoming increasingly important for the smooth operation of modern workshops. Moreover, the nature of jobs undertaken by manufacturing small and medium enterprises (SMEs) has shifted from a mass production to small batch. To address the challenges caused by modern fast changing environments, a new cloud-based approach for monitoring the use of manufacturing equipment, dispatching jobs to the selected computer numerical control (CNC) machines, and creating the optimum machining code is presented. In this approach the manufacturing equipment is monitored using a sensor network and though an information fusion technique it derives and broadcasts the data of available tools and machines through the internet to a cloud-based platform. On the manufacturing equipment event driven function blocks with embedded optimization algorithms are responsible for selecting the optimal cutting parameters and generating the moves required for machining the parts while considering the latest information regarding the available machines and cutting tools. A case study based on scenario from a shop floor that undertakes machining jobs is used to demonstrate the developed methods and tools.
Issue Section:
Special Section Articles
References
1.
Hädeby
, H.
, and Sohlenius
, G.
, 1989
, “Increasing Availability and Efficiency by Monitoring the Cutting Process in a Lathe During Production With Limited Manpower
,” CIRP Ann.
, 38
(1
), pp. 393
–398
.10.1016/S0007-8506(07)62731-02.
Mourtzis
, D.
, Doukas
, M.
, Vlachou
, A.
, and Xanthopoulos
, N.
, 2014
, “Machine Availability Monitoring for Adaptive Holistic Scheduling: A Conceptual Framework for Mass Customisation
,” Proceedings of the Procedia CIRP 8th International Conference on Digital Enterprise Technology—DET
, Stuttgart, Germany, Mar. 25–28, pp. 406
–413
.3.
Mitchell
, J. S.
, 1993
, Introduction to Machinery Analysis and Monitoring
, 2nd ed., PennWell Publishing
, Tulsa, OK
, p. 566
.4.
Mohring
, H. C.
, Litwinski
, K. M.
, and Gummer
, O.
, 2010
, “Process Monitoring With Sensory Machine Tool Components
,” CIRP Ann.
, 59
(1
), pp. 383
–386
.10.1016/j.cirp.2010.03.0875.
Teti
, R.
, Jemielniak
, K.
, O'Donnell
, G.
, and Dornfeld
, D.
, 2010
, “Advanced Monitoring of Machining Operations
,” CIRP Ann.
, 59
(2
), pp. 717
–739
.10.1016/j.cirp.2010.05.0106.
Kunpeng
, Z.
, San
, W. Y.
, and Soon
, H. G.
, 2009
, “Wavelet Analysis of Sensor Signals for Tool Condition Monitoring: A Review and Some New Results
,” Int. J. Mach. Tools Manuf.
, 49
(7–8
), pp. 537
–553
.10.1016/j.ijmachtools.2009.02.0037.
Jardine
, A. K. S.
, Lin
, D.
, and Banjevic
, D.
, 2006
, “A Review on Machinery Diagnostics and Prognostics Implementing Condition-Based Maintenance
,” Mech. Syst. Signal Process.
, 20
(7
), pp. 1483
–1510
.10.1016/j.ymssp.2005.09.0128.
Si
, X. S.
, Wang
, W.
, Hu
, C. H.
, and Zhou
, D. H.
, 2011
, “Remaining Useful Life Estimation—A Review on the Statistical Data Driven Approaches
,” Eur. J. Oper. Res.
, 213
(1
), pp. 1
–14
.10.1016/j.ejor.2010.11.0189.
Rehorn
, A. G.
, Jiang
, J.
, and Orban
, P. E.
, 2005
, “State-of-the-Art Methods and Results in Tool Condition Monitoring: A Review
,” Int. J. Adv. Manuf. Technol.
, 26
(7–8
), pp. 693
–710
.10.1007/s00170-004-2038-210.
Attanasio
, A.
, Ceretti
, E.
, Giardini
, C.
, and Cappellini
, C.
, 2013
, “Tool Wear in Cutting Operations: Experimental Analysis and Analytical Models
,” ASME J. Manuf. Sci. Eng.
, 135
(5
), p.051012
.10.1115/1.402501011.
Wang
, L.
, 2013
, “Machine Availability Monitoring and Machining Process Planning Towards Cloud Manufacturing
,” CIRP J. Manuf. Sci. Technol.
, 6
(4), pp. 263
–273
.10.1016/j.cirpj.2013.07.00112.
Bhuiyan
, M. S. H.
, and Choudhury
, I. A.
, 2014
, “13.22—Review of Sensor Applications in Tool Condition Monitoring in Machining
,” Comp. Mater. Process.
, 13
, pp. 539
–569
.10.1016/B978-0-08-096532-1.01330-313.
Tlusty
, J.
, and Andrews
, G. C.
, 1983
, “A Critical Review of Sensors for Unmanned Machining
,” CIRP Ann.
, 32
(2
), pp. 563
–572
.10.1016/S0007-8506(07)60184-X14.
Byrne
, G.
, Dornfeld
, D.
, Inasaki
, I.
, Konig
, W.
, and Teti
, R.
, 1995
, “Tool Condition Monitoring—The Status of Research and Industrial Application
,” CIRP Ann.
, 44
(2
), pp. 541
–567
.10.1016/S0007-8506(07)60503-415.
Dimla
, E.
, and Dimla
, S.
, 2000
, “Sensor Signals for Tool-Wear Monitoring in Metal Cutting Operations—A Review of Methods
,” Int. J. Mach. Tools Manuf.
, 40
(8
), pp. 1073
–1098
.10.1016/S0890-6955(99)00122-416.
Zhang
, D.
, Dai
, S.
, Han
, Y.
, and Chen
, D.
, 1994
, “On-Line Monitoring of Tool Breakage Using Spindle Current in Milling
,” Proceedings of the 1st Asia–Pacific and 2nd Japan–China International Conference Progress of Cutting and Grinding
, Shanghai, China, pp. 270
–276
.17.
Khaleghi
, B.
, Khamisa
, A.
, Karraya
, F. O.
, and Razavib
, S. N.
, 2013
,”Multi Sensor Data Fusion: A Review of the State-of-the-Art
,” Inform. Fusion
, 14
(1
), pp. 28
–44
.10.1016/j.inffus.2011.08.00118.
Hall
, D. L.
, and Llinas
, J.
, 2001
, Handbook of Multisensor Data Fusion
, CRC Press
, Boca Raton, FL
.19.
Chryssolouris
, G.
, and Domroese
, M.
, 1989
, “An Experiment Study of Strategies for Integrating Sensor Information in Machining
,” CIRP Ann.
, 38
(1
), pp. 425
–428
.10.1016/S0007-8506(07)62738-320.
Saaty
, T.
, 2008
, “Decision Making With Analytic Hierarchy Process
,” Int. J. Serv. Sci.
, 1
(1
), pp. 83
–98
.10.1504/IJSSCI.2008.01759021.
Awasthi
, A.
, and Chauhan
, S.
, 2011
, “Using AHP and Dempster–Shafer Theory for Evaluating Sustainable Transport Solutions
,” Environ. Modell. Software
, 26
(6
), pp. 787
–796
.10.1016/j.envsoft.2010.11.01022.
Basir
, O.
, and Yuan
, X.
, 2007
, “Engine Fault Diagnosis Based on Multi-Sensor Information Fusion Using Dempster–Shafer Evidence Theory
,” Inform. Fusion
, 8
(4
), pp. 379
–386
.10.1016/j.inffus.2005.07.00323.
Kaya
, T.
, and Kahraman
, C.
, 2010
, “Multicriteria Renewable Energy Planning Using an Integrated Fuzzy VIKOR & AHP Methodology: The Case of Istanbul
,” Energy
, 35
(6
), pp. 2517
–2527
.10.1016/j.energy.2010.02.05124.
Mendoza
, G. A.
, 2000
, “Multiple Criteria Decision Making Approaches to Assessing Forest Sustainability Using Criteria and Indicators: A Case Study
,” For. Ecol. Manage.
, 131
(1
), pp. 107
–126
.10.1016/S0378-1127(99)00204-225.
Lu
, Y.
, Xu
, X.
, and Xu
, J.
, 2014
, “Development of a Hybrid Manufacturing Cloud
,” J. Manuf. Syst.
, 33
(4
), pp. 551
–566
.10.1016/j.jmsy.2014.05.00326.
Xu
, X.
, 2012
, “From Cloud Computing to Cloud Manufacturing
,” Rob. Comput.-Integr. Manuf.
, 28
(1
), pp. 75
–86
.10.1016/j.rcim.2011.07.00227.
Ren
, L.
, Zhang
, L.
, Tao
, F.
, Zhao
, C.
, Chai
, X.
, and Zhao
, X.
, 2015
, “Cloud Manufacturing: From Concept to Practice
,” Enterp. Inform. Syst.
, 9
(2
), pp. 186
–209
.10.1080/17517575.2013.83905528.
Ren
, L.
, Zhang
, L.
, Wang
, L.
, Tao
, F.
, and Chai
, X.
, 2014, “Cloud Manufacturing: Key Characteristics and Applications
,” Int. J. Comput. Integr. Manuf
Taylor & Francis, Boca Raton, FL, (published online).10.1080/0951192X.2014.90210529.
Li
, W.
, and Mehnen
, J.
, 2013
, Cloud Manufacturing: Distributed Computing Technologies for Global and Sustainable Manufacturing
, Springer
, London
.30.
Shahzad
, F.
, 2014
, “State-of-the-Art Survey on Cloud Computing Security Challenges, Approaches and Solutions
,” Proceedings of the 6th International Symposium on Applications of Ad Hoc and Sensor Networks (AASNET’14)
, Vol. 37
, pp. 357
–362
.31.
International Electrotechnical Commission
, 2005
, Function Blocks—Part 1: Architecture
, IEC 61499-1
, Geneva, Switzerland
.32.
Hegny
, I.
, Strasser
, T.
, Melik-Merkumians
, M.
, Wenger
, M.
, and Zoitl
, A.
, 2012
, “Towards an Increased Reusability of Distributed Control Applications Modelled in IEC 61499
,” Proceedings of the 17th IEEE Conference on Emerging Technologies and Factory Automation (ETFA)
, Krakow, Poland, Sept. 17–21, pp. 1
–8
.33.
Black
, G.
, and Vyatkin
, V.
, 2010
, “Intelligent Component-Based Automation of Baggage Handling Systems With IEC 61499
,” IEEE Trans. Autom. Sci. Eng.
, 7
(2
), pp. 337
–351
.10.1109/TASE.2008.200721634.
Wang
, L.
, Adamson
, G.
, Holm
, M.
, and Moore
, P.
, 2012
, “A Review of Function Blocks for Process Planning and Control of Manufacturing Equipment
,” J. Manuf. Syst.
, 31
(3
), pp. 269
–279
.10.1016/j.jmsy.2012.02.00435.
Wang
, L.
, Feng
, H.-Y.
, and Cai
, N.
, 2003
, “Architecture Design for Distributed Process Planning
,” J. Manuf. Syst.
, 22
(2
), pp. 99
–115
.10.1016/S0278-6125(03)90008-236.
Wang
, L.
, Hao
, Q.
, and Shen
, W.
, 2007
, “A Novel Function Block Based Integration Approach to Process Planning and Scheduling With Execution Control
,” Int. J. Manuf. Technol. Manage.
, 11
(2
), pp. 228
–250
.10.1504/IJMTM.2007.01319337.
Wang
, L.
, Song
, Y.
, and Gao
, Q.
, 2009
, “Designing Function Blocks for Distributed Process Planning and Adaptive Control
,” Eng. Appl. Artif. Intell.
, 22
(7
), pp. 1127
–1138
.10.1016/j.engappai.2008.11.00838.
Wang
, L.
, Keshavarzmanesh
, S.
, and Feng
, H.-Y.
, 2008
, “Design of Adaptive Function Blocks for Dynamic Assembly Planning and Control
,” J. Manuf. Syst.
, 27
(1
), pp. 45
–51
.10.1016/j.jmsy.2008.06.00339.
Wang
, L.
, Keshavarzmanesh
, S.
, and Feng
, H.-S.
, 2011
, “A Function Block Based Approach for Increasing Adaptability of Assembly Planning and Control
,” Int. J. Prod. Res.
, 49
(16
), pp. 4903
–4924
.10.1080/00207543.2010.50182740.
Wang
, H.
, Xu
, X.
, and Tedford
, J. D.
, 2007
, “An Adaptable CNC System Based on STEP-NC and Function Blocks
,” Int. J. Prod. Res.
, 45
(17
), pp. 3809
–3829
.10.1080/0020754060077407541.
Minhat
, M.
, Vyatkin
, V.
, Xu
, X.
, and Al-Bayaa
, Z.
, 2009
, “A Novel Open CNC Architecture Based on STEP-NC Data Model and IEC 61499 Function Blocks
,” Rob. Comput.-Integr. Manuf.
, 25
(3), pp. 560
–569
.10.1016/j.rcim.2008.03.02142.
Huang
, X.
, 2010
, “Enhancing STEP-NC Compliant CNC Controller for Distributed and Reconfigurable Environment in Production Line
,” Proceedings of the International Conference on Computer, Mechatronics, Control, and Electronic Engineering
, pp. 106
–109
.43.
Yusup
, N.
, Zain
, A. M.
, and Hashim
, S. Z. M.
, 2012
, “Evolutionary Techniques in Optimizing Machining Parameters: Review and Recent Applications (2007–2011)
,” Expert Syst. Appl.
, 39
(10
), pp. 9909
–9927
.10.1016/j.eswa.2012.02.10944.
Zheng
, C. M.
, Junz Wang
, J.-J.
, and Sung
, C. F.
, 2013
, “Analytical Prediction of the Critical Depth of Cut and Worst Spindle Speeds for Chatter in End Milling
,” ASME J. Manuf. Sci. Eng.
, 136
(1
), p. 011003
.10.1115/1.402545245.
Cheng
, Z. C.
, and Abdelkhalek
, S.
, 2014
, “A New Approach to Planning Plungers Paths for Efficient 2½-Axis Computer Numerically Controlled Plunge Milling of Complex Pockets With Islands
,” ASME J. Manuf. Sci. Eng.
, 136
(4
), p. 041013
.10.1115/1.402753846.
Sambhav
, K.
, Tandon
, P.
, and Dhande
, S. G.
, 2014
, “Force Modeling for Generic Profile of Drills
,” ASME J. Manuf. Sci. Eng.
, 136
(4
), p. 041019
.10.1115/1.402759547.
Sonmez
, A. I.
, Baykasoglu
, A.
, Dereli
, T.
, and Filiz
, I. H.
, 1999
, “Dynamic Optimization of Multi-Pass Milling Operations Via Geometric Programming
,” Int. J. Mach. Tools Manuf.
, 39
(2), pp. 297
–320
.10.1016/S0890-6955(98)00027-348.
Rao
, R. V.
, and Pawar
, P. J.
, 2010
, “Parameter Optimization of a Multi-Pass Milling Process Using Non-Traditional Optimization Algorithms
,” Appl. Soft Comput.
, 10
(2
), pp. 445
–456
.10.1016/j.asoc.2009.08.00749.
Shunmugam
, M. S.
, Bhaskara Reddy
, S. V.
, and Narendran
, T. T.
, 2000
, “Selection of Optimal Conditions in Multi-Pass Face-Milling Using a Genetic Algorithm
,” Int. J. Mach. Tools Manuf.
, 40
(3
), pp. 401
–414
.10.1016/S0890-6955(99)00063-250.
El-Hofy
, H.
, 2006
, Fundamentals of Machining Processes: Conventional and Nonconventional Processes
, CRC Taylor & Francis
, New York
, Chap. VI.51.
FBDK—Function Block Development Kit,
2014
, Accessed Oct. 14, www.holobloc.com52.
NC Speed, 2012, “
Version 6
,” Formtec GmbH, www.formtec.deCopyright © 2015 by ASME
You do not currently have access to this content.
