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The development of a practical pipe auto-routing system in a shipbuilding CAD environment using network optimization


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An automatic pipe routing system is proposed and implemented. Generally, the pipe routing design as a part of the shipbuilding process requires a considerable number of man hours due to the complexity which comes from physical and operational constraints and the crucial influence on outfitting construction productivity. Therefore, the automation of pipe routing design operations and processes has always been one of the most important goals for improvements in shipbuilding design. The proposed system is applied to a pipe routing design in the engine room space of a commercial ship. The effectiveness of this system is verified as a reasonable form of support for pipe routing design jobs. The automatic routing result of this system can serve as a good basis model in the initial stages of pipe routing design, allowing the designer to reduce their design lead time significantly. As a result, the design productivity overall can be improved with this automatic pipe routing system.
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Int. J. Naval Archit. Ocean Eng. (2013) 5:468~477
The development of a practical pipe auto-routing system in
a shipbuilding CAD environment using network optimization
Shin-Hyung Kim1, Won-Sun Ruy2 and Beom Seon Jang3
1R&D Institute, Daewoo Shipbuilding & Marine Engineering Co., Korea
2Department of Naval Architecture and Ocean Engineering, Chungnam National University, Daejeon, Korea
3Department of Naval Architecture and Ocean Engineering, Seoul National University, Seoul, Korea
ABSTRACT: An automatic pipe routing system is proposed and implemented. Generally, the pipe routing design as a
part of the shipbuilding process requires a considerable number of man hours due to the complexity which comes from
physical and operational constraints and the crucial influence on outfitting construction productivity. Therefore, the
automation of pipe routing design operations and processes has always been one of the most important goals for im-
provements in shipbuilding design. The proposed system is applied to a pipe routing design in the engine room space of
a commercial ship. The effectiveness of this system is verified as a reasonable form of support for pipe routing design
jobs. The automatic routing result of this system can serve as a good basis model in the initial stages of pipe routing
design, allowing the designer to reduce their design lead time significantly. As a result, the design productivity overall
can be improved with this automatic pipe routing system.
KEY WORDS: Pipe routing; Automatic routing; Shipbuilding customized Computer Aided Design (CAD)-based system.
The pipe routing design as it pertains to shipbuilding is usually performed during the basic and detail design stage after the
creation of the pipe & instrument diagram (P&ID), which contains connection data between equipment in the preliminary de-
sign stage. Generally, this type of pipe routing design is accomplished by a highly experienced designer who can consider not
only the complex shapes and connections of each piece of equipment but also the issues of space availability, material costs,
accessibility, and suitability for installation. The amount of pipe routing work is nearly a half of all outfitting design work at that
stage. In addition, the quality of the pipe routing design effort has a direct effect on the subsequent construction design stage, on
which the total material and construction cost strongly depends (Shao et al., 2009), just like other design work in the detail des-
ign stage of shipbuilding.
When we consider the Just-In-Time (JIT) production scheme in the area of shipbuilding, not only the quality of the routing
design which guarantees an accurate amount of raw materials for pipe construction but also the on-time delivery of the routing
result to the subsequent design stage are very important in JIT production (Koenig et al., 2002). Moreover, every ship has diffe-
rent specifications, except for a few sister ships. Therefore, every ship needs to be designed based on individual specifications.
Consequently, the ratio of the design cost to the total building cost is significantly higher in the shipbuilding industry. Therefore,
pipe-routing design automation schemes with feasible quality results that are delivered on time have been key issues to those
seeking shipbuilding design process improvements.
Corresponding author: Won-Sun Ruy
Int. J. Naval Archit. Ocean Eng. (2013) 5:468~477 469
Routing optimization problem
The pipe routing optimization problem should satisfy the various constraints. Park (2002) and Qian et al. (2008) catego-
rized these constraints into the two groups of restrictive constraints and quantifiable constraints. Some of them are discussed
Physical Constraints
The pipe routing should avoid physical obstacles and connect to the proper equipment.
Economic Constraints
The pipe routing should minimize the total material and fabrication cost by reducing pipe lengths and number of bent parts
and by increasing shared pipe supports.
Operational Constraints
The pipe routing should consider the proper operations like valve accessibility and clearance from some equipment for safety.
Physical and operational constraints are restrictive while economic constraints are quantifiable. Therefore, pipe routing opti-
mization seeks to find the best path from an economic point of view among the set of feasible paths restricted by physical and
operation constraints.
Related works
Various types of optimization algorithms have been applied to the pipe routing problem. In an early example, the Maze
algorithm was proposed by Lee (1961). This algorithm divides a space into cells and labels and chooses the next cell until the
target cell is reached. Hightower (1969) proposed the escape algorithm, also known as the line-search algorithm. This is shown
in Fig. 1.
Fig. 1 The escape algorithm proposed by Hightower.
Some network-based algorithms can be used to solve various problems (Nicholson, 1966; Ando and Kimura, 2011). In
network-based optimization, each vertex vi denotes the junction of a pipe where a bent pipe part can be placed; the edge eij
between the vertexes vi and vj denotes a straight pipe part with cost cij. Fig. 2 shows a graph representation of this.
Fig. 2 A graphic representation of pipe routing between equipment.
470 Int. J. Naval Archit. Ocean Eng. (2013) 5:468~477
G = (V, E, C) (1)
In Eq. (1), V denotes the set of vertices, E is the set of edges, and C denotes the cost. The pipe routing optimization
problem is to find the shortest path between the start vertex s and the end vertex f in the graph G in Fig. 2. These traditional
routing algorithms with graph representation are generally based on what is known as the ‘cell decomposition’ approach. The
cell decomposes the problem space containing the start and end points of the target equipment into cubic cells to reduce the
problem size and represent the pipe path through the sequencing of connected cells. A good example was given by Asmara
and Nienhuis (2006). Ito (1999), Park (2002) and Ando and Kimura (2011) also applied for this approach to represent the pipe
routing path.
To find the global optimum route path, several efforts have been made. Examples include an evolution-based algorithm
such as a genetic algorithm (Ito, 1999; Ikehira et al., 2005; Kimura, 2011) and an ant colony optimization scheme (Xiaoning et
al., 2006, 2007). The target of route optimization is usually the minimum cost of the pipe routing path. In many studies, the cost
consists of the pipe length cost and the cost of all bent parts, which require expensive bending fabrication or elbow fitting
processes. Park (2002), Kimura and Ikehira (2009) and Ando and Kimura (2011) also considered the operability costs such as
the costs incurred to determine valve locations and safety clearances.
Much research has been done since the 1970s. However, there are still limitations when attempting to make use of it to
create a fully automatic routing system for actual shipbuilding design work. As discussed by Missuta et al. (1986) and Kang et
al. (1999), the main reason for this is that pipe routing algorithms generally do not consider the knowledge and the preference of
the designer suitably as required in the actual design work. This type of limitation is not a matter purely related to the optimiza-
tion algorithm itself. It is rather a matter of knowledge representation during the design automation process (Sriram et al., 1989).
Therefore, the knowledge representation in the design has become a more important issue in the area of design automation.
Moreover, from a practical point of view, it is also important that the implemented routing algorithm can be utilized effectively
in an actual shipbuilding design environment. Some pipe routing algorithms are evaluated in the form of a design support
package program; these have a neutral data interface to a CAD system for practical use (Sandurkar and Chen, 1999; Asmara
and Nienhuis, 2006; Paulo and Lobo, 2009). They use text-based neutral files such as standard tessellation language (STL) for
interfacing data to the CAD system. After constructing the pipe network, Ruy et al. (2012) studied a hole plan system recently.
Network based routing algorithm
The pipe routing algorithm developed in this research is based on a network optimization algorithm. The target space inclu-
ding target equipment is divided into non-uniform cells. The graph is constructed considering the route constraints of the fitness
of the space, pipe length and bending. This graph represents the pipe route in the target space. An optimum route path can then
be obtained by a general minimum path-finding algorithm.
Cell decomposition
Cell decomposition is useful strategy for reducing the problem size. Cell decomposition divides a continuous target space on
which pipe lines and equipment are positioned into discrete cells. The edges and vertexes of the divided cubic cells can represent
the edges and vertexes of the graph, which connect the start and end points of the routing path. In this case, the network based
routing algorithm can be practically applied to these graphs in a reduced problem space. One of the major issues associated with
this cell-division method is the number of cells. A larger number of cells generally guarantees a better route path but takes more
time to calculate. Therefore, the number of cubic cells should be controlled considering the characteristics of the problems.
A pipe path along the wall or ceiling structures is preferred due to the issue of space availability after the routing process. This
indicates that this near wall space has higher fitness than other spaces. In this research, the target space is divided non-uniformly
according to the degree of the special fitness. A space with higher fitness is divided into smaller cubic spaces. The vertexes and
edges of cubic cells can be used as the vertexes and edges of the graph which contains a candidate route path. Thus, the space with
higher fitness has denser cubic cells and more candidate routes. In contrast, the space around passageways or equipment which
may require some distance is divided into larger cubic cell. This cell-division strategy is a part of the consideration of routing de-
sign practices pertaining to space fitness. Fig. 3 shows non-uniformly divided cells in the target space. Each cubic cell can have its
own fitness factor, and this fitness factor has an effect on the cost decision (value Cij) between the vertices in Fig. 2.
Int. J. Naval Archit. Ocean Eng. (2013) 5:468~477 471
Graph construction
As mentioned above, the vertices and edges of a cubic cell in the target space could be the vertices and edges of the graph.
Though the numbers of vertices and edges are reduced by cell decomposition, it is still possible for the graph to be more sim-
plified while maintaining a feasible route path in the target space. To construct a simpler graph, a vertex construction strategy is
developed. It is essentially based on the escape algorithm proposed by Hightower (1969). The original escape algorithm is fast
and simple, producing one solution directly, as shown in Fig. 3, but it cannot guarantee a solution (Kai-jian and Hong-e, 1987).
The vertex construction method of this system uses a strategy similar to that of the escape algorithm to expand the route graph.
An edge runs like a beam until it encounters the side of an obstacle or a wall boundary of the target space, at this point it
branches off in another direction, as shown below in Fig. 4.
Fig. 3 Non-uniformly divided cells. Fig. 4 A graph construction by the vertex branching.
A branch also could be made during edge runs when it meets the edges of cubic cells in the target space. Therefore, a dense
area with smaller cubic cells in the target space has more candidate vertices; i.e., it is a preferable space with more candidate
The vertices are located on the corners of non-uniformly divided cubic cells and are connected by edges which have their
own weight factor, as shown in Fig. 5. Basically, a network graph is characterized only by the vertices and weighted edges be-
tween them. In terms of this traditional definition of a graph, the two graphs in Fig. 6 are equivalent. The relative location of the
vertices makes no difference while the connection is maintained.
Fig. 5 Vertex located on the corner of a cubic cell.
472 Int. J. Naval Archit. Ocean Eng. (2013) 5:468~477
However, the vertex and edge connection of the graph applied in this system needs to have a topological meaning, as the
graph should represent the physical pipe routing. An edge connection running in the target space corresponds to the pipe
routing and the vertex on the corner of a cubic cell also contains location information. In this new definition, the equivalent
graphs in Fig. 6 are not the same. The figure on the left is a straight pipe and the right side is a bent one. This bending route
needs the pipe-bending or an additional elbow fitting pipe part, which generally increases the cost compared to a straight
pipe. Therefore, this type of bent pipe should be considered as a cost factor in the route optimize algorithm. To consider a
bent pipe such as this one in the graph, a vertex split strategy is introduced. This strategy simply removes the ambiguousness
of vertex connections.
Fig. 6 Equivalent graphs.
The left figure in Fig. 7 is a part of a route graph with a directional edge, showing each weight factor. In this graph, route A-
B-D is a straight route while route C-B-D is a bent one. However, the edge between B and D also has a single weight factor of 5;
it can be part of A-B-D and part of C-B-D at the same time. Therefore, a pipe bent in this manner is not suitable for this type of
graph structure. The right graph of Fig. 7 illustrates the vertex split strategy. Vertex B is split into B and B’ with a bending pe-
nalty weight factor of 6. The graph is reconstructed with route A-B-D and route C-B’-D. Then, the bending of the route could
be considered without ambiguity.
A vertex with two or more incoming edges and outgoing edges should be split when outgoing edges can be used in a diffe-
rent route path, straight or bent simultaneously. In the case shown in Fig. 8, there are two split vertices. Practically, in a 3D cu-
bic cell space where the number of neighbor vertices cannot exceed six, the number of split vertices is at most three in a case
with three incoming edges and three outgoing edges.
Fig. 7 Vertex split 1. Fig. 8 Vertex split 2.
Fig. 8 shows another example of a vertex split. This vertex split strategy expands the route graph for mapping onto an actual
pipe route in the target space considering the relative locations of the neighbor vertices. The weight factor of an edge is pro-
portional to the penalty factor expressed by Eq. (2), which is evaluated according to the distance and space factor of the edge
location and the bent condition.
Penalty factor = distance * distance factor + bending factor + space factor (2)
Eq. (2) accounts for the component of the weight factor, the distance is the actual distance between two vertices, and the
distance factor adjusts for the effect of the distance in the weight factor. The bending factor has a positive value when an edge is
a part of a bent route. On the other hand, the space factor shows the fitness of the space; here, a smaller value means better
fitness. For example, a cubic cell located near equipment, a wall or a ceiling has a smaller space factor because it is a preferable
Int. J. Naval Archit. Ocean Eng. (2013) 5:468~477 473
Routes A-B and C-D-E-F in Fig. 9 have the same distance. If the space factor (a route along wall is recommended generally
recommended) is more important than the bending factor, route C-D-E-F would be chosen; otherwise, route A-B with less ben-
ding would be selected by the optimization algorithm.
Fig. 9 Bending route along a wall side.
Shortest path-finding algorithm
After the vertex distribution and weight decision of the edges, the path-finding algorithm to find the shortest path for the
graph can be applied. The shortest path of the graph may be the best pipe route because the weights of the edges represent the
total cost of the route, including the materials, fabrication cost, operation cost, and other factors. The graph constructed with
these rules is a directional and positive single graph. Therefore, Dijkstra’s algorithm can be applied. For the simplest implemen-
tation, it is known that the running time of Dijkstra’s algorithm is in O(V2). Therefore, the construction of the simpler graph G is
an important process in the development of this automatic routing scheme. The non-uniform cell decomposition and the vertex
location strategy can reduce the size of the graph considerably as well.
Design practice management
The sizes of the non-uniformly divided cubic cells and the edge weight factors are all based on the practices of the pipe
routing designer. This practice should be represented and controlled explicitly in the system to be used by a designer who may
not have enough pipe routing experience or who wants to accomplish the pipe routing tasks quickly.
In this development, the design practice is basically represented as a parameter. Some aspects, such as the wall side pre-
ferences, can be represented by a parameter set that affect the fitness of the space near the side wall, while other practices such
as grouping pipes on the same pipe support cannot easily be represented by a parameter set. Therefore, the former is represented
in the form of a parameter set and the latter remains as work needing to be done by the designer, who can review and modify
the automatic routing result.
The parameters are classified into two groups, one for cell decomposition and the evaluation of the space fitness, and the
other for the construction of an efficient graph. The designer can choose a pre-defined parameter set or modify each parameter
depending on their preferences. It should be noted that this approach cannot cover all tasks needed for the full automation of the
pipe routing routine. Further studies are necessary to accomplish this. Note that a rapid design cycle including automatic routing
and route modification, however, can still be practically accomplished.
System configuration
The automatic routing system consists of three modules. The first module is for input data creation, the second one is for
routing optimization, and the third one is for the resulting pipe model and for its modification. The input data module and pipe
model creation module are embedded in the CAD system Tribon M3 of AVEVA Marine Design and Engineering, while the
routing optimization module is a standalone program.
This CAD system provides an application program interface (API) written in Python script. Therefore, the main structure of
this automatic routing system is written in Python and the mathematic library and GUI are written in C++. These two embedded
474 Int. J. Naval Archit. Ocean Eng. (2013) 5:468~477
modules exchange data with the CAD system directly via the API and the standalone optimization module receives and sends
data via the XML file format. Fig. 10 presents the configuration of the automatic routing system.
Fig. 10 Configuration of the automatic pipe routing system.
Input data creation module
The input data creation module obtains the equipment connection data from the P&ID and the equipment property data
from the CAD database. It also has a user input interface with which the designer can input or modify the space and equipment
data. This module generates cell decomposition data and equipment data and sends this data to the routing optimization module.
The equipment volume is simplified as a cuboid and the locations of the pipe connections on the equipment are modified de-
pending on the direction of the flow for practical reasons. The target space is divided non-uniformly according to the space
fitness and the equipment volume is then subtracted. Fig. 11 shows the input data creation module integrated in the CAD
system. The designer can select and change the parameter set as they wish, and this selected parameter set governs the routing
Fig. 11 Integrated input data module.
Int. J. Naval Archit. Ocean Eng. (2013) 5:468~477 475
Route optimization module
The route optimization module divides the target space non-uniformly and constructs a network graph with the vertex and
edges of the cubic cell. Fig. 12 shows an example of a constructed route path graph with start point A and end point B.
Fig. 12 A example of a constructed graph.
Pipe model creation module
This module creates an actual pipe model in the CAD system with the routing result from the optimization module and the
pipe specification data from the input data module. This module runs on the pipe modeling CAD system. Thus, the designer can
modify or confirm the pipe model in the same user environment.
This module also generates the pipe model data for the following stage of production, including the design and preparation
stages. One of the most important types of model data is the bill of materials (BOM), which contains information about the raw
materials and the construction processes. The BOM of this system would be accurate and on time because it is based on the
accurately and quickly created pipe model. This feature of the BOM plays an important role in the JIT production processes.
Route optimization result
This automatic routing system is applied to pipe routing in a ship engine room space. The volume of the engine and some
equipment in the target space are shown in Fig. 13.
Fig. 13 Engine room CAD model.
476 Int. J. Naval Archit. Ocean Eng. (2013) 5:468~477
Fig. 14 A graph construction in an engine room and the result of automatic routing from A to B.
The left side in Fig. 14 shows a simplified graph of the equipment volume and candidate pipe routing. The graph is cons-
tructed according to design as represented by the parameters. The right side in Fig. 14 shows the routing result from the start A
to end B points.
This system can produce a practical pipe-routing result, showing the amount of pipe material and the approximate route
path information. This type of information is useful during the basic design stage. However, this auto-routing pipe model
should be checked whether detailed pipe routing practices and rules are considered. These considerations include the air poc-
kets, the thermal expansion, the alignment of support structures, and the valve accessibility, for instance, at the detail design
stage. Moreover, some path modification is necessary to utilize the extra space caused by the cuboid simplification of the
equipment volume and to reduce the degree of complexity in the narrow spaces through the use of diagonal piping and bent
pipes instead of elbow fittings.
In an actual pipe routing job in a shipbuilding outfitting design, there are numerous pipe lines in a single work area (e.g., a
block, a room); moreover, there are not only simple pipes which have single start and end point but also pipes with bypasses or
branches. This system can handle multiple pipes via the input data creation module, and the automatic pipe routing is done
sequentially. Therefore, the sequence set by the designer in the input data creation module characterizes the total routing result
of multiple pipes. And this system can handle only simple pipes, the pipe lines with bypass or branch should be divided into
simple one in the input data creation module.
A practical automatic pipe routing system is developed and integrated in a shipbuilding CAD system. The pipe routing algo-
rithm is based on graph optimization. A graph containing candidate route paths is constructed on a target space composed of
ununiformly divided cubic cells. The design preferences are represented and managed by parameters.
This system is applied to the engine room area of a commercial ship. The result shows that the system cannot always pro-
duce the best pipe route initially. However, the designer can recalculate the result easily and quickly with a new parameter set to
obtain a satisfying result in the integrated CAD environment. However, there are several limitations of this system. These are
mainly related to the management of design knowledge and practices which are rarely expressed by a simple parameter. How-
ever, the routing result can serve as a good basis for data generation tasks such as the creation of a BOM and for detailed pipe
routing with slight modifications. As a result, the lead time of the basic pipe design stage can be reduced and more accurate and
earlier product model data can be produced. These features of the system can improve the productivity of outfitting design and
construction in the shipbuilding industry.
Ando, Y. and Kimura, H., 2011. An automatic piping algorithm including elbows and bends. International Conference on
Computer Applications in Shipbuilding (ICCAS). Trieste, Italy, 20-22 September 2011, 3, pp.153-158.
Asmara, A. and Nienhuis, U., 2006. Automatic piping system in ship. International Conference on Computer and IT Appli-
cation (COMPIT). Delft, Netherlands, 8-10 May 2006.
Int. J. Naval Archit. Ocean Eng. (2013) 5:468~477 477
Hightower, D.W., 1969. A solution to line routing problems on the continuous plane. Proceedings of Sixth Annual Design
Automation Conference. IEEE, pp.1-24.
Ikehira, S., Kimura, H. and Kajiwara, H., 2005. Automatic design for pipe arrangement using multi-objective genetic al-
gorithms. International Conference on Computer Applications in Shipbuilding (ICCAS). Busan, Korea, 23-26 August
2005, 2, pp.97-110.
Ito, T., 1999. A genetic algorithm approach to piping route path planning. Journal of Intelligent Manufacturing, 10,
Kai-jian, S. and Hong-e, Z., 1987. Efficient routing algorithm. Computer- Ai+ded Design, 19(7), pp.375-379.
Kang, S., Myung, S. and Han, S., 1999. A design expert system for auto-routing of ship pipes. Journal of Ship Production,
15(1), pp.1-9.
Kimura, H. and Ikehira, S., 2009. Automatic pipe arrangement design considering operationality valve operationality. In-
ternational Conference on Computer Applications in Shipbuilding (ICCAS). Shanghai, China, 1-3 September 2009, 2,
Kimura, H., 2011. Automatic designing system for piping and instruments arrangement including branches of pipes. Inter-
national Conference on Computer Applications in Shipbuilding (ICCAS). Trieste, Italy, 20-22 September 2011, 3,
Koenig, P.C., Narita, H. and Baba, K., 2002. Lean production in the Japanese Shipbuilding Industry. Journal of Ship pro-
duction, 18(3), pp.167-174.
Lee, C.Y., 1961. An algorithm for path connections and its applications. IEEE Trans on Electron Computers, 10(3),
Mitsuta, T., Kobayashi, Y., Wada, Y., Kiguchi, T. and Yoshinaga, T., 1986. A knowledge-based approach to routing pro-
blems in industrial plant design. Proceedings of the Sixth International Workshop Expert System and Their Applica-
tions. Avignon, France, March 1987, pp.237-256.
Nicholson, T.A.J., 1966. Finding the shortest route between two points in a network. The Computer Journal, 9(3), pp.275-
Park, J.H., 2002. Pipe-routing algorithm development for a ship engine room design. Ph.D. Washington University.
Paulo, T.M. and Lobo, V.J.A.S., 2009. A Tool for Automatic Routing of Auxiliary Circuits in Ships. Portuguese Confer-
ence on Artificial Intelligence (EPIA). Aveiro, Portugal, 12-15 October 2009, pp.77-86.
Qian, X.L., Ren, T. and Wang, C.E., 2008. A survey of pipe routing design. Control and Decision Conference, Chinese IEEE.
Yantai, Shandong, China, 2-4 July 2008, pp.3994-3998.
Ruy, W.S., Ko, D.E. and Yang, Y.S., 2012. The implementation of the integrated design process in the hole-plan system.
International Journal of Naval Architecture and Ocean Engineering, 4(4), pp.353-361.
Sandurkar, S. and Chen, W., 1999. Gaprus-genetic algorithm based pipe routing using tessellated objects. Journal of Com-
puters in Industry, 38(3), pp.209-223.
Shao, X.Y., Chu, X.Z., Qiu, H.B., Gao, L. and Yan, J., 2009. An expert system using rough sets theory for aided concept-
tual design of ship’s engine room automation. Expert Systems with Application, 36(2), pp.3223-3233.
Sriram, D., Stephanopoulos, G., Logcher, R., Gossard, D., Groleau, N., Serrano, D. and Navinchandra, D., 1989. Know-
ledge-based systems applications in engineering design: Research at MIT. AI Magazine, 10(3), pp.79-96.
Xiaoning, F., Yan, L. and Zhuoshang, J., 2006. The ant colony optimization for ship pipe route design in 3D space. World
Congress on Intelligent Control and Automation (WCICA). Dalian, China, 21-23 June 2006, pp.3103-3108.
Xiaoning, F., Yan, L. and Zhuoshang, J., 2007. Ship pipe routing design using the ACO with iterative pheromone updating.
Journal of Ship Production, 23(1), pp.36-45.
... As most of these algorithms work for some simple problems, they are challenging to implement in the design process in the industry. For these reasons, some studies have developed an automatic pipe design system to solve these fundamental problems, and some useful results for the ship design industry were obtained (Asmara, 2013;Kim et al., 2013). ...
... An automatic pipe model generation method based on the hull structural model was also proposed (Roh et al., 2007), which automatically updated the pipe route design as the hull structural design was changed. An automatic pipe routing system was proposed for ship design (Kim et al., 2013), which utilized a graph-based design domain and Dijkstra's algorithm to find the shortest pipe route. In addition, this system exported the routing results of the algorithm to the CAD system. ...
... Generation of a parametric pipe model in a CAD system (Roh et al., 2007) Automatic design system Implementation of the automatic pipe route design module into a CAD system (Kim et al., 2013) Automatic design system Prototype software package integrated with commercial software (Asmara, 2013) Automatic layout routing system Integration of the layout route system with CAD system and FE software ( Van der Velden et al., 2007) Aircraft industry ...
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Although many routing algorithms have been developed, it is difficult for designers in the automotive industry to adopt them because of the complicated preliminary steps that are required. This study presents a systematic framework for generating the routing layout of the tubes, hoses, and cable harnesses in a commercial truck. The routing layout design problem in a commercial truck is analysed and defined. For routing operations, a sequential graph-based routing algorithm is employed to rapidly provide a routing solution. Because a reference routing layout design does not exist in most engineering problems, a cell-based genetic algorithm combined with a modified maze algorithm is employed to generate a reference design. To consider the clamping condition of the routing components, a new fitness function in the genetic algorithm is implemented. The numerical study shows that the proposed routing algorithm provides a better reference routing layout design than the conventional algorithm. The proposed automatic design system was applied to the routing layout design problem of a commercial truck. It was demonstrated that the proposed framework satisfies all industrial practitioners’ functional requirements and provides a systematic method of solving the routing layout design problem, considering all its characteristics.
... Escape graphs are widely used in the field of rectilinear path planning [34]. From these graphs, KIM [54] simply proposed to directly apply DIKJSTRA's algorithm to solve the single pipe routing problem. In some applications, engineering or safety considerations may require to route pipes close c Airbus Defence and Space SAS -"This document and the information it contains are property of Airbus Defence and Space. ...
In recent decades, the demand for fixed and mobile communication services as well as over-the-air television, digital broadcasting or broadband Internet has raised exponentially. To meet these growing needs, telecommunication satellite operators must continually increase the capacity of their satellites, which leads to a significantly higher number of components and connections inside the new satellite payloads. Among these connections, the waveguides are pipes with a rectangular section which carry useful electromagnetic signals between two components of the satellite payload. However, these signals suffer from on-line radio-frequency losses during their carriage along the waveguides. It results that the design of the waveguide harness plays a crucial role on the performances of the satellite. This PhD thesis proposes optimisation methods for the detailed routing of waveguides, reducing their lengths while taking into account the design constraints of the radio-frequency harness.The studied Waveguide Routing Problem, introduced in Part I, consists in connecting an input configuration to an output configuration by using a waveguide composed of a succession of straight sections and bends (Chapter 1). It considers several non-standard features for classical Pipe Routing approaches (Chapter 2) such as dealing with a set of bends restricted to a catalogue that can contain both orthogonal and non-orthogonal bends, or with pipes of rectangular section, which makes the pipe orientation important.As a first step, in Part II, all routing space constraints are ignored in the Free Waveguide Routing Problem (Chapter 4) and two resolution approaches are introduced. The first formulation uses Mixed Integer Linear Programming and is based on the enumeration of the possible orientations for the waveguide segments (Chapter 5). Because of the poor performances of this approach on industrial instances, another formulation adapted to the Informed Search Algorithms is proposed using a notion of routing plan that describes a partially routed waveguide (Chapter 6). The feasibility of a plan is then evaluated using Linear Programming while the space of plans can be explored with algorithms like Weighted A* or Beam Search. To do so, two different heuristics are proposed to estimate the distance to the destination using Euclidean distance and minimal bend combinations. With the best heuristic, which has been shown to be consistent, this second formulation clearly outperforms the MILP approach, solving most instances within a second (Chapter 7).In a second phase, in Part III, the Constrained Waveguide Routing Problem, which consists in routing a single waveguide within a restricted three-dimensional space that may contain obstacles, is studied. To model these spatial constraints, the routing space is seen as a three dimensional continuous space divided into non-regular convex cells that avoid obstacles (Chapter 8). Then, both resolution methods introduced for the Free Waveguide Routing Problem are extended. The channel of cells to be traversed is first introduced as a set of new decision variables in the MILP model (Chapter 9) and in the Search Problem formulation. Furthermore, several heuristics based on relaxed trails in the routing space are proposed to improve the estimations by considering the space constraints and obstacles (Chapter 10). While the MILP approach tested is not able to provide solutions in a reasonable time, the Informed Search Algorithms solve small and medium industrial instances with realistic waveguides within a few minutes (Chapter 11).These approaches have been integrated into software tools for the industrial design of waveguides and have successfully reduced the time of design for the radio-frequency harness.
... 2D routing algorithms were developed for VLSI circuits with fixed layouts based on the Manhattan distance and its variants [91]. Other 3D routing applications include aero-engine externals routing [112,113], ship pipe routing [114][115][116], electrical harnesses routing for vehicles [117], chemical plant pipe routing [85], electrical wire routing in buildings [118,119], field-programmable gate array (FPGA) design [120], piping for airbus landing gear bay [121], unmanned aerial vehicle navigation [89], vehicle routing [107], and robotic path planning [90,122]. ...
Three-dimensional spatial packaging of interconnected systems with physical interactions (SPI2) design plays a vital role in the functionality, operation, energy usage, and lifecycle of practically all engineered systems, from chips to ships. SPI2 design problems are highly-nonlinear, involving tightly constrained component placement, governed by coupled physical phenomena (thermal, hydraulic, electromagnetic, etc.), and involve energy and material transfer through intricate geometric interconnects. While many aspects of engineering system design have advanced rapidly in the last few decades through breakthroughs in computational support, SPI2 design has largely resisted automation, and in practice requires at least some human-executed design steps. SPI2 system reasoning and design decisions can quickly exceed human cognitive abilities at even moderate complexity levels, thwarting efforts to accelerate design cycles and tackle increasingly complex systems. Existing design methods treat pieces of the SPI2 problem separately without a fundamental systems approach, are sometimes inefficient to evaluate various possible designs and present barriers to effective adoption in practice. This article explores a vision of a holistic SPI2 design approach needed to develop next generation automated design methods capable of rapidly producing viable SPI2 design candidates. We review several technical domains related to holistic SPI2 design, discuss existing knowledge gaps and practical challenges, examine exciting opportunities at the intersection of multiple domains that can enable comprehensive exploration of SPI2 design spaces, and present one viable two-stage SPI2 design automation framework. Holistic SPI2 design opens up a new direction of high industrial and societal relevance for the design research community.
... In response to the nature of the construction industry, the interests of various companies are intertwined, which causes confusion in process control and supervision as well as frequent design changes [8]. In particular, construction equipment has a high frequency of design changes in response to design changes in the previous processes, and the connection relationship could be complicated depending on the shape of the structure [9]. In addition, since high professionalism is required to understand the MEP structure only with blueprints, installation is often different from the original design when a non-specialist participates in the work. ...
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This paper introduces a modified A* pathfinding algorithm that can be used in building Mechanical Electronic Plumbing (MEP) path design by revising nodes selection process and post-processing. The pathfinding algorithm is used when a computer calculates the optimal path in a given space by algorithmizing how humans intuitively calculate the optimal path. As construction technology is gradually advancing, buildings with large and complex internal structures are increasing, so there is a need to automatically optimize existing design methods that rely on human intuition for a more efficient design. In the case of building MEP design, it is time and money consuming to design paths since they are complexly arranged throughout the building, and designs are frequently changed in response to the nature of the construction industry, where construction errors are frequent. Therefore, an MEP path design optimization module, MEPAutoroute, was developed by implementing a modified A* pathfinding algorithm to solve these problems. Algorithm was applied to seven different exemplary structures with MEP equipment, and the results are analyzed to determine its efficiency.
... e improved maze algorithm and improved genetic algorithm are used for automatic routing in grid space proposed by [10]. is research provides a way of multibranch pipe routing under certain conditions. Taking the Dijkstra algorithm as the basic algorithm, a special evaluation method is designed to comprehensively evaluate the route length, the number of bends, and constraints, so as to realize the selection of the optimal route [11]. For this research, all nodes and their parameters must be defined before the algorithm runs. ...
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The pipeline layout design of nuclear power plant is to find the optimal route to meet the objectives and constraints in the 3D routing space. However, due to the intensive equipment and complex structure of the nuclear power plant, various types of pipeline systems, complex layout constraints, and a large number of pipelines, even for experienced designers, pipeline layout is a difficult and time-consuming task. In order to solve the problem of the automatic layout of pipeline in 3D routing space of nuclear power plant, a pipeline automatic routing method combining Dijkstra algorithm in large space and improved A ∗ algorithm in local space is proposed in this paper. Firstly, the method identifies the key vertices of each room in the nuclear power plant, constructs the topological routing map, and determines the preliminary passage area of the pipeline through the traditional Dijkstra algorithm. Secondly, the space of the layout area is divided into 3D grids, and then the items in the area are identified and preprocessed. Finally, the 3D pipeline routing environment is established through AABB-OBB hybrid collision detection technology. On this basis, the improved method of A ∗ evaluation function is given to satisfy the pipeline layout constraints and improve the search efficiency. Through experiments, the effectiveness of this method is proved. This method can quickly and automatically route the nuclear power pipelines that meet the requirements of the engineering, which greatly improves the efficiency of 3D pipeline layout design for the nuclear power plant.
... Asmara [22] developed a pipe routing framework for detailed ship pipe design. Kim et al. [23] developed a pipe routing system in CAD environment using network optimization. Moreover, some researchers focus on solving SPRD with swarm intelligent algorithms. ...
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goal of ship pipe route design (SPRD) is to seek the near-optimal paths that meet various constraints and objectives. Due to the complex construction of routing space, diverse piping constraints, and the large number of pipes, SPRD is one of the most difficult and time-consuming tasks even to a skilled pipe designer. This paper proposes automatic approaches for solving SPRD with A* algorithm and genetic algorithm (GA). Firstly, by simplifying the equipment and decomposing the routing space into grids, the mathematical model of SPRD is created. Then, the improved A* algorithm (A*-Router) for single pipe routing is introduced. The evaluation function, auxiliary tables and algorithm framework of A*-Router are presented. To obtain high-quality and diverse layouts, the improved GA (A*-GA-Router) is formulated by A*-Router and the connection-points strategy. Several new genetic operators of A*-GA-Router are de-signed to improve the routing performance. For multiple pipes routing, the novel algorithm (Multi-Pipes-Router) which calls A*-GA-Router internally is put forward. It arranges pipes according to the specified routing sequence and can produce parallel layout under the function of GA optimization and connection-points strategy. To cope with branch-pipe routing widely existing in engineering, a new pipe router (Branch-Pipe-Router) is put forward using a modified Steiner Tree framework in combination with the pro-posed single pipe routing algorithms. Compared with the traditional methods based on coevolution, it is more versatile and can effectively balance the layout quality and time efficiency. Finally, the feasibility and effectiveness of the proposed algorithms are demonstrated by the experiments on the designed and actual cases.
... Particle Swarm Optimization (PSO) has been mainly studied for the pipe routing of aero-engines, and it considers the branches of pipes (Asmara and Nienhuis, 2006) and multi-terminal pipe routing (Liu and Wang, 2012). Among the studies that used Dijkstra algorithms is one study that considers pipe elbows and bends (Ando and Kimura, 2012) and another that provides designers with the initial paths of pipes that considers pipe elbows and preferred spaces (S.H. Kim et al., 2013). In the case of aero-engines, there was a study that exhibited higher path-finding speed than PSO using the Dijkstra algorithm (Liu and Wang, 2015). ...
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Previous studies on pipe auto-routing algorithms generally used such algorithms as A∗, Dijkstra, Genetic Algorithm, Particle Swarm Optimization, and Ant Colony Optimization, to satisfy the relevant constraints of its own field and improve the output quality. On the other hand, this study aimed to significantly improve path-finding speed by applying the Jump Point Search (JPS) algorithm, which requires lower search cost than the abovementioned algorithms, for pipe routing. The existing JPS, however, is limited to two-dimensional spaces and can only find the shortest path. Thus, it requires several improvements to be applied to pipe routing. Pipe routing is performed in a three-dimensional space, and the path of piping must be parallel to the axis to minimize its interference with other facilities. In addition, the number of elbows must be reduced to the maximum from an economic perspective, and preferred spaces in the path must also be included. The existing JPS was improved for the pipe routing problem such that it can consider the above-mentioned problem. The fast path-finding speed of the proposed algorithm was verified by comparing it with the conventional A∗ algorithm in terms of resolution.
In this paper we propose a general methodology for the optimal automatic routing of spatial pipelines motivated by a recent collaboration with Ghenova, a leading Naval Engineering company. We provide a minimum cost multicommodity network flow based model for the problem incorporating all the technical requirements for a feasible pipeline routing. A branch-and-cut approach is designed and different matheuristic algorithms are derived for solving efficiently the problem. We report the results of a battery of computational experiments to assess the problem performance as well as a case study of a real-world naval instance provided by our partner company.
Ship pipe route design (SPRD) is one of the most complex and time-consuming processes in ship detail design. Currently, there are many researches on the optimization of ship pipe routes, but there is still a lack of effective and convenient methods to build the pipe routing space. In order to solve this problem, a piping space modeling method for SPRD is proposed. This method is based on stereo lithographic (STL) file which is commonly used in data exchange, and it can convert the initial space model built in 3D-CAD software into the data model required by the pipe routing algorithms. For the application purpose, a piping space modeling utility (PSMU) is developed with Python and OpenGL, promoting the development of practical pipe routing system. Finally, the feasibility and practicability of the proposed method are verified by the experiment on the piping space of an actual ship fuel system.
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All current shipyards are using the customized CAD/CAM programs in order to improve the design quality and increase the design efficiency. Even though the data structures for ship design and construction are almost completed, the implementation related to the ship design processes are still in progress so that it has been the main causes of the bottleneck and delay during the middle of design process. In this study, we thought that the hole-plan system would be a good example which is remained to be improved. The people of outfitting division who don't have direct authority to edit the structural panels, should request the hull design division to install the holes for the outfitting equipment. For acceptance, they should calculate the hole position, determine the hole type, and find the intersected contour of panel. After consideration of the hull people, the requested holes are manually installed on the hull structure. As the above, many processes are needed such as communication and discussion between the divisions, drawings for hole-plan, and the consideration for the structural or production compatibility. However this iterative process takes a lot of working time and requires mental pressure to the related people and cross-division conflict. This paper will handle the hole-plan system in detail to automate the series of process and minimize the human efforts and time-consumption.
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Finding the optimum route of ship pipes is a complicated and time-consuming process. Experience of designers is the main tool in this process. To reduce design man-hours and human errors an expert system shell and a geometric modeling kernel are integrated to automate the design process. Existing algorithms for routing problems have been analyzed - most of them are to solve 2-D circuit routing problems. Design of the ship piping system, especially within the engine room, is a complicated, large-scale 3-D routing problem. Methods of expert systems have been implemented to find the routes of ship pipes on the main deck of a bulk carrier. A framework of the intelligent CAD system for pipe auto-routing is suggested. The CADDS 5 of Computervision is used as the overall CAD environment, the Nexpert Object of Neuron Data is used as the expert system shell, and the CADDS 5 ISSM is used to build user interface through which geometric models of pipes are created and modified.
This paper presents an automatic design method for pipe arrangement. A pipe arrangement design problem is proposed for a space in which many pipes and objects co-exist. This problem includes large-scale numerical optimization and combinatorial optimization problems, as well as two criteria. For these reasons, it is difficult to optimize the problem using usual optimization techniques such as Random Search. Therefore, multi-objective genetic algorithms (GAs) suitable for this problem are developed. A pipe is characterized by both a pattern of generation and numerical parameters. The former describes the way the pipe bends and the latter details the length of the straight parts. For this reason, a combination of the pattern of generation and the numerical parameters is used for the solution representation and a new method of crossover is proposed that takes into account interference with obstacles. As the number of pipes increases, it becomes rapidly more difficult to find feasible solutions where pipes do not interfere with each other. Therefore, two modification operators that transform infeasible solution candidates into feasible ones are introduced. One operator modifies the pipe having a lot of interferences with other pipes so that it will not interfere with them, and the other is related with the operation that modifies the pipe that travels through obstacles. Although there are cases in which pipes cannot completely avoid obstacles in practical designs, this situation is taken into consideration by this design process. The proposed method for optimizing a pipe arrangement efficiently is demonstrated through several experiments, and remarks are provided for applying this methodology to a practical pipe arrangement design.
Finding the optimum route of ship pipes is a complicated and time-consuming process. Experience of designers is the main tool in this process. To reduce design man-hours and human errors an expert system shell and a geometric modeling kernel are integrated to automate the design process. Existing algorithms for routing problems have been analyzed - most of them are to solve 2-D circuit routing problems. Design of the ship piping system, especially within the engine room, is a complicated, large-scale 3-D routing problem. Methods of expert systems have been implemented to find the routes of ship pipes on the main deck of a bulk carrier. A framework of the intelligent CAD system for pipe auto-routing is suggested. The CADDS 5 of Computervision is used as the overall CAD environment, the Nexpert Object of Neuron Data is used as the expert system shell, and the CADDS 5 ISSM is used to build user interface through which geometric models of pipes are created and modified.
抄録 Nowadays, the pipe arrangement has been enabled to be more efficient and economical by development and spread of CAD(Computer-Aided Design). However, it is difficult to design a piping layout automatically because there are many regulations and functional design rules which must be satisfied. We propose an automatic routing method for simple pipes including elbows and bends. In a practical design of a piping layout, there are many bends connecting straight eccentric pipes which have gaps within the pipes' diameter. However, no precedence automatic piping algorithm has been taken into account pipelines with such bends. The proposed method finds piping routes making use of not only elbows but the bends in order to minimize costs of the path connecting start point to goal point, while avoiding obstacles such as structures, equipments and the other circuits. In our approach, we regard the piping route design problem as a routing problem in a directed and weighted graph. Note that the nodes in the proposed graph have state variables not only locations but directions of the pipes. This graph can easily express the bends as simple edges, and then the routing algorithm can easily handle the bends. In addition, the presented method has specifications that the sizes of each cell, which is generated by decomposing of a free space, are not restricted within the diameter of the pipe. The routing algorithm uses Dijkstra's method to provide candidate paths. The efficiency of the proposed method is demonstrated through several experiments
The line expansion algorithm provided by Heynes was a new kind of routing algorithm that took advantage of both Lee's algorithm and linear expansion algorithms, and hence was more efficient. However, it was less efficient in two layer routing situations. In this paper, this problem is analysed and several ways of solving it are proposed. Three criteria are provided in the paper, and these are used in the development of a modified line expansion algorithm. The modified algorithm is not only fast but also consumes less memory in two layer routing situations. Based on this algorithm, a Fortran printed circuit board routing system is built that can solve two layer routing problems with up to 2600 connection lines on a microcomputer with 64 kbyte RAM.