Research Papers

Sustainable Manufacturing With Cyber-Physical Discrete Manufacturing Networks: Overview and Modeling Framework

[+] Author and Article Information
Daniel J. Garcia

Department of Chemical and Biological Engineering,
Northwestern University,
2145 Sheridan Road,
Evanston, IL 60208
e-mail: danielgarcia2018@u.northwestern.edu

Mojtaba Mozaffar, Huaqing Ren

Department of Mechanical Engineering,
Northwestern University,
2145 Sheridan Road,
Evanston, IL 60208
e-mail: MojtabaMozaffar2020@u.northwestern.edu

Jorge E. Correa

Department of Mechanical Science and Engineering,
University of Illinois Urbana-Champaign,
1206 W. Green St.,
Urbana, IL 61801
e-mail: jcorre20@illinois.edu

Kornel Ehmann

Department of Mechanical Engineering,
Northwestern University,
2145 Sheridan Road,
Evanston, IL 60208
e-mail: k-ehmann@northwestern.edu

Jian Cao

Department of Mechanical Engineering,
Northwestern University,
2145 Sheridan Road,
Evanston, IL 60208
e-mail: jcao@northwestern.edu

Fengqi You

Robert Frederick Smith School of Chemical and
Biomolecular Engineering,
Cornell University,
Ithaca, NY 14853
e-mail: fengqi.you@cornell.edu

1Corresponding author.

Manuscript received April 30, 2018; final manuscript received October 18, 2018; published online December 24, 2018. Assoc. Editor: William Bernstein.

J. Manuf. Sci. Eng 141(2), 021013 (Dec 24, 2018) (17 pages) Paper No: MANU-18-1285; doi: 10.1115/1.4041833 History: Received April 30, 2018; Revised October 18, 2018

Cyber-physical systems (CPS) enable unprecedented communication between product designers and manufacturers. Effective use of these technologies both enables and requires a new paradigm of methods and models to identify the most profitable and environmentally friendly production plans for a manufacturing network. The operating system for cyber-physical manufacturing (OSCM) and the paired network operations administration and monitoring (NOAM) software are introduced. These technologies guide our development of a mixed integer bilevel programming (BP) model that models the hierarchy between designers and manufacturers as a Stackelberg game while considering multiple objectives for each of them. Designers select and pay manufacturers, while manufacturers decide how to execute the order with the payment provided by the designer. To solve the model, a tailored solution method combining a decomposition-based approach with approximation of the lower level Pareto-optimal solution set is proposed. The model is applied to a case study based on a network of manufacturers in Wisconsin and Illinois. With the proposed model, designers and manufacturers alike can take full advantage of CPS to increase profits and decrease environmental impacts.

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Fig. 1

Cyber-physical manufacturing network framework: OSCM and NOAM

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Fig. 2

The designer (leader) proposes a set of payment distributions to the manufacturing network (followers). The manufacturers decide how to make the part under each payment distribution and return a manufacturing pathway to the designer.

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Fig. 3

Solution algorithm flowchart

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Fig. 4

Maps representing the manufacturers (green dots) in Wisconsin and Illinois considered in the case studies. The yellow star is the final demand location. Full network (left), Wisconsin manufacturers (middle), and Illinois manufacturers (right). All map images created in ArcMap [72].

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Fig. 5

Part designs considered in the case studies. Aluminum bearing bracket (left), and steel gearbox housing (right).

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Fig. 6

Case study results. The compromise solution is shown in yellow, and the corresponding Pareto-optimal curve for the manufacturers is also shown. The solution with the fewest GHG emissions is circled in green, and the solution with the highest profit is circled in amber.

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Fig. 7

Production plan details for the compromise solution

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Fig. 8

Production plan details for the solution with the highest profit

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Fig. 9

Production plan details for the solution with the fewest GHG emissions

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Fig. 10

Sensitivity analyses on machining processing rates (left) and machining costs (right). Percentages are given as deviations from nominal values.



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