Abstract
Greenhouse gas emission has become a recent global concern for green manufacturing. As product low-carbon design is an essential approach to achieve low-carbon manufacturing, which has a profound effect on the product carbon footprint, many researches have been focused on it in recent years with a result of valuable contributions. This paper is devoted to presenting a dynamic programmingbased approach to product low-carbon design. After product low-carbon design is characterized by a multi-stage decision process with interaction effects on each other in the product life cycle, a dynamic programming method is used to optimize the total carbon footprint of each stage while considering interaction effects of solutions at each stage in product life cycle. The low-carbon design of a cold heading machine is used to demonstrate the proposed methodology.
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Abbreviations
- g i (x i , x i+1):
-
carbon footprint mapping function of x i and x i+1
- f k (x k ):
-
sum of carbon footprint from the k th to the last stage
- s ij :
-
design states in set S i
- u i (x i ):
-
control variables of x i at the i th stage
- v i (x i , u i ):
-
carbon footprint under the consideration of x i and u i
- x i :
-
state variables set in S i at the i th stage
- x ij :
-
state variable set in the design state s ij
- x ij p :
-
design variables of the p th solution in s ij at the i th stage
- C i :
-
carbon emission factor of the i th activity
- D i (x i ):
-
control variables set of x i at the i th stage
- E a :
-
carbon footprint at the acquisition of raw materials stage
- E c :
-
carbon footprint in the product life cycle
- E i (s ik ):
-
carbon footprint function of s ik at the i th stage
- E m :
-
carbon footprint at the manufacturing stage
- E r :
-
carbon footprint at the recycle and disposal stage
- E t :
-
carbon footprint at the transportation stage
- E u :
-
carbon footprint at the usage stage
- G k :
-
emission of the k th GHG
- GWP k :
-
global warming potential of the k th GHG
- M i :
-
consumption of the i th activity
- S i :
-
design state set at the i th stage
- T k (x k , u k ):
-
transition function with k stages to go
- U k (x k , x k+1):
-
control law describing x k and x k+1
- X :
-
overall state variables of different stages
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He, B., Huang, S. & Wang, J. Product low-carbon design using dynamic programming algorithm. Int. J. of Precis. Eng. and Manuf.-Green Tech. 2, 37–42 (2015). https://doi.org/10.1007/s40684-015-0005-z
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DOI: https://doi.org/10.1007/s40684-015-0005-z