<｜begin▁of▁sentence｜>### Instruction:
In the context of optimizing a production system, consider an assembly line represented as a network with stations connected in a loop. The network has specific points of connection that form a cycle: station 1 to station 2, station 2 to station 3, station 3 to station 4, station 4 to station 5, and back from station 5 to station 1. 

Your task as an industrial engineer is to analyze this cycle for any critical connections that, if interrupted, would isolate a part of the loop, potentially causing inefficiency. Specifically, you need to identify each 'local bridge' within this network—a term referring to an edge whose removal would increase the shortest path length between its endpoints. For each local bridge found, determine the 'span', which measures the extent of its impact on the system by quantifying the new shortest path length between the previously connected nodes. 

Use NetworkX, an appropriate analytical tool for network analysis, to carry out this examination and assessment. This information will be crucial in evaluating the robustness of the assembly line and ensuring the minimization of bottleneck risks in production flow.
### Response:
import networkx as nx

# Create an undirected graph G
G = nx.Graph()
G.add_edges_from([(1, 2), (2, 3), (3, 4), (4, 5), (5, 1)])

# Use local_bridges to find edges that are local bridges
# and also compute the span of these bridges.
local_bridges_with_span = list(nx.local_bridges(G, with_span=True))

print('Local bridges with span:', local_bridges_with_span)
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