An Expert System Approach to Container Ship Layout Design

AN EXPERT SYSTEM APPROACH TO CONTAINER SHIPLAYOUT DESIGN

S,ebnem Helvacioglu and Mustafa I·nselFaculty of Naval Architecture and Ocean Engineering, Istanbul Technical University,Istanbul, Turkey

Int. Shipbuild. Progr., 50, no. 1 & 2 (2003) pp. 19-34

Received: February 2002Accepted: January 2003

Ship design applications are carried out mainly by human experts who generallyutilise computerised deterministic analysis techniques. Application of stochasticmethods, and formalisation of heuristic methods in computer aided ship design havenot been widely utilised yet. This work investigates whether such a heuristic method,namely expert system approach, can be satisfactorily applied into ship design.An expert system program package called ALDES (Accommodation Layout DesignExpert System) was developed by using CLIPS expert system shell in order to assesthe current approach. Preliminary dimensions of a container ship were calculated bya heuristic approach supported by a database of similar ships, empirical formulation,and deterministic analysis techniques. The hull was subdivided into maincompartments by locating decks, double bottom, and transverse bulkheads. Thenumber of crew was calculated by utilising manning regulations, then thesuperstructure layout was developed by assigning spaces for access, passageways,public and private rooms. Two cases were selected to test the current approach:firstly the effects of design heuristics were analysed in an evacuation analysis, andsecondly a preliminary concept design for a fast containership was conducted. Inconclusion, this study presents a case study approach in which an expert system isapplied into ship design domain successfully with layout design emphasis.

1. Introduction

Expert systems (ESs) have found a wide application area in engineering applicationsalong with the development of Artificial Intelligence (AI) since 1980s [1, 2, 3, 4, 5,6]. Ship design is a complex engineering process due to requirement of largeexpertise and its iterative nature. It also requires a wide dynamic knowledge base asboth national and international rules and regulations are updated every year. Because

20 An expert system approach to container ship layout design

of these interrelated characteristics of ship design, it may be accepted as a suitableapplication domain for ESs.In the current work, an ES program, called ALDES (Accommodation Layout DesignExpert System), has been developed to investigate this approach, and application ofESs to ship design is examined through a case study approach. ALDES has beenestablished using CLIPS expert system shell, an object oriented visual programmingenvironment, and a general purposed CAD tool.

2. Background

The result of a design process is a specification of a proposed object to fulfil apredefined set of requirements within a set of environmental, regulatory, technical,economic, social, ethic and physical constraints [7]. Design of an engineering artefactis usually carried out by an analysis-synthesis-evaluation cycle. In the design ofintegrated systems, an overall analysis is usually not possible and the solution isdivided into a number of manageable parts [2]. These parts can then be analysedindividually and combined to give an overall solution. If the individual parts are notfully independent, integration stage is performed in an iterative method. Ship designinvolves a wide range of tasks; hence integration task is very demanding.Evan’s design spiral was the first structured methodology in ship design [8].However, its limitations were soon realized, and computer assisted techniques wereconsequently developed and utilized as universal tools [1, 3, 7]. At first, computertechnology was used for simple applications facilitating tedious manual tasks in theship design. But lately, researchers have been developing models based on AItechniques and domain knowledge as well as the procedural analysis approaches.Knowledge based design is a model of design process in computer environment in anattempt to capture and render operable human knowledge about the domain. The goalis to represent knowledge in such a way that it is comprehensible to both human andthe computer [9].Facility layout problem refers to design process of a layout for production or servicefacilities. The interest in the facility layout and location problems in the current workis oriented towards exploration of the techniques and methods that can be adopted forlayout design of ship accommodation. Some steps of Systematic Layout Planning(SLP) [10] technique have been utilised to develop an accommodation block layoutfor the current work.

3. Knowledge base

The knowledge base is a part of the expert system, which contains the knowledge andexpertise associated with a particular domain. The general capability of any ES is

S,ebnem Helvacioglu and Mustafa I·nsel 21

determined by the quality of the associated knowledge base [2]. A number of issuesabout knowledge have been evaluated during the development of the current system.

Knowledge elicitationThe main problems associated with the development of ES applications are nearly allconcerned with the process of obtaining the information required to construct theapplication of a specific knowledge base. This process of extracting knowledge fromeither human or non-human sources is often called knowledge elicitation, and is offundamental importance in the development of ES applications.In the current work, interviewing of several domain experts, as well as extractingknowledge from reference books and technical regulations for container ship designsuch as SOLAS [11], ILO [12] and national regulations [13] has been utilised todevelop a knowledge base. Interviews have lead into compilation of heuristics, goodpractices, accepted standards, and judgemental reasoning within container ship designdomain.

Meta KnowledgeKnowledge about design consists of not only rules about how to do tasks but also onwhen to perform the tasks. For example, a designer will know when to calculateweights in order to check weight-displacement balance. This knowledge about orderof tasks is probably the main difference between a designer and spiral based iterativedesign. Designer’s way of process must also involve a conflict resolution, e.g. thestability calculations may indicate an increase in the beam, while poweringcalculations may require a decrease in the beam. This type of knowledge can bereferred to as “meta-knowledge” and can only be extracted through interviews.

Knowledge RepresentationThe basis of knowledge representation in a computer is the organisation and storageof knowledge, which the expert system uses to solve a problem. In the current work,two different types of knowledge representation methods have been employed thosebeing an object oriented hierarchical database, which was utilized for shipcomponents and production rules, which were used to define the expert system.Object oriented database enables the program to locate each entity, which may be aspace or physical object belonging to a class derived from a class tree. Characteristicsabout an entity such as dimensions, volume, weight, etc. have been represented asproperties, and calculations performed on each object, knowledge, have beenrepresented as methods, which can be inherited through class definitions.Production rules have been adopted due to the nature of ship design knowledge in theexpert system. The heuristic knowledge acquired through interviews has beenrepresented as rules, while facts have been utilized to represent dynamic memory. Aproduction system has the form:


IF [condition] THEN [conclusion]The condition part of the rule must be true, to use the conclusion part. Conclusion andcondition relate to the state of the global database. If the condition is true accordingto the working memory, then the conclusion may be added to the working memory.

ReasoningReasoning is the process of creating new facts from existing facts, which mayindicate a property of an object or may indicate some type of calculation is required.Production rules are used to perform reasoning managed by interference engine ofexpert system. In this study CLIPS inference engine has been used with depth firstsearch algorithm.

Explanation of Reasoning

This capability is provided through the compile editor of the CLIPS watch facilityand allows for the Fired rules, asserted and retracted facts to be seen while a programis running.

4. Application

Ship layout design, being a complex problem, is often solved by the utilisation ofheuristics. Typically only some aspects of the problem are considered and one ormore approximate solutions to the problem are created using this restricted version.The resulting solutions are then adjusted to create an acceptable layout and the bestresulting solution is implemented.As a pilot application, an ES for container ship layout design has been developed toinvestigate expert system approach in ship design. Two main tasks in the containership layout design have been selected instead of overall design: “compartmentation”i.e. division of the ship into compartments, and arrangement of the superstructure.The former task allocates functional/spatial units, which make up ship volume; whilethe latter task involves the layout design of one of these functional units. A conceptmodel of these tasks is illustrated in Figure 1, where the roles of ship design process,ES, and knowledge base are shown inclusive of the reasoning logic. For example, themodel includes the determination of number of crew required which in turn effectsboth “compartmentation” and the superstructure layout.


Figure 1. Conceptual model of ALDES.


Two programming paradigms were employed in the development of ALDES: aPascal based visual programming environment was utilised as an interface shell andCLIPS expert system shell was used as the inference engine (see Figure 2). Theinterface shell has functions to input data from the user, to output the results, to keepa database of objects in the design process, to visualise the layout, and to performsome procedural tasks, such as resistance, propulsion calculations, calculation fornumber of containers in the hull etc. This paradigm enabled the expert system part tooperate outside of all usual computerised operations and focus only in the expertsystem heuristics. ES works in a DLL format communicating with user through theinterface shell. It keeps its own agenda and facts list which is modified by theinterface shell whenever it is required. Events, usually calculations, are fired at theinterface shell by checking fact list of CLIPS.

Figure 2. System layout.

In addition to ES utilisation a number of knowledge based design techniques wereadopted in the development of ALDES:


i) Object oriented programming paradigm was utilised for the representation ofship and its components in the interface shell. Hence, ship consists of ahierarchical database of objects. Each object, derived from a class, has propertiessuch as length, width, depth, volume, weight and methods such as weightcalculation, size calculation, procedure of moving etc. In the establishment of thedatabase, object oriented programming paradigm was utilised with inheritance,polymorphism, and encapsulation techniques. With these techniques it waspossible to represent ownership and neighbouring relations, which allows for thedefinition and utilisation of topological relationships of ship sub-components. Inthis hierarchical object tree, each object has an owner and relations to otherobjects, e.g. left, above, below. As an illustration, when a cabin is defined itbelongs to owner deck (Parent) should have been defined. Similarly, surroundingcabins (brothers and sisters) may also be defined, and obviously a cabin willhave objects (as its children) such as a door derived from door class.

ii) Ship has been divided into sub-components in a varying level of detail. Thishierarchical decomposition may be explained by choosing accommodation partas shown in Figure 3. In this figure accommodation part is chosen as the firstlevel decomposition, in its entirety. At the second level each deck of theaccommodation part can separately be taken into account. At the third level aspecific cabin at a selected deck may be examined. Decomposition has a generaldisadvantage as it causes to loose the interactions between sub-components. Thishas been overcomed by building ES heuristic rules for the design of eachcomponent to include the interactions. As a result each component may bedesigned independently but it must include the effects of other sub-components.For example, accommodation block has an algorithm to define the size but italso takes engine room size into account, as two bays of containers are taken ontop of engine room and in front of accommodation block, if the engine room sizeis large enough. Accommodation block design is updated whenever the engineroom size changes.

iii) A technique called systematic layout planning has been utilized to derive therelationships between the cabins in the layout. Table 1 shows an examplerelational chart, which was derived from human flow diagrams for dailyfunctions, emergency operations, and from considerations of fire, flooding,social relations and from heuristics extracted from the interviews [2]. Thisrelational chart was utilised in the layout design process as production rules. Thenumber designation used in Table 1 are explained by Table 2 and Table 3.


Figure 3. Decomposition.


Table 1. Relational chart for the sample ship.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

1 A U E O U A I U E O U I O X X I U U X X X X A X U I

2 E E A O E I O I O U O O X X O O U X X X X E X U I

3 U O E U U I U I E O O X X O O U X X X X U X U U

4 E U I I U U O O I O X X I E X X X X U I X U I

5 U I U U U U U I O X X I U X X X X U I X U U

6 U U I U E I I O X X I O X X X X E U X U U

7 U U U U O I O X X I O X X X X U A X U I

8 U U U O I O X X I O X X X X U U X U I

9 U U I I O X X I O X X X X E U X U U

10 U O I O X X I O X X X X O U X U U

11 I I O X X I O X X X X I U X U U

12 U O O X U U X U U U I U X U U

13 E X E U O U U U X U U I U U

14 U I I U O U U U U U I U U

15 E X U U U U I X U U U X

16 E U A U A U U U I A U

17 U U U U X U U I U U

18 U U X U X U X U U

19 U I U U U U U U

20 U U U U U U X

21 U U U U U X

22 X U I U X

23 U U U X

24 X U U

25 U X

26 X

27

Relations: A: Absolutely necessary, E: Especially important, I: Important, O: Ordinary importance,U: Unimportant, X: Undesirable

Table 2. Crew members and cabins related to crew according to the program.

No Crew Member Duty Number No Crew Member Duty Number

2 Oceangoing-master 1 22 Able-seaman 2

4 Oceangoing-chief-officer 1 22 Ordinary-seaman 3

8 Oceangoing-watchkeeping officer 1 22 Deckboy 1

3 Unlimited-chief-engineer 1 19 Cook 1

6 Unlimited-second-engineer 1 25 Steward 1

9 Unlimited-engineer-officer 1 22 Donkyman 1

7 Radio-officer 1 22 Oiler 3

11 Electrician 1 22 Wiper 1

22 Boatswain 1 - -

Total Number of Crew: 22


Table 3. The other compartments in the accommodation part.

No Name of the Section Number No Name of the Section Number

5 Owner 1 16 Galley 1

1 Bridge 1 18 Hospital 1

24 Radio-room 1 15 Crew-mess-room 1

27 Deck-office 1 Store-3 1

12 Engine-office 1 Store-2 1

17 Officer-dining-room 1 Store-1 1

13 Officer-day-room 1 20 Laundry 1

10 Pilot 1 21 Cold-room 1

14 Pantry 1 26 Dry-provision 1

4.1. Structure of knowledge base

ALDES consists of three integrated task modules of ship design.

Task Module A: General arrangement plan

Task Module A aims to generate a general arrangement plan by decomposing shipconcept into hierarchical components such as bow, cargo holds, engine room, sternand accommodation space. Only first level of decomposition is utilised in thismodule.Ship size is calculated by use of sub-compartments integration and by takingconsiderations of total volume, area and location requirements. Sub-tasks as listedbelow are performed a number of times in a non-orderly iterative manner:i) Ship main dimensions are determined form deck area, and volume requirements.ii) Ship resistance, engine power, propeller efficiency, engine room size and fuel

consumption are calculated.iii) Double bottom, main deck and main transverse bulkheads are located.iv) The accommodation part is determined, the size and the number of the

accommodation decks are calculated. General heuristics are used to calculatecrew size.

v) First approach to weight and weight distribution is made and updated as moredata becomes available.

vi) Preliminary assessment of stability is made and ballast requirement isdetermined.

vii) Container capacity under main deck is calculated.

The basic requirements to start the design are speed, capacity (number of TEU), shiprange and initial hull form of the ship. These inputs are handled by Interface shell andare fed into CLIPS as facts.


Task Module B: Crew number calculation

This module was developed to determine required crew number. The knowledge baseof the program was prepared by extracting the knowledge from regulations [14].Crew number module seeks gross tonnage (GRT), engine power and range of thedesigned ship to fire the rules. Owner selected crew; number of cooks, stewards,electricians, etc. can be entered as preferences by the user. This information is thenutilised in the next modules to define the superstructure layout.

Task Module C: Accommodation layout

Accommodation layout is performed in three steps:1. requirement definition, i.e. determination of required cabin numbers and their

sizes,2. arrangement of cabins, i.e. relations and locations,3. calculation of a cost function.

The first step of accommodation layout defines name, statue and area for both crewmembers’ cabins, public rooms, and other spaces such as stores, galleys, etc. Arearequirement of each room is calculated as required by ILO and IMO regulations, andcommon practicesA Relational Chart is incorporated to define the topology of the accommodationblock. The information from this chart and space requirements for each cabin is usedto decide deck levels for each cabin. When decks are fully defined the cabins in eachdeck are located, and final sizes are determined.A cost factor is calculated for different scenarios in order to provide a ranking facilitybetween various design strategies. Design strategy can easily be altered by makingchanges in the meta-knowledge.

4.2. Case studies

Case study approach has been adopted to assess and validate the program. Twoapplications of program were developed: Firstly a container ship with 750 TEU wasselected and two alternative layouts were developed by varying decision rules. A costfunction was defined as the distance for every personnel from their room to a safetypoint, which is assumed to be on the third deck acting as the boat deck forevacuation. Secondly, a search for an unusual containership carrying 1000 TEU at 30knots speed was made.

Case Study I: Effect of design strategyOne of the main design concerns is to find answers to “what-if” questions. Thisapproach has been adopted in a large number of design studies only in the microlevel,i.e. effect of a variable such as beam, depth etc. is investigated and the effect of thischange on the overall design and cost function is observed. From this information,


sensitivity of the design for this parameter can be determined, or design can beoptimised for this parameter. In this study, a fundamentally different approach isadopted whereby instead of changing a design parameter the design strategy ischanged.In the first case study a containership of 750 passenger at 16 knots is developed. Theaccommodation block is developed and a deck layout is given as an example inFigure 4a. As a change in the design strategy, the heuristics about the locations ofdoors for each cabin has been changed. For the first case, the cabin doors werepositioned in the nearest position to the staircase or safety point. In the second casethe doors were located without the minimum distance rules. Typical door positionsare given in Figure 4a and Figure 4b.

Figure 4 a and b. Example deck for the second case.

The cost function was chosen as the total evacuation distance for the whole crew.And it was calculated with respect to the crew’s normal operating/resting locations,i.e. working posts and living areas. A few sample results from the outputs are givenin Table 4 for comparison purposes. These two simple case studies illustrate that witha computer system such as ALDES, ship design strategy changes can be evaluatedwith respect to the selected cost function.


Table 4. Comparison of two cases.

Short distance case Long distance casePerson : donkeymandistance from centre to door : 4665distance from door to point : 1073distance from point to stair : 5423distance from stair to deck : -4000total distance : 15161

Person : donkeymandistance from centre to door : 4422distance from door to point : 2110distance from point to stair : 5423distance from stair to deck : -4000total distance : 15956

person : oceangoing-masterdistance from centre to door : 3033distance from door to stair : 1011distance from stair to deck : 6000total distance : 10044

person : oceangoing-masterdistance from centre to door : 3335distance from door to stair : 1930distance from stair to deck : 6000total distance : 11265

Person : stewarddistance from centre to door : 1550distance from door to point : 1073distance from point to stair : 943distance from stair to deck : -4000total distance : 7566

person : stewarddistance from centre to door : 450distance from door to point : 2110distance from point to stair : 943distance from stair to deck : -4000total distance : 7503

Person : ownerdistance from centre to door : 6308distance from door to stair : 2926distance from stair to deck : 6000total distance : 15235

Person : ownerdistance from centre to door : 4250distance from door to stair : 4930distance from stair to deck : 6000total distance : 15180

Person : radio-officerdistance from centre to door : 2550distance from door to stair : 626distance from stair to deck : 4000total distance : 7176

Person : radio-officerdistance from centre to door : 2550distance from door to stair : 626distance from stair to deck : 4000total distance : 7176

Case Study II: Concept design of unusual shipsConcept design of unusual ships is difficult to model with the usual design spiral.This task is usually performed by the designer’s heuristics combined with theavailable analysis techniques. As an alternative, a concept exploration model can bedefined [15]. The main difficulty in concept exploration is the quantity of data andthe post-processing especially if the number of variables is large. In the current worka variation of concept exploration model was used for concept design of a fastcontainership carrying approximately 1000 TEU at 30 knots. In order to reduce theamount of data produced with concept exploration, some of the variables are chosenby heuristics rules. Only the effect of number of piers and rows were left for thedesigner. A cost criterion was defined as fuel consumption per TEU-mile, and aselection process was performed. Figure 5 shows general arrangement of 1000 TEU30 knot containership as defined in ALDES and Figure 6 shows fuel consumption perTEU-Mile and GM/Breadth ratio by change of number of tiers (Ny) and rows (Nz)


without ballast weight change. Smallest number of container rows and tiers results inleast cost as expected from a long slender ship with high powered ship concept, butstability criteria, as GM/B Ratio, dictates increase in number of rows. Large numberof tiers is ruled out, and a compromise must be reached by addition of ballast as wellas increasing number of rows.

Figure 5. General arrangement.

Figure 6. The result of the case study.


5. Conclusion

In this study, development of an expert system called ALDES has been presentedwhere the adopted system model implements logical reason methods both forgenerative and interpretative knowledge. It is shown that such a system can have agreat potential for utilisation in the ship layout design process.Hierarchical decomposition of ship object into sub-components has proved to be avery useful tool. This approach allowed for the development of program modules todesign each sub-component independently and yet also allowed for the utilisation ofheuristics for integration. The main advantage of this approach over the conventionaldesign spiral is to include integration heuristics within each sub-component designmodule.Use of the calculated evacuation distance as a cost function is found to be useful. Asan illustration it was applied for two cases to examine the effect of changing thedesign strategy with respect to cabin door locations on the cost function.The main advantage of the expert system appears to be the ability to design a shipsimply generating a general arrangement plan with the backing of rule, knowledge,and calculation base, similar to the way a domain expert performs his design. Such anapproach also increases the efficiency of communication between the expert systemand the user.

Acknowledgements

The authors wish to express their thanks to domain experts; S. Aka, S. Börü, O. Dayı,A. Demirsoylu, G. Göke, T. Gürsel, A.Y. Odabas,ı, H. S,is,manyazıcı, D.G.M. Watson,Welsh who shared their expertise on containership design through knowledgeextraction interviews.

References

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An Expert System Approach to Container Ship Layout Design