TY - GEN
T1 - An investigation to manufacturing analytical services composition using the analytical target cascading method
AU - Tien, Kai Wen
AU - Kulvatunyou, Boonserm
AU - Jung, Kiwook
AU - Prabhu, Vittaldas
N1 - Funding Information:
The work described in this paper was funded in part by NIST cooperative agreement with Penn State University No. 70NANB14H255.
Publisher Copyright:
© IFIP International Federation for Information Processing 2016. All rights reserved.
PY - 2016
Y1 - 2016
N2 - As cloud computing is increasingly adopted, the trend is to offer software functions as modular services and compose them into larger, more meaningful ones. The trend is attractive to analytical problems in the manufacturing system design and performance improvement domain because (1) finding a global optimization for the system is a complex problem; and (2) sub-problems are typically compartmentalized by the organizational structure. However, solving sub-problems by independent services can result in a sub-optimal solution at the system level. This paper investigates the technique called Analytical Target Cascading (ATC) to coordinate the optimization of loosely-coupled subproblems, each may be modularly formulated by differing departments and be solved by modular analytical services. The result demonstrates that ATC is a promising method in that it offers system-level optimal solutions that can scale up by exploiting distributed and modular executions while allowing easier management of the problem formulation.
AB - As cloud computing is increasingly adopted, the trend is to offer software functions as modular services and compose them into larger, more meaningful ones. The trend is attractive to analytical problems in the manufacturing system design and performance improvement domain because (1) finding a global optimization for the system is a complex problem; and (2) sub-problems are typically compartmentalized by the organizational structure. However, solving sub-problems by independent services can result in a sub-optimal solution at the system level. This paper investigates the technique called Analytical Target Cascading (ATC) to coordinate the optimization of loosely-coupled subproblems, each may be modularly formulated by differing departments and be solved by modular analytical services. The result demonstrates that ATC is a promising method in that it offers system-level optimal solutions that can scale up by exploiting distributed and modular executions while allowing easier management of the problem formulation.
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U2 - 10.1007/978-3-319-51133-7_56
DO - 10.1007/978-3-319-51133-7_56
M3 - Conference contribution
AN - SCOPUS:85016034761
SN - 9783319511320
T3 - IFIP Advances in Information and Communication Technology
SP - 469
EP - 477
BT - Advances in Production Management Systems
A2 - Naas, Irenilza
A2 - Vendrametto, Oduvaldo
A2 - Reis, Joao Mendes
A2 - Goncalves, Rodrigo Franco
A2 - Silva, Marcia Terra
A2 - Kiritsis, Gregor
A2 - von Cieminski, Gregor
PB - Springer New York LLC
T2 - IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2016
Y2 - 3 September 2016 through 7 September 2016
ER -